�ݺ�ߣshows by User: PAWDeutschland

�ݺ�ߣshows by User: PAWDeutschland / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: PAWDeutschland / Tue, 10 Dec 2019 10:04:57 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: PAWDeutschland Data Science at Roche: From Exploration to Productionization - Frank Block /PAWDeutschland/data-science-at-roche-from-exploration-to-productionization 0905block-191210100457
The excitement about the potential opportunities for leveraging data by means of advanced analytics is huge. But, the honeymoon between business and data science is over. Stakeholders want to see value generation from data science. At Roche Diagnostics the Data Science Lab was created. Its mission is to explore business opportunities for data science across the company and to deliver productive, algorithm based systems that create impact. In his keynote, Frank presented some examples of data science initiatives going from data exploration over predictive modelling to productionization. Some of the challenges encountered were addressed as well as the learnings.]]>
The excitement about the potential opportunities for leveraging data by means of advanced analytics is huge. But, the honeymoon between business and data science is over. Stakeholders want to see value generation from data science. At Roche Diagnostics the Data Science Lab was created. Its mission is to explore business opportunities for data science across the company and to deliver productive, algorithm based systems that create impact. In his keynote, Frank presented some examples of data science initiatives going from data exploration over predictive modelling to productionization. Some of the challenges encountered were addressed as well as the learnings.]]> Tue, 10 Dec 2019 10:04:57 GMT /PAWDeutschland/data-science-at-roche-from-exploration-to-productionization PAWDeutschland@slideshare.net(PAWDeutschland) Data Science at Roche: From Exploration to Productionization - Frank Block PAWDeutschland The excitement about the potential opportunities for leveraging data by means of advanced analytics is huge. But, the honeymoon between business and data science is over. Stakeholders want to see value generation from data science. At Roche Diagnostics the Data Science Lab was created. Its mission is to explore business opportunities for data science across the company and to deliver productive, algorithm based systems that create impact. In his keynote, Frank presented some examples of data science initiatives going from data exploration over predictive modelling to productionization. Some of the challenges encountered were addressed as well as the learnings. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/0905block-191210100457-thumbnail.jpg?width=120&height=120&fit=bounds" /> The excitement about the potential opportunities for leveraging data by means of advanced analytics is huge. But, the honeymoon between business and data science is over. Stakeholders want to see value generation from data science. At Roche Diagnostics the Data Science Lab was created. Its mission is to explore business opportunities for data science across the company and to deliver productive, algorithm based systems that create impact. In his keynote, Frank presented some examples of data science initiatives going from data exploration over predictive modelling to productionization. Some of the challenges encountered were addressed as well as the learnings.

Data Science at Roche: From Exploration to Productionization - Frank Block from Rising Media Ltd.

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0 Cost-Effective Personalisation Platform for 30M Users of Ringier Axel Springer - Piotr Turek and Michal Zmuda /PAWDeutschland/costeffective-personalisation-platform-for-30m-users-of-ringier-axel-springer 1135turekzmuda-191209081549
Profit margins in the digital publishing business leave no place for flirting with expensive experiments. How to choose an appropriate approach to personalization that works well not only in theory but in the real world? How to ensure cost-efficiency & future-proofness not covered by academic research? How to respond to changing business requirements in no time? Draw from the experience of building a pragmatic, real-world personalization platform for 30M users of Ringier Axel Springer.]]>
Profit margins in the digital publishing business leave no place for flirting with expensive experiments. How to choose an appropriate approach to personalization that works well not only in theory but in the real world? How to ensure cost-efficiency & future-proofness not covered by academic research? How to respond to changing business requirements in no time? Draw from the experience of building a pragmatic, real-world personalization platform for 30M users of Ringier Axel Springer.]]> Mon, 09 Dec 2019 08:15:49 GMT /PAWDeutschland/costeffective-personalisation-platform-for-30m-users-of-ringier-axel-springer PAWDeutschland@slideshare.net(PAWDeutschland) Cost-Effective Personalisation Platform for 30M Users of Ringier Axel Springer - Piotr Turek and Michal Zmuda PAWDeutschland Profit margins in the digital publishing business leave no place for flirting with expensive experiments. How to choose an appropriate approach to personalization that works well not only in theory but in the real world? How to ensure cost-efficiency & future-proofness not covered by academic research? How to respond to changing business requirements in no time? Draw from the experience of building a pragmatic, real-world personalization platform for 30M users of Ringier Axel Springer. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1135turekzmuda-191209081549-thumbnail.jpg?width=120&height=120&fit=bounds" /> Profit margins in the digital publishing business leave no place for flirting with expensive experiments. How to choose an appropriate approach to personalization that works well not only in theory but in the real world? How to ensure cost-efficiency & future-proofness not covered by academic research? How to respond to changing business requirements in no time? Draw from the experience of building a pragmatic, real-world personalization platform for 30M users of Ringier Axel Springer.

Cost-Effective Personalisation Platform for 30M Users of Ringier Axel Springer - Piotr Turek and Michal Zmuda from Rising Media Ltd.

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0 Uplift Modelling as a Tool for Making Causal Inferences at Shopify - Mojan Hamed /slideshow/uplift-modelling-as-a-tool-for-making-causal-inferences-at-shopify/201903116 1205hamed-191205144421
For many businesses, it is not enough to model the probability of an outcome but rather, “given a predictive model, what can we do to change the probability of this outcome?” The goal of this talk is to present how uplift modelling is used to make causal inferences that guide acquisition strategy at Shopify. Mojan will walk through a case study focused on the statistics and experimental design behind uplift modelling, in addition to the learnings gained from bringing this model to production. The python implementation of this presentation will be made available to attendees.]]>
For many businesses, it is not enough to model the probability of an outcome but rather, “given a predictive model, what can we do to change the probability of this outcome?” The goal of this talk is to present how uplift modelling is used to make causal inferences that guide acquisition strategy at Shopify. Mojan will walk through a case study focused on the statistics and experimental design behind uplift modelling, in addition to the learnings gained from bringing this model to production. The python implementation of this presentation will be made available to attendees.]]> Thu, 05 Dec 2019 14:44:21 GMT /slideshow/uplift-modelling-as-a-tool-for-making-causal-inferences-at-shopify/201903116 PAWDeutschland@slideshare.net(PAWDeutschland) Uplift Modelling as a Tool for Making Causal Inferences at Shopify - Mojan Hamed PAWDeutschland For many businesses, it is not enough to model the probability of an outcome but rather, “given a predictive model, what can we do to change the probability of this outcome?” The goal of this talk is to present how uplift modelling is used to make causal inferences that guide acquisition strategy at Shopify. Mojan will walk through a case study focused on the statistics and experimental design behind uplift modelling, in addition to the learnings gained from bringing this model to production. The python implementation of this presentation will be made available to attendees. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1205hamed-191205144421-thumbnail.jpg?width=120&height=120&fit=bounds" /> For many businesses, it is not enough to model the probability of an outcome but rather, “given a predictive model, what can we do to change the probability of this outcome?” The goal of this talk is to present how uplift modelling is used to make causal inferences that guide acquisition strategy at Shopify. Mojan will walk through a case study focused on the statistics and experimental design behind uplift modelling, in addition to the learnings gained from bringing this model to production. The python implementation of this presentation will be made available to attendees.

Uplift Modelling as a Tool for Making Causal Inferences at Shopify - Mojan Hamed from Rising Media Ltd.

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0 Behind the Buzzword: Understanding Customer Data Platforms in the Light of Predictive Analytics - David Raab /slideshow/behind-the-buzzword-understanding-customer-data-platforms-in-the-light-of-predictive-analytics/201902687 1345raab-191205144306
Customer Data Platform (CDP) systems are the newest answer to an old question: how to assemble a complete view of each customer. This session explores the reality of what CDPs can and cannot do, how CDPs differ from other systems, the types of CDP systems available, and how to find the right CDP for your purpose, especially with regard to data science projects and predictive modeling. You will come away with a clear understanding of where CDP fits into the larger data management landscape, what distinguishes CDP from older approaches to customer data management, and the state of the CDP industry in Europe. ]]>
Customer Data Platform (CDP) systems are the newest answer to an old question: how to assemble a complete view of each customer. This session explores the reality of what CDPs can and cannot do, how CDPs differ from other systems, the types of CDP systems available, and how to find the right CDP for your purpose, especially with regard to data science projects and predictive modeling. You will come away with a clear understanding of where CDP fits into the larger data management landscape, what distinguishes CDP from older approaches to customer data management, and the state of the CDP industry in Europe. ]]> Thu, 05 Dec 2019 14:43:06 GMT /slideshow/behind-the-buzzword-understanding-customer-data-platforms-in-the-light-of-predictive-analytics/201902687 PAWDeutschland@slideshare.net(PAWDeutschland) Behind the Buzzword: Understanding Customer Data Platforms in the Light of Predictive Analytics - David Raab PAWDeutschland Customer Data Platform (CDP) systems are the newest answer to an old question: how to assemble a complete view of each customer. This session explores the reality of what CDPs can and cannot do, how CDPs differ from other systems, the types of CDP systems available, and how to find the right CDP for your purpose, especially with regard to data science projects and predictive modeling. You will come away with a clear understanding of where CDP fits into the larger data management landscape, what distinguishes CDP from older approaches to customer data management, and the state of the CDP industry in Europe. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1345raab-191205144306-thumbnail.jpg?width=120&height=120&fit=bounds" /> Customer Data Platform (CDP) systems are the newest answer to an old question: how to assemble a complete view of each customer. This session explores the reality of what CDPs can and cannot do, how CDPs differ from other systems, the types of CDP systems available, and how to find the right CDP for your purpose, especially with regard to data science projects and predictive modeling. You will come away with a clear understanding of where CDP fits into the larger data management landscape, what distinguishes CDP from older approaches to customer data management, and the state of the CDP industry in Europe.

Behind the Buzzword: Understanding Customer Data Platforms in the Light of Predictive Analytics - David Raab from Rising Media Ltd.

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0 Data Science Development Lifecycle - Everyone Talks About it, Nobody Really Knows How to Do it and Everyone Else is Doing It - Christian Lindenlaub and Rene Traue /slideshow/data-science-development-lifecycle-everyone-talks-about-it-nobody-really-knows-how-to-doit-and-everyone-else-is-doing-it/201898887 1030trauelindenlaub-191205143131
Data science is rapidly becoming the primary catalyst for product innovation. However, most of the projects are stuck in the Proof-of-Concept (POC) phase. Christian and René had the chance to be part of GfK’s journey from a traditional market research company to a prescriptive data analytics provider. In order to build end-to-end data-driven products successfully, it is necessary to blend what existing frameworks like SCRUM and CRISP provide with the best practices from software engineering. You will learn about how they gradually established a data science development lifecycle that overcomes the POC-trap by considering production realities from day 1. Leveraging core concepts like KPI-driven development and micro-services they are able to successfully develop, deploy, scale and maintain data science models in production. ]]>
Data science is rapidly becoming the primary catalyst for product innovation. However, most of the projects are stuck in the Proof-of-Concept (POC) phase. Christian and René had the chance to be part of GfK’s journey from a traditional market research company to a prescriptive data analytics provider. In order to build end-to-end data-driven products successfully, it is necessary to blend what existing frameworks like SCRUM and CRISP provide with the best practices from software engineering. You will learn about how they gradually established a data science development lifecycle that overcomes the POC-trap by considering production realities from day 1. Leveraging core concepts like KPI-driven development and micro-services they are able to successfully develop, deploy, scale and maintain data science models in production. ]]> Thu, 05 Dec 2019 14:31:30 GMT /slideshow/data-science-development-lifecycle-everyone-talks-about-it-nobody-really-knows-how-to-doit-and-everyone-else-is-doing-it/201898887 PAWDeutschland@slideshare.net(PAWDeutschland) Data Science Development Lifecycle - Everyone Talks About it, Nobody Really Knows How to Do it and Everyone Else is Doing It - Christian Lindenlaub and Rene Traue PAWDeutschland Data science is rapidly becoming the primary catalyst for product innovation. However, most of the projects are stuck in the Proof-of-Concept (POC) phase. Christian and René had the chance to be part of GfK’s journey from a traditional market research company to a prescriptive data analytics provider. In order to build end-to-end data-driven products successfully, it is necessary to blend what existing frameworks like SCRUM and CRISP provide with the best practices from software engineering. You will learn about how they gradually established a data science development lifecycle that overcomes the POC-trap by considering production realities from day 1. Leveraging core concepts like KPI-driven development and micro-services they are able to successfully develop, deploy, scale and maintain data science models in production. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1030trauelindenlaub-191205143131-thumbnail.jpg?width=120&height=120&fit=bounds" /> Data science is rapidly becoming the primary catalyst for product innovation. However, most of the projects are stuck in the Proof-of-Concept (POC) phase. Christian and René had the chance to be part of GfK’s journey from a traditional market research company to a prescriptive data analytics provider. In order to build end-to-end data-driven products successfully, it is necessary to blend what existing frameworks like SCRUM and CRISP provide with the best practices from software engineering. You will learn about how they gradually established a data science development lifecycle that overcomes the POC-trap by considering production realities from day 1. Leveraging core concepts like KPI-driven development and micro-services they are able to successfully develop, deploy, scale and maintain data science models in production.

Data Science Development Lifecycle - Everyone Talks About it, Nobody Really Knows How to Do it and Everyone Else is Doing It - Christian Lindenlaub and Rene Traue from Rising Media Ltd.

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0 Creating Community at WeWork through Graph Embeddings with node2vec - Karry Lu /PAWDeutschland/creating-community-at-wework-through-graph-embeddings-with-node2vec-karry-lu 1350lu-190529103314
Embeddings have become a powerful tool for representing discrete entities as continuous vectors. Recent advances have extended the original text embedding framework to accommodate new types of data. Of particular interest is a novel algorithm called “node2vec” that learns embeddings for nodes in a network. This is an especially pertinent use case for our team, since WeWork’s member community can conveniently be expressed in graphical form. In this talk, we’ll discuss how we use “node2vec” to create rich feature representations of WeWork communities, and then build recommendation services that are powered by these trained models. ]]>
Embeddings have become a powerful tool for representing discrete entities as continuous vectors. Recent advances have extended the original text embedding framework to accommodate new types of data. Of particular interest is a novel algorithm called “node2vec” that learns embeddings for nodes in a network. This is an especially pertinent use case for our team, since WeWork’s member community can conveniently be expressed in graphical form. In this talk, we’ll discuss how we use “node2vec” to create rich feature representations of WeWork communities, and then build recommendation services that are powered by these trained models. ]]> Wed, 29 May 2019 10:33:14 GMT /PAWDeutschland/creating-community-at-wework-through-graph-embeddings-with-node2vec-karry-lu PAWDeutschland@slideshare.net(PAWDeutschland) Creating Community at WeWork through Graph Embeddings with node2vec - Karry Lu PAWDeutschland Embeddings have become a powerful tool for representing discrete entities as continuous vectors. Recent advances have extended the original text embedding framework to accommodate new types of data. Of particular interest is a novel algorithm called “node2vec” that learns embeddings for nodes in a network. This is an especially pertinent use case for our team, since WeWork’s member community can conveniently be expressed in graphical form. In this talk, we’ll discuss how we use “node2vec” to create rich feature representations of WeWork communities, and then build recommendation services that are powered by these trained models. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1350lu-190529103314-thumbnail.jpg?width=120&height=120&fit=bounds" /> Embeddings have become a powerful tool for representing discrete entities as continuous vectors. Recent advances have extended the original text embedding framework to accommodate new types of data. Of particular interest is a novel algorithm called “node2vec” that learns embeddings for nodes in a network. This is an especially pertinent use case for our team, since WeWork’s member community can conveniently be expressed in graphical form. In this talk, we’ll discuss how we use “node2vec” to create rich feature representations of WeWork communities, and then build recommendation services that are powered by these trained models.

Creating Community at WeWork through Graph Embeddings with node2vec - Karry Lu from Rising Media Ltd.

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0 More than 10 Blue Links: Advanced-Level SERP Optimisation /slideshow/more-than-10-blue-links-advancedlevel-serp-optimisation/140430897 1600petrovic-190411083436
In his talk at SMX Munich 2019, Dan Petrovic highlighted one emerging aspect of Google search - no search at all! We're talking about Google Discover, a machine learning content delivery platform that provides, "queryless" results served to users based on their interests, location and user behaviour. Discover already brings enormous traffic to those who show up on the feed, but remarkably remains largely under the radar by majority of the marketing community. Only days after Dan's presentation, Google started rolling out Discover performance report in Search Console. Find out more: https://dejanseo.com.au/discover/]]>
In his talk at SMX Munich 2019, Dan Petrovic highlighted one emerging aspect of Google search - no search at all! We're talking about Google Discover, a machine learning content delivery platform that provides, "queryless" results served to users based on their interests, location and user behaviour. Discover already brings enormous traffic to those who show up on the feed, but remarkably remains largely under the radar by majority of the marketing community. Only days after Dan's presentation, Google started rolling out Discover performance report in Search Console. Find out more: https://dejanseo.com.au/discover/]]> Thu, 11 Apr 2019 08:34:36 GMT /slideshow/more-than-10-blue-links-advancedlevel-serp-optimisation/140430897 PAWDeutschland@slideshare.net(PAWDeutschland) More than 10 Blue Links: Advanced-Level SERP Optimisation PAWDeutschland In his talk at SMX Munich 2019, Dan Petrovic highlighted one emerging aspect of Google search - no search at all! We're talking about Google Discover, a machine learning content delivery platform that provides, "queryless" results served to users based on their interests, location and user behaviour. Discover already brings enormous traffic to those who show up on the feed, but remarkably remains largely under the radar by majority of the marketing community. Only days after Dan's presentation, Google started rolling out Discover performance report in Search Console. Find out more: https://dejanseo.com.au/discover/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1600petrovic-190411083436-thumbnail.jpg?width=120&height=120&fit=bounds" /> In his talk at SMX Munich 2019, Dan Petrovic highlighted one emerging aspect of Google search - no search at all! We're talking about Google Discover, a machine learning content delivery platform that provides, "queryless" results served to users based on their interests, location and user behaviour. Discover already brings enormous traffic to those who show up on the feed, but remarkably remains largely under the radar by majority of the marketing community. Only days after Dan's presentation, Google started rolling out Discover performance report in Search Console. Find out more: https://dejanseo.com.au/discover/

More than 10 Blue Links: Advanced-Level SERP Optimisation from Rising Media Ltd.

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0 How to Get Great Results Across Every Marketing Channel /slideshow/how-to-get-great-results-across-every-marketing-channel/125607552 1345kim-181211135759
By now, most companies are doing Google & Facebook marketing (both paid and organic)-yet 99% of these marketing efforts end up going nowhere. This session will explore data that explains why the vast majority of internet marketing efforts fail. And now? Larry will provide an unusual, repeatable workflow on how to beat the Facebook & Google algorithms in 2018 and beyond. ● 99% of marketing efforts end up going nowhere ● Beat the Facebook & Google algorithms in 2018 and beyond ● Unusual, repeatable workflow]]>
By now, most companies are doing Google & Facebook marketing (both paid and organic)-yet 99% of these marketing efforts end up going nowhere. This session will explore data that explains why the vast majority of internet marketing efforts fail. And now? Larry will provide an unusual, repeatable workflow on how to beat the Facebook & Google algorithms in 2018 and beyond. ● 99% of marketing efforts end up going nowhere ● Beat the Facebook & Google algorithms in 2018 and beyond ● Unusual, repeatable workflow]]> Tue, 11 Dec 2018 13:57:59 GMT /slideshow/how-to-get-great-results-across-every-marketing-channel/125607552 PAWDeutschland@slideshare.net(PAWDeutschland) How to Get Great Results Across Every Marketing Channel PAWDeutschland By now, most companies are doing Google & Facebook marketing (both paid and organic)-yet 99% of these marketing efforts end up going nowhere. This session will explore data that explains why the vast majority of internet marketing efforts fail. And now? Larry will provide an unusual, repeatable workflow on how to beat the Facebook & Google algorithms in 2018 and beyond. ● 99% of marketing efforts end up going nowhere ● Beat the Facebook & Google algorithms in 2018 and beyond ● Unusual, repeatable workflow <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1345kim-181211135759-thumbnail.jpg?width=120&height=120&fit=bounds" /> By now, most companies are doing Google & Facebook marketing (both paid and organic)-yet 99% of these marketing efforts end up going nowhere. This session will explore data that explains why the vast majority of internet marketing efforts fail. And now? Larry will provide an unusual, repeatable workflow on how to beat the Facebook & Google algorithms in 2018 and beyond. ● 99% of marketing efforts end up going nowhere ● Beat the Facebook & Google algorithms in 2018 and beyond ● Unusual, repeatable workflow

How to Get Great Results Across Every Marketing Channel from Rising Media Ltd.

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0 Don’t Freak Out! Tips for Mobile and Voice Search /slideshow/tipps-um-die-mobile-suche-und-die-sprachsuche-2018-und-in-zukunft-zu-meistern-125606794/125606794 0900gifford-181211134614
Mobile search overtook desktop search in less than five years... Mobile searches are inherently local, yet most digital marketers don't use Local SEO tactics. In this epic keynote session, Greg will cover the rise of mobile searches and how the landscape has changed for both organic and paid search. He'll share specific tactics to help you succeed in mobile searches in 2018. Even more shocking than the fast rise of mobile search, voice search went from zero to 10% in less than one year. Google recently announced that 20% of all mobile searches are voice based. Greg will share specific examples and tactics for voice search to help you prepare for the massive shift in search behavior that's already started. Are you ready for a Star Trek world where users simply talk to their mobile computers? We're living in that world already, and this session will make sure you're able to compete in 2018 and beyond. ● We are already living in a Star Trek world ● The rise of mobile searches and voice search causes massive changes ● Implications for organic and paid search, and how to compete in the future]]>
Mobile search overtook desktop search in less than five years... Mobile searches are inherently local, yet most digital marketers don't use Local SEO tactics. In this epic keynote session, Greg will cover the rise of mobile searches and how the landscape has changed for both organic and paid search. He'll share specific tactics to help you succeed in mobile searches in 2018. Even more shocking than the fast rise of mobile search, voice search went from zero to 10% in less than one year. Google recently announced that 20% of all mobile searches are voice based. Greg will share specific examples and tactics for voice search to help you prepare for the massive shift in search behavior that's already started. Are you ready for a Star Trek world where users simply talk to their mobile computers? We're living in that world already, and this session will make sure you're able to compete in 2018 and beyond. ● We are already living in a Star Trek world ● The rise of mobile searches and voice search causes massive changes ● Implications for organic and paid search, and how to compete in the future]]> Tue, 11 Dec 2018 13:46:14 GMT /slideshow/tipps-um-die-mobile-suche-und-die-sprachsuche-2018-und-in-zukunft-zu-meistern-125606794/125606794 PAWDeutschland@slideshare.net(PAWDeutschland) Don’t Freak Out! Tips for Mobile and Voice Search PAWDeutschland Mobile search overtook desktop search in less than five years... Mobile searches are inherently local, yet most digital marketers don't use Local SEO tactics. In this epic keynote session, Greg will cover the rise of mobile searches and how the landscape has changed for both organic and paid search. He'll share specific tactics to help you succeed in mobile searches in 2018. Even more shocking than the fast rise of mobile search, voice search went from zero to 10% in less than one year. Google recently announced that 20% of all mobile searches are voice based. Greg will share specific examples and tactics for voice search to help you prepare for the massive shift in search behavior that's already started. Are you ready for a Star Trek world where users simply talk to their mobile computers? We're living in that world already, and this session will make sure you're able to compete in 2018 and beyond. ● We are already living in a Star Trek world ● The rise of mobile searches and voice search causes massive changes ● Implications for organic and paid search, and how to compete in the future <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/0900gifford-181211134614-thumbnail.jpg?width=120&height=120&fit=bounds" /> Mobile search overtook desktop search in less than five years... Mobile searches are inherently local, yet most digital marketers don't use Local SEO tactics. In this epic keynote session, Greg will cover the rise of mobile searches and how the landscape has changed for both organic and paid search. He'll share specific tactics to help you succeed in mobile searches in 2018. Even more shocking than the fast rise of mobile search, voice search went from zero to 10% in less than one year. Google recently announced that 20% of all mobile searches are voice based. Greg will share specific examples and tactics for voice search to help you prepare for the massive shift in search behavior that's already started. Are you ready for a Star Trek world where users simply talk to their mobile computers? We're living in that world already, and this session will make sure you're able to compete in 2018 and beyond. ● We are already living in a Star Trek world ● The rise of mobile searches and voice search causes massive changes ● Implications for organic and paid search, and how to compete in the future

Don’t Freak Out! Tips for Mobile and Voice Search from Rising Media Ltd.

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0 The Scout24 Data Landscape Manifesto: Building an Opinionated Data Platform /slideshow/the-scout24-data-landscape-manifesto-building-an-opinionated-data-platform/124352212 thescout24datalandscapemanifesto-181129091042
The Scout24 Data Landscape Manifesto is the formalization of our opinions on how a successful data-driven company should approach data. In a truly data-driven company, no manager, no salesperson, no engineer and no data scientist can do their job properly without easy access to large amounts of high-quality data. It is Sean's mandate to create a platform that encourages the production of high-quality data and enables engagement with data by all employees. He and his team are opinionated about how all producers and consumers of data need to be active participants in the data platform, to make data-driven decisions and to be responsible for the data they produce. And he built the data platform with 'nudges' that reward data usage that matches his vision for a data-driven company. In this talk, Sean will present the Scout24 Data Landscape Manifesto and will show how the strong opinions it contains enabled him to successfully migrate from a classic centralized data warehouse to a decentralized, scalable, cloud-based data platform at AutoScout24 and ImmobilienScout24 that is core to their analytics and machine learning activities.]]>
The Scout24 Data Landscape Manifesto is the formalization of our opinions on how a successful data-driven company should approach data. In a truly data-driven company, no manager, no salesperson, no engineer and no data scientist can do their job properly without easy access to large amounts of high-quality data. It is Sean's mandate to create a platform that encourages the production of high-quality data and enables engagement with data by all employees. He and his team are opinionated about how all producers and consumers of data need to be active participants in the data platform, to make data-driven decisions and to be responsible for the data they produce. And he built the data platform with 'nudges' that reward data usage that matches his vision for a data-driven company. In this talk, Sean will present the Scout24 Data Landscape Manifesto and will show how the strong opinions it contains enabled him to successfully migrate from a classic centralized data warehouse to a decentralized, scalable, cloud-based data platform at AutoScout24 and ImmobilienScout24 that is core to their analytics and machine learning activities.]]> Thu, 29 Nov 2018 09:10:42 GMT /slideshow/the-scout24-data-landscape-manifesto-building-an-opinionated-data-platform/124352212 PAWDeutschland@slideshare.net(PAWDeutschland) The Scout24 Data Landscape Manifesto: Building an Opinionated Data Platform PAWDeutschland The Scout24 Data Landscape Manifesto is the formalization of our opinions on how a successful data-driven company should approach data. In a truly data-driven company, no manager, no salesperson, no engineer and no data scientist can do their job properly without easy access to large amounts of high-quality data. It is Sean's mandate to create a platform that encourages the production of high-quality data and enables engagement with data by all employees. He and his team are opinionated about how all producers and consumers of data need to be active participants in the data platform, to make data-driven decisions and to be responsible for the data they produce. And he built the data platform with 'nudges' that reward data usage that matches his vision for a data-driven company. In this talk, Sean will present the Scout24 Data Landscape Manifesto and will show how the strong opinions it contains enabled him to successfully migrate from a classic centralized data warehouse to a decentralized, scalable, cloud-based data platform at AutoScout24 and ImmobilienScout24 that is core to their analytics and machine learning activities. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/thescout24datalandscapemanifesto-181129091042-thumbnail.jpg?width=120&height=120&fit=bounds" /> The Scout24 Data Landscape Manifesto is the formalization of our opinions on how a successful data-driven company should approach data. In a truly data-driven company, no manager, no salesperson, no engineer and no data scientist can do their job properly without easy access to large amounts of high-quality data. It is Sean's mandate to create a platform that encourages the production of high-quality data and enables engagement with data by all employees. He and his team are opinionated about how all producers and consumers of data need to be active participants in the data platform, to make data-driven decisions and to be responsible for the data they produce. And he built the data platform with 'nudges' that reward data usage that matches his vision for a data-driven company. In this talk, Sean will present the Scout24 Data Landscape Manifesto and will show how the strong opinions it contains enabled him to successfully migrate from a classic centralized data warehouse to a decentralized, scalable, cloud-based data platform at AutoScout24 and ImmobilienScout24 that is core to their analytics and machine learning activities.

The Scout24 Data Landscape Manifesto: Building an Opinionated Data Platform from Rising Media Ltd.

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0 Prescriptive ohne Predictive: Regression ist noch nicht tot! ROMI bei Unitymedia https://de.slideshare.net/slideshow/romi-unitymedia-124352164/124352164 romiunitymedia-181129091020
Wo investieren wir die nächsten 100.000 €? Wenn wir das Marketingbudget in diesem Monat kürzen, was werden die Auswirkungen auf unsere Sales-Aktivitäten sein und für wie lange? Welche Botschaften sollen wir in unseren TV-Spots platzieren, welche im Bereich Out-of-Home? Wie wirkt sich das Fernsehen auf unseren Kanal-Mix aus und wann und wo lohnt sich die Investition am meisten? Das sind die Fragen, die sich Unitymedia gestellt hat. Das Advanced Analytics-Team hat einen Baukasten aus fortgeschrittenen Regressionsmodellen entwickelt, um solche Fragen beantworten zu können, eine Diskussionsgrundlage zu bieten wie Marketing-Mittel optimal zu reallokieren sind und damit langfristig die Marktbearbeitung zu optimieren. Die Case Study des Projekts erklärt die Modellierung und den Projektansatz, warum Predictive Analytics hier nicht funktionieren würde und wie wir uns darauf konzentriert haben präskriptiv zu handeln (und das nicht nur im Hinblick auf die Modellierung).]]>
Wo investieren wir die nächsten 100.000 €? Wenn wir das Marketingbudget in diesem Monat kürzen, was werden die Auswirkungen auf unsere Sales-Aktivitäten sein und für wie lange? Welche Botschaften sollen wir in unseren TV-Spots platzieren, welche im Bereich Out-of-Home? Wie wirkt sich das Fernsehen auf unseren Kanal-Mix aus und wann und wo lohnt sich die Investition am meisten? Das sind die Fragen, die sich Unitymedia gestellt hat. Das Advanced Analytics-Team hat einen Baukasten aus fortgeschrittenen Regressionsmodellen entwickelt, um solche Fragen beantworten zu können, eine Diskussionsgrundlage zu bieten wie Marketing-Mittel optimal zu reallokieren sind und damit langfristig die Marktbearbeitung zu optimieren. Die Case Study des Projekts erklärt die Modellierung und den Projektansatz, warum Predictive Analytics hier nicht funktionieren würde und wie wir uns darauf konzentriert haben präskriptiv zu handeln (und das nicht nur im Hinblick auf die Modellierung).]]> Thu, 29 Nov 2018 09:10:19 GMT https://de.slideshare.net/slideshow/romi-unitymedia-124352164/124352164 PAWDeutschland@slideshare.net(PAWDeutschland) Prescriptive ohne Predictive: Regression ist noch nicht tot! ROMI bei Unitymedia PAWDeutschland Wo investieren wir die nächsten 100.000 €? Wenn wir das Marketingbudget in diesem Monat kürzen, was werden die Auswirkungen auf unsere Sales-Aktivitäten sein und für wie lange? Welche Botschaften sollen wir in unseren TV-Spots platzieren, welche im Bereich Out-of-Home? Wie wirkt sich das Fernsehen auf unseren Kanal-Mix aus und wann und wo lohnt sich die Investition am meisten? Das sind die Fragen, die sich Unitymedia gestellt hat. Das Advanced Analytics-Team hat einen Baukasten aus fortgeschrittenen Regressionsmodellen entwickelt, um solche Fragen beantworten zu können, eine Diskussionsgrundlage zu bieten wie Marketing-Mittel optimal zu reallokieren sind und damit langfristig die Marktbearbeitung zu optimieren. Die Case Study des Projekts erklärt die Modellierung und den Projektansatz, warum Predictive Analytics hier nicht funktionieren würde und wie wir uns darauf konzentriert haben präskriptiv zu handeln (und das nicht nur im Hinblick auf die Modellierung). <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/romiunitymedia-181129091020-thumbnail.jpg?width=120&height=120&fit=bounds" /> Wo investieren wir die nächsten 100.000 €? Wenn wir das Marketingbudget in diesem Monat kürzen, was werden die Auswirkungen auf unsere Sales-Aktivitäten sein und für wie lange? Welche Botschaften sollen wir in unseren TV-Spots platzieren, welche im Bereich Out-of-Home? Wie wirkt sich das Fernsehen auf unseren Kanal-Mix aus und wann und wo lohnt sich die Investition am meisten? Das sind die Fragen, die sich Unitymedia gestellt hat. Das Advanced Analytics-Team hat einen Baukasten aus fortgeschrittenen Regressionsmodellen entwickelt, um solche Fragen beantworten zu können, eine Diskussionsgrundlage zu bieten wie Marketing-Mittel optimal zu reallokieren sind und damit langfristig die Marktbearbeitung zu optimieren. Die Case Study des Projekts erklärt die Modellierung und den Projektansatz, warum Predictive Analytics hier nicht funktionieren würde und wie wir uns darauf konzentriert haben präskriptiv zu handeln (und das nicht nur im Hinblick auf die Modellierung).

from Rising Media Ltd.

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0 Reinforcement Learning - Learning from Experience like a Human /PAWDeutschland/reinforcement-learning-learning-from-experience-like-a-human-124352159 reinforcementlearning-learningfromexperiencelikeahuman-181129091017
Reinforcement learning is in addition to (un)-supervised learning a major machine learning technology, which has a huge potential in a broad field of applications like robotics, autonomous driving, gaming and general control. This talk describes the major concepts, algorithms and software environments of it and gives a detailed overview of its capabilities. It addresses people with a reasonable background of other AI/ML technologies and therefore requires a good technical background.]]>
Reinforcement learning is in addition to (un)-supervised learning a major machine learning technology, which has a huge potential in a broad field of applications like robotics, autonomous driving, gaming and general control. This talk describes the major concepts, algorithms and software environments of it and gives a detailed overview of its capabilities. It addresses people with a reasonable background of other AI/ML technologies and therefore requires a good technical background.]]> Thu, 29 Nov 2018 09:10:17 GMT /PAWDeutschland/reinforcement-learning-learning-from-experience-like-a-human-124352159 PAWDeutschland@slideshare.net(PAWDeutschland) Reinforcement Learning - Learning from Experience like a Human PAWDeutschland Reinforcement learning is in addition to (un)-supervised learning a major machine learning technology, which has a huge potential in a broad field of applications like robotics, autonomous driving, gaming and general control. This talk describes the major concepts, algorithms and software environments of it and gives a detailed overview of its capabilities. It addresses people with a reasonable background of other AI/ML technologies and therefore requires a good technical background. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/reinforcementlearning-learningfromexperiencelikeahuman-181129091017-thumbnail.jpg?width=120&height=120&fit=bounds" /> Reinforcement learning is in addition to (un)-supervised learning a major machine learning technology, which has a huge potential in a broad field of applications like robotics, autonomous driving, gaming and general control. This talk describes the major concepts, algorithms and software environments of it and gives a detailed overview of its capabilities. It addresses people with a reasonable background of other AI/ML technologies and therefore requires a good technical background.

Reinforcement Learning - Learning from Experience like a Human from Rising Media Ltd.

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0 Mindful Analytics - Wie Achtsamkeit uns noch besser macht https://de.slideshare.net/slideshow/mindful-analytics-wie-achtsamkeit-uns-noch-besser-macht/124351694 mindfulanalytics-wieachtsamkeitunsnochbessermacht-181129090559
Digitalisierung und Achtsamkeit sind zwei Trends, die unsere Gesellschaft und unsere Unternehmen beeinflussen. Im Rahmen der Digitalisierung und insbesondere mit der zunehmenden Nutzung von Daten, erzielen wir seit vielen Jahren große Fortschritte. Der Achtsamkeitstrend hingegen ist in den Unternehmen heute noch kaum spürbar. Dabei gibt es mittlerweile zahlreiche empirische Belege für die positiven Effekte eines achtsamen Arbeitsalltags und es wird Zeit, auch diesen Hebel zur Optimierung unseres digitalisierten Geschäfts zu nutzen. In dem Vortrag werden grundlegende Konzepte der Achtsamkeit und Möglichkeiten zu deren Integration in den Arbeitsalltag gezeigt. Im Detail wird das Achtsamkeitsprinzip des „Nicht Bewertens“ mit Blick auf „Predictive Analytics“ analysiert. Außerdem werden die positiven Wirkungen der Achtsamkeit auf unsere täglichen und ganz praktischen Probleme der zunehmend datengetriebene Unternehmenskultur aufgezeigt.]]>
Digitalisierung und Achtsamkeit sind zwei Trends, die unsere Gesellschaft und unsere Unternehmen beeinflussen. Im Rahmen der Digitalisierung und insbesondere mit der zunehmenden Nutzung von Daten, erzielen wir seit vielen Jahren große Fortschritte. Der Achtsamkeitstrend hingegen ist in den Unternehmen heute noch kaum spürbar. Dabei gibt es mittlerweile zahlreiche empirische Belege für die positiven Effekte eines achtsamen Arbeitsalltags und es wird Zeit, auch diesen Hebel zur Optimierung unseres digitalisierten Geschäfts zu nutzen. In dem Vortrag werden grundlegende Konzepte der Achtsamkeit und Möglichkeiten zu deren Integration in den Arbeitsalltag gezeigt. Im Detail wird das Achtsamkeitsprinzip des „Nicht Bewertens“ mit Blick auf „Predictive Analytics“ analysiert. Außerdem werden die positiven Wirkungen der Achtsamkeit auf unsere täglichen und ganz praktischen Probleme der zunehmend datengetriebene Unternehmenskultur aufgezeigt.]]> Thu, 29 Nov 2018 09:05:59 GMT https://de.slideshare.net/slideshow/mindful-analytics-wie-achtsamkeit-uns-noch-besser-macht/124351694 PAWDeutschland@slideshare.net(PAWDeutschland) Mindful Analytics - Wie Achtsamkeit uns noch besser macht PAWDeutschland Digitalisierung und Achtsamkeit sind zwei Trends, die unsere Gesellschaft und unsere Unternehmen beeinflussen. Im Rahmen der Digitalisierung und insbesondere mit der zunehmenden Nutzung von Daten, erzielen wir seit vielen Jahren große Fortschritte. Der Achtsamkeitstrend hingegen ist in den Unternehmen heute noch kaum spürbar. Dabei gibt es mittlerweile zahlreiche empirische Belege für die positiven Effekte eines achtsamen Arbeitsalltags und es wird Zeit, auch diesen Hebel zur Optimierung unseres digitalisierten Geschäfts zu nutzen. In dem Vortrag werden grundlegende Konzepte der Achtsamkeit und Möglichkeiten zu deren Integration in den Arbeitsalltag gezeigt. Im Detail wird das Achtsamkeitsprinzip des „Nicht Bewertens“ mit Blick auf „Predictive Analytics“ analysiert. Außerdem werden die positiven Wirkungen der Achtsamkeit auf unsere täglichen und ganz praktischen Probleme der zunehmend datengetriebene Unternehmenskultur aufgezeigt. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mindfulanalytics-wieachtsamkeitunsnochbessermacht-181129090559-thumbnail.jpg?width=120&height=120&fit=bounds" /> Digitalisierung und Achtsamkeit sind zwei Trends, die unsere Gesellschaft und unsere Unternehmen beeinflussen. Im Rahmen der Digitalisierung und insbesondere mit der zunehmenden Nutzung von Daten, erzielen wir seit vielen Jahren große Fortschritte. Der Achtsamkeitstrend hingegen ist in den Unternehmen heute noch kaum spürbar. Dabei gibt es mittlerweile zahlreiche empirische Belege für die positiven Effekte eines achtsamen Arbeitsalltags und es wird Zeit, auch diesen Hebel zur Optimierung unseres digitalisierten Geschäfts zu nutzen. In dem Vortrag werden grundlegende Konzepte der Achtsamkeit und Möglichkeiten zu deren Integration in den Arbeitsalltag gezeigt. Im Detail wird das Achtsamkeitsprinzip des „Nicht Bewertens“ mit Blick auf „Predictive Analytics“ analysiert. Außerdem werden die positiven Wirkungen der Achtsamkeit auf unsere täglichen und ganz praktischen Probleme der zunehmend datengetriebene Unternehmenskultur aufgezeigt.

from Rising Media Ltd.

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0 Data Science Development with Impact /slideshow/data-science-development-with-impact-124351683/124351683 datasciencedevelopmentwithimpact-181129090552
Organizations across the globe ramp up Data Science teams and invest tremendous amounts in ambitious development initiatives. Hardly any CEO left who is not into developing a data driven organization or – even better – activating AI to become a true disruptor. Despite the highly motivated key stakeholders and rapidly growing data assets, many Data Science projects ultimately go wrong. Some of them produce impressive prototypes or MVPs and yet, fail to generate real impact. Data Science development with impact and at scale needs to address the differences between pure software development and development with analytical focus and high invention risk.]]>
Organizations across the globe ramp up Data Science teams and invest tremendous amounts in ambitious development initiatives. Hardly any CEO left who is not into developing a data driven organization or – even better – activating AI to become a true disruptor. Despite the highly motivated key stakeholders and rapidly growing data assets, many Data Science projects ultimately go wrong. Some of them produce impressive prototypes or MVPs and yet, fail to generate real impact. Data Science development with impact and at scale needs to address the differences between pure software development and development with analytical focus and high invention risk.]]> Thu, 29 Nov 2018 09:05:52 GMT /slideshow/data-science-development-with-impact-124351683/124351683 PAWDeutschland@slideshare.net(PAWDeutschland) Data Science Development with Impact PAWDeutschland Organizations across the globe ramp up Data Science teams and invest tremendous amounts in ambitious development initiatives. Hardly any CEO left who is not into developing a data driven organization or – even better – activating AI to become a true disruptor. Despite the highly motivated key stakeholders and rapidly growing data assets, many Data Science projects ultimately go wrong. Some of them produce impressive prototypes or MVPs and yet, fail to generate real impact. Data Science development with impact and at scale needs to address the differences between pure software development and development with analytical focus and high invention risk. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/datasciencedevelopmentwithimpact-181129090552-thumbnail.jpg?width=120&height=120&fit=bounds" /> Organizations across the globe ramp up Data Science teams and invest tremendous amounts in ambitious development initiatives. Hardly any CEO left who is not into developing a data driven organization or – even better – activating AI to become a true disruptor. Despite the highly motivated key stakeholders and rapidly growing data assets, many Data Science projects ultimately go wrong. Some of them produce impressive prototypes or MVPs and yet, fail to generate real impact. Data Science development with impact and at scale needs to address the differences between pure software development and development with analytical focus and high invention risk.

Data Science Development with Impact from Rising Media Ltd.

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0 Predictive Analytics World for Business Deutschland 2018 https://de.slideshare.net/slideshow/predictive-analytics-world-for-business-deutschland-2018/96251235 pawbiz2018de20180505-180507101441
Die Predictive Analytics World for Business ist die führende anbieter-unabhängige Fachkonferenz für anwendungsorientierte Predictive Analytics. Anwender, Entscheider und Experten von Predictive Analytics treffen sich am 13 bis 14. November in Berlin, um sich über die neuesten Erkenntnisse und Fortschritte zu informieren, sich untereinander fachlich und persönlich auszutauschen und sich von den Erfolgen inspirieren zu lassen.]]>
Die Predictive Analytics World for Business ist die führende anbieter-unabhängige Fachkonferenz für anwendungsorientierte Predictive Analytics. Anwender, Entscheider und Experten von Predictive Analytics treffen sich am 13 bis 14. November in Berlin, um sich über die neuesten Erkenntnisse und Fortschritte zu informieren, sich untereinander fachlich und persönlich auszutauschen und sich von den Erfolgen inspirieren zu lassen.]]> Mon, 07 May 2018 10:14:41 GMT https://de.slideshare.net/slideshow/predictive-analytics-world-for-business-deutschland-2018/96251235 PAWDeutschland@slideshare.net(PAWDeutschland) Predictive Analytics World for Business Deutschland 2018 PAWDeutschland Die Predictive Analytics World for Business ist die führende anbieter-unabhängige Fachkonferenz für anwendungsorientierte Predictive Analytics. Anwender, Entscheider und Experten von Predictive Analytics treffen sich am 13 bis 14. November in Berlin, um sich über die neuesten Erkenntnisse und Fortschritte zu informieren, sich untereinander fachlich und persönlich auszutauschen und sich von den Erfolgen inspirieren zu lassen. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/pawbiz2018de20180505-180507101441-thumbnail.jpg?width=120&height=120&fit=bounds" /> Die Predictive Analytics World for Business ist die führende anbieter-unabhängige Fachkonferenz für anwendungsorientierte Predictive Analytics. Anwender, Entscheider und Experten von Predictive Analytics treffen sich am 13 bis 14. November in Berlin, um sich über die neuesten Erkenntnisse und Fortschritte zu informieren, sich untereinander fachlich und persönlich auszutauschen und sich von den Erfolgen inspirieren zu lassen.

from Rising Media Ltd.

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0 Predictive Analytics World for Business Germany 2018 /slideshow/predictive-analytics-world-for-business-germany-2018/96251202 pawbiz2018en20180505-180507101418
Predictive Analytics World for Business is the leading provider of independent specialized conferences in applied predictive analytics. Users, decision makers and experts in predictive analytics will meet in Berlin in order to discover the latest findings and progress, to exchange among specialists and in person and to be inspired by the success stories.]]>
Predictive Analytics World for Business is the leading provider of independent specialized conferences in applied predictive analytics. Users, decision makers and experts in predictive analytics will meet in Berlin in order to discover the latest findings and progress, to exchange among specialists and in person and to be inspired by the success stories.]]> Mon, 07 May 2018 10:14:18 GMT /slideshow/predictive-analytics-world-for-business-germany-2018/96251202 PAWDeutschland@slideshare.net(PAWDeutschland) Predictive Analytics World for Business Germany 2018 PAWDeutschland Predictive Analytics World for Business is the leading provider of independent specialized conferences in applied predictive analytics. Users, decision makers and experts in predictive analytics will meet in Berlin in order to discover the latest findings and progress, to exchange among specialists and in person and to be inspired by the success stories. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/pawbiz2018en20180505-180507101418-thumbnail.jpg?width=120&height=120&fit=bounds" /> Predictive Analytics World for Business is the leading provider of independent specialized conferences in applied predictive analytics. Users, decision makers and experts in predictive analytics will meet in Berlin in order to discover the latest findings and progress, to exchange among specialists and in person and to be inspired by the success stories.

Predictive Analytics World for Business Germany 2018 from Rising Media Ltd.

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0 The Centrality of a Detailed Understanding of your Audience /slideshow/the-centrality-of-a-detailed-understanding-of-your-audience/84617128 0900owusu-171221095241
For media organizations an understanding of one's audience is key to delivering optimal content. The path to this understanding often runs through logged behavioral data, but can we leverage methods from the world of polling to generate additional insights?]]>
For media organizations an understanding of one's audience is key to delivering optimal content. The path to this understanding often runs through logged behavioral data, but can we leverage methods from the world of polling to generate additional insights?]]> Thu, 21 Dec 2017 09:52:41 GMT /slideshow/the-centrality-of-a-detailed-understanding-of-your-audience/84617128 PAWDeutschland@slideshare.net(PAWDeutschland) The Centrality of a Detailed Understanding of your Audience PAWDeutschland For media organizations an understanding of one's audience is key to delivering optimal content. The path to this understanding often runs through logged behavioral data, but can we leverage methods from the world of polling to generate additional insights? <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/0900owusu-171221095241-thumbnail.jpg?width=120&height=120&fit=bounds" /> For media organizations an understanding of one's audience is key to delivering optimal content. The path to this understanding often runs through logged behavioral data, but can we leverage methods from the world of polling to generate additional insights?

The Centrality of a Detailed Understanding of your Audience from Rising Media Ltd.

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0 Der steinige Weg zum automatisierten Data Science Produkt – Empfehlungen und Lessons Learned https://de.slideshare.net/slideshow/der-steinige-weg-zum-automatisierten-data-science-produkt-empfehlungen-und-lessons-learned/84538167 1130huberwirth-171220124353
„Irgendwie müsste es doch möglich sein, unsere Marketing-Entscheidungen automatisiert und datengestützt zu optimieren. Bauchgefühl ist ja gut, aber auf Dauer? Wir haben da doch diesen Riesenberg an Daten. Nein, eigentlich sind es ganz viele Berge. Und eine Idee habe ich auch – lass uns unsere Preissetzung optimieren! Oder doch die Vertriebstätigkeiten?“ In unserer Deep-Dive Session zeigen wir im Detail, wie wir von einem unklaren „Ideenwust“ und einem bestenfalls rudimentären Verständnis von Datenerfordernissen und –realitäten schrittweise zu einer komplett datengetriebenen Software zur Optimierung von Marketing-Aktivitäten kommen. Interaktive Elemente machen den kompletten Prozess erlebbar – von der Priorisierung der Use Cases über die Erstellung erster Design Scribbles in Design Studio Workshops bis hin zur agilen Entwicklung der webbasierten Softwarelösung. Ein besonderes Augenmerk wird dabei auf der Herausforderung liegen, komplexe Data Science Modelle im agilen Setup – welches auf stetige Software-Inkremente abzielt – zu entwickeln. Konkrete Praxisbeispiele ziehen wir aus unseren noch laufenden Entwicklungen von Data Science Webapplikationen zur Retail Store Optimierung, Promotion-Optimierung und zur Produkt-Launch-Optimierung.]]>
„Irgendwie müsste es doch möglich sein, unsere Marketing-Entscheidungen automatisiert und datengestützt zu optimieren. Bauchgefühl ist ja gut, aber auf Dauer? Wir haben da doch diesen Riesenberg an Daten. Nein, eigentlich sind es ganz viele Berge. Und eine Idee habe ich auch – lass uns unsere Preissetzung optimieren! Oder doch die Vertriebstätigkeiten?“ In unserer Deep-Dive Session zeigen wir im Detail, wie wir von einem unklaren „Ideenwust“ und einem bestenfalls rudimentären Verständnis von Datenerfordernissen und –realitäten schrittweise zu einer komplett datengetriebenen Software zur Optimierung von Marketing-Aktivitäten kommen. Interaktive Elemente machen den kompletten Prozess erlebbar – von der Priorisierung der Use Cases über die Erstellung erster Design Scribbles in Design Studio Workshops bis hin zur agilen Entwicklung der webbasierten Softwarelösung. Ein besonderes Augenmerk wird dabei auf der Herausforderung liegen, komplexe Data Science Modelle im agilen Setup – welches auf stetige Software-Inkremente abzielt – zu entwickeln. Konkrete Praxisbeispiele ziehen wir aus unseren noch laufenden Entwicklungen von Data Science Webapplikationen zur Retail Store Optimierung, Promotion-Optimierung und zur Produkt-Launch-Optimierung.]]> Wed, 20 Dec 2017 12:43:52 GMT https://de.slideshare.net/slideshow/der-steinige-weg-zum-automatisierten-data-science-produkt-empfehlungen-und-lessons-learned/84538167 PAWDeutschland@slideshare.net(PAWDeutschland) Der steinige Weg zum automatisierten Data Science Produkt – Empfehlungen und Lessons Learned PAWDeutschland „Irgendwie müsste es doch möglich sein, unsere Marketing-Entscheidungen automatisiert und datengestützt zu optimieren. Bauchgefühl ist ja gut, aber auf Dauer? Wir haben da doch diesen Riesenberg an Daten. Nein, eigentlich sind es ganz viele Berge. Und eine Idee habe ich auch – lass uns unsere Preissetzung optimieren! Oder doch die Vertriebstätigkeiten?“ In unserer Deep-Dive Session zeigen wir im Detail, wie wir von einem unklaren „Ideenwust“ und einem bestenfalls rudimentären Verständnis von Datenerfordernissen und –realitäten schrittweise zu einer komplett datengetriebenen Software zur Optimierung von Marketing-Aktivitäten kommen. Interaktive Elemente machen den kompletten Prozess erlebbar – von der Priorisierung der Use Cases über die Erstellung erster Design Scribbles in Design Studio Workshops bis hin zur agilen Entwicklung der webbasierten Softwarelösung. Ein besonderes Augenmerk wird dabei auf der Herausforderung liegen, komplexe Data Science Modelle im agilen Setup – welches auf stetige Software-Inkremente abzielt – zu entwickeln. Konkrete Praxisbeispiele ziehen wir aus unseren noch laufenden Entwicklungen von Data Science Webapplikationen zur Retail Store Optimierung, Promotion-Optimierung und zur Produkt-Launch-Optimierung. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1130huberwirth-171220124353-thumbnail.jpg?width=120&height=120&fit=bounds" /> „Irgendwie müsste es doch möglich sein, unsere Marketing-Entscheidungen automatisiert und datengestützt zu optimieren. Bauchgefühl ist ja gut, aber auf Dauer? Wir haben da doch diesen Riesenberg an Daten. Nein, eigentlich sind es ganz viele Berge. Und eine Idee habe ich auch – lass uns unsere Preissetzung optimieren! Oder doch die Vertriebstätigkeiten?“ In unserer Deep-Dive Session zeigen wir im Detail, wie wir von einem unklaren „Ideenwust“ und einem bestenfalls rudimentären Verständnis von Datenerfordernissen und –realitäten schrittweise zu einer komplett datengetriebenen Software zur Optimierung von Marketing-Aktivitäten kommen. Interaktive Elemente machen den kompletten Prozess erlebbar – von der Priorisierung der Use Cases über die Erstellung erster Design Scribbles in Design Studio Workshops bis hin zur agilen Entwicklung der webbasierten Softwarelösung. Ein besonderes Augenmerk wird dabei auf der Herausforderung liegen, komplexe Data Science Modelle im agilen Setup – welches auf stetige Software-Inkremente abzielt – zu entwickeln. Konkrete Praxisbeispiele ziehen wir aus unseren noch laufenden Entwicklungen von Data Science Webapplikationen zur Retail Store Optimierung, Promotion-Optimierung und zur Produkt-Launch-Optimierung.

from Rising Media Ltd.

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0 Data Alchemy /slideshow/data-alchemy/84532304 1710vermeer-171220104637
The “Big Data” and “Data Science” rhetoric of recent years seems to focus mostly on collecting, storing and analysing existing data. Data which many seem to think they have “too much of” already. However, the greatest discoveries in both science and business rarely come from analysing things that are already there. True innovation starts with asking Big Questions. Only then does it become apparent which data is needed to find the answers we seek. In this session, we relive the true story of an epic voyage in search of data. A quest for knowledge that will take us around the globe and into the solar system. Along the way, we attempt to transmute lead into gold, use machine learning to optimise email marketing campaigns, experiment with sauerkraut, investigate a novel “Data Scientific” method for sentiment analysis, and discover a new continent. This ancient adventure brings new perspectives on the Big Data and Data Science challenges we face today. Come and see how learning from the past can help you solve the problems of the future.]]>
The “Big Data” and “Data Science” rhetoric of recent years seems to focus mostly on collecting, storing and analysing existing data. Data which many seem to think they have “too much of” already. However, the greatest discoveries in both science and business rarely come from analysing things that are already there. True innovation starts with asking Big Questions. Only then does it become apparent which data is needed to find the answers we seek. In this session, we relive the true story of an epic voyage in search of data. A quest for knowledge that will take us around the globe and into the solar system. Along the way, we attempt to transmute lead into gold, use machine learning to optimise email marketing campaigns, experiment with sauerkraut, investigate a novel “Data Scientific” method for sentiment analysis, and discover a new continent. This ancient adventure brings new perspectives on the Big Data and Data Science challenges we face today. Come and see how learning from the past can help you solve the problems of the future.]]> Wed, 20 Dec 2017 10:46:37 GMT /slideshow/data-alchemy/84532304 PAWDeutschland@slideshare.net(PAWDeutschland) Data Alchemy PAWDeutschland The “Big Data” and “Data Science” rhetoric of recent years seems to focus mostly on collecting, storing and analysing existing data. Data which many seem to think they have “too much of” already. However, the greatest discoveries in both science and business rarely come from analysing things that are already there. True innovation starts with asking Big Questions. Only then does it become apparent which data is needed to find the answers we seek. In this session, we relive the true story of an epic voyage in search of data. A quest for knowledge that will take us around the globe and into the solar system. Along the way, we attempt to transmute lead into gold, use machine learning to optimise email marketing campaigns, experiment with sauerkraut, investigate a novel “Data Scientific” method for sentiment analysis, and discover a new continent. This ancient adventure brings new perspectives on the Big Data and Data Science challenges we face today. Come and see how learning from the past can help you solve the problems of the future. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1710vermeer-171220104637-thumbnail.jpg?width=120&height=120&fit=bounds" /> The “Big Data” and “Data Science” rhetoric of recent years seems to focus mostly on collecting, storing and analysing existing data. Data which many seem to think they have “too much of” already. However, the greatest discoveries in both science and business rarely come from analysing things that are already there. True innovation starts with asking Big Questions. Only then does it become apparent which data is needed to find the answers we seek. In this session, we relive the true story of an epic voyage in search of data. A quest for knowledge that will take us around the globe and into the solar system. Along the way, we attempt to transmute lead into gold, use machine learning to optimise email marketing campaigns, experiment with sauerkraut, investigate a novel “Data Scientific” method for sentiment analysis, and discover a new continent. This ancient adventure brings new perspectives on the Big Data and Data Science challenges we face today. Come and see how learning from the past can help you solve the problems of the future.

Data Alchemy from Rising Media Ltd.

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0 SpiegelMining – Data Science auf Spiegel Online https://de.slideshare.net/PAWDeutschland/spiegelmining-data-science-auf-spiegel-online 1635kriesel-171220104038
Seit Mitte 2014 hat David fast 100.000 Artikel von Spiegel Online systematisch gespeichert. Zum einen gelingt dadurch Reverse Engineering von Spiegel Online: Der Datensatz wird auseinander genommen und Spiegel Online aus vielen völlig neuen Blickwinkeln betrachtet. Das Ganze wird bunt, unterhaltsam und anschaulich, so dass sowohl Techies als auch Nicht-Techies profitieren. Warum sind manche Artikel lang, manche kurz? Kann man Artikeln ansehen, ob die Redakteure wirklich dahinter stehen oder nicht? Welche Redakteure sind enger miteinander verbandelt als andere? Welche Inhalte hält der Spiegel selbst für politisch inkorrekt? Zum anderen gibt David zum Konferenzabschluss einen Überblick darüber, was Data Science für ihn bedeutet und über die gesellschaftlichen Implikationen, die sich aus dem Hype ergeben - zum Nachdenken und meditieren. Nicht nur die Vorgehensweise, sondern auch die Möglichkeiten und gesellschaftlichen Gefahren der Datensammelwut und Auswerterei werden betrachtet und das anhand bunter Grafiken anstatt von Formeln.]]>
Seit Mitte 2014 hat David fast 100.000 Artikel von Spiegel Online systematisch gespeichert. Zum einen gelingt dadurch Reverse Engineering von Spiegel Online: Der Datensatz wird auseinander genommen und Spiegel Online aus vielen völlig neuen Blickwinkeln betrachtet. Das Ganze wird bunt, unterhaltsam und anschaulich, so dass sowohl Techies als auch Nicht-Techies profitieren. Warum sind manche Artikel lang, manche kurz? Kann man Artikeln ansehen, ob die Redakteure wirklich dahinter stehen oder nicht? Welche Redakteure sind enger miteinander verbandelt als andere? Welche Inhalte hält der Spiegel selbst für politisch inkorrekt? Zum anderen gibt David zum Konferenzabschluss einen Überblick darüber, was Data Science für ihn bedeutet und über die gesellschaftlichen Implikationen, die sich aus dem Hype ergeben - zum Nachdenken und meditieren. Nicht nur die Vorgehensweise, sondern auch die Möglichkeiten und gesellschaftlichen Gefahren der Datensammelwut und Auswerterei werden betrachtet und das anhand bunter Grafiken anstatt von Formeln.]]> Wed, 20 Dec 2017 10:40:37 GMT https://de.slideshare.net/PAWDeutschland/spiegelmining-data-science-auf-spiegel-online PAWDeutschland@slideshare.net(PAWDeutschland) SpiegelMining – Data Science auf Spiegel Online PAWDeutschland Seit Mitte 2014 hat David fast 100.000 Artikel von Spiegel Online systematisch gespeichert. Zum einen gelingt dadurch Reverse Engineering von Spiegel Online: Der Datensatz wird auseinander genommen und Spiegel Online aus vielen völlig neuen Blickwinkeln betrachtet. Das Ganze wird bunt, unterhaltsam und anschaulich, so dass sowohl Techies als auch Nicht-Techies profitieren. Warum sind manche Artikel lang, manche kurz? Kann man Artikeln ansehen, ob die Redakteure wirklich dahinter stehen oder nicht? Welche Redakteure sind enger miteinander verbandelt als andere? Welche Inhalte hält der Spiegel selbst für politisch inkorrekt? Zum anderen gibt David zum Konferenzabschluss einen Überblick darüber, was Data Science für ihn bedeutet und über die gesellschaftlichen Implikationen, die sich aus dem Hype ergeben - zum Nachdenken und meditieren. Nicht nur die Vorgehensweise, sondern auch die Möglichkeiten und gesellschaftlichen Gefahren der Datensammelwut und Auswerterei werden betrachtet und das anhand bunter Grafiken anstatt von Formeln. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1635kriesel-171220104038-thumbnail.jpg?width=120&height=120&fit=bounds" /> Seit Mitte 2014 hat David fast 100.000 Artikel von Spiegel Online systematisch gespeichert. Zum einen gelingt dadurch Reverse Engineering von Spiegel Online: Der Datensatz wird auseinander genommen und Spiegel Online aus vielen völlig neuen Blickwinkeln betrachtet. Das Ganze wird bunt, unterhaltsam und anschaulich, so dass sowohl Techies als auch Nicht-Techies profitieren. Warum sind manche Artikel lang, manche kurz? Kann man Artikeln ansehen, ob die Redakteure wirklich dahinter stehen oder nicht? Welche Redakteure sind enger miteinander verbandelt als andere? Welche Inhalte hält der Spiegel selbst für politisch inkorrekt? Zum anderen gibt David zum Konferenzabschluss einen Überblick darüber, was Data Science für ihn bedeutet und über die gesellschaftlichen Implikationen, die sich aus dem Hype ergeben - zum Nachdenken und meditieren. Nicht nur die Vorgehensweise, sondern auch die Möglichkeiten und gesellschaftlichen Gefahren der Datensammelwut und Auswerterei werden betrachtet und das anhand bunter Grafiken anstatt von Formeln.

from Rising Media Ltd.

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0 https://cdn.slidesharecdn.com/profile-photo-PAWDeutschland-48x48.jpg?cb=1592551122 Technology Events for Business People: Rising Media brings people together to better understand the fast-moving intersection of business and technology. We deliver practical insights organizations can use to improve their bottom line and better connect with customers. We love looking over the horizon and sharing the most incisive, cogent and constructive perspectives with as many people as possible. We love creating communities of practice. risingmedia.com https://cdn.slidesharecdn.com/ss_thumbnails/0905block-191210100457-thumbnail.jpg?width=320&height=320&fit=bounds PAWDeutschland/data-science-at-roche-from-exploration-to-productionization Data Science at Roche:... https://cdn.slidesharecdn.com/ss_thumbnails/1135turekzmuda-191209081549-thumbnail.jpg?width=320&height=320&fit=bounds PAWDeutschland/costeffective-personalisation-platform-for-30m-users-of-ringier-axel-springer Cost-Effective Persona... https://cdn.slidesharecdn.com/ss_thumbnails/1205hamed-191205144421-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/uplift-modelling-as-a-tool-for-making-causal-inferences-at-shopify/201903116 Uplift Modelling as a ...