狠狠撸shows by User: NikoVuokko / http://www.slideshare.net/images/logo.gif 狠狠撸shows by User: NikoVuokko / Wed, 11 Nov 2015 10:10:26 GMT 狠狠撸Share feed for 狠狠撸shows by User: NikoVuokko Analytics in business /slideshow/analytics-in-business/54988521 analyticsinbusiness-englishwebversion-151111101026-lva1-app6892
Material for the 26 Oct 2015 lecture I held for Aalto University business students. The lecture focuses on the high level topics in analytics and Big Data that are either central to the subject or just highly visible in the media. The main messages of the lecture are: - The purpose of analytics and of the data analyst is to solve business problems - Big Data brings over some very special traits to doing analytics that don't exist when working working with smaller datasets. Understanding these traits is a must for successful analytics. - Deploying analytics is more dependent on humans than on technology - Data and analytics are nowadays significant assets to many companies. Therefore they need their own strategy and need to be managed just like any other business critical assets. ]]>

Material for the 26 Oct 2015 lecture I held for Aalto University business students. The lecture focuses on the high level topics in analytics and Big Data that are either central to the subject or just highly visible in the media. The main messages of the lecture are: - The purpose of analytics and of the data analyst is to solve business problems - Big Data brings over some very special traits to doing analytics that don't exist when working working with smaller datasets. Understanding these traits is a must for successful analytics. - Deploying analytics is more dependent on humans than on technology - Data and analytics are nowadays significant assets to many companies. Therefore they need their own strategy and need to be managed just like any other business critical assets. ]]>
Wed, 11 Nov 2015 10:10:26 GMT /slideshow/analytics-in-business/54988521 NikoVuokko@slideshare.net(NikoVuokko) Analytics in business NikoVuokko Material for the 26 Oct 2015 lecture I held for Aalto University business students. The lecture focuses on the high level topics in analytics and Big Data that are either central to the subject or just highly visible in the media. The main messages of the lecture are: - The purpose of analytics and of the data analyst is to solve business problems - Big Data brings over some very special traits to doing analytics that don't exist when working working with smaller datasets. Understanding these traits is a must for successful analytics. - Deploying analytics is more dependent on humans than on technology - Data and analytics are nowadays significant assets to many companies. Therefore they need their own strategy and need to be managed just like any other business critical assets. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-englishwebversion-151111101026-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Material for the 26 Oct 2015 lecture I held for Aalto University business students. The lecture focuses on the high level topics in analytics and Big Data that are either central to the subject or just highly visible in the media. The main messages of the lecture are: - The purpose of analytics and of the data analyst is to solve business problems - Big Data brings over some very special traits to doing analytics that don&#39;t exist when working working with smaller datasets. Understanding these traits is a must for successful analytics. - Deploying analytics is more dependent on humans than on technology - Data and analytics are nowadays significant assets to many companies. Therefore they need their own strategy and need to be managed just like any other business critical assets.
Analytics in business from Niko Vuokko
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Drones in real use /slideshow/drones-in-real-use/54947014 technologyconvention-drones2015-10-07-150ppi-webversion-151110104838-lva1-app6892
Where are drones actually used and how do they relate to the Internet of Things? 狠狠撸s to the presentations I held at Tech'15 Convention and Helsinki Tech Days '15. The contents also focus on the data collected by drones and especially to one the most prominent drone use cases: inspection of public infrastructure.]]>

Where are drones actually used and how do they relate to the Internet of Things? 狠狠撸s to the presentations I held at Tech'15 Convention and Helsinki Tech Days '15. The contents also focus on the data collected by drones and especially to one the most prominent drone use cases: inspection of public infrastructure.]]>
Tue, 10 Nov 2015 10:48:38 GMT /slideshow/drones-in-real-use/54947014 NikoVuokko@slideshare.net(NikoVuokko) Drones in real use NikoVuokko Where are drones actually used and how do they relate to the Internet of Things? 狠狠撸s to the presentations I held at Tech'15 Convention and Helsinki Tech Days '15. The contents also focus on the data collected by drones and especially to one the most prominent drone use cases: inspection of public infrastructure. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/technologyconvention-drones2015-10-07-150ppi-webversion-151110104838-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Where are drones actually used and how do they relate to the Internet of Things? 狠狠撸s to the presentations I held at Tech&#39;15 Convention and Helsinki Tech Days &#39;15. The contents also focus on the data collected by drones and especially to one the most prominent drone use cases: inspection of public infrastructure.
Drones in real use from Niko Vuokko
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Analytiikka bisneksess盲 /slideshow/analytiikka-bisneksess/54433547 analyticsinbusiness-finnishwebversion-151027143516-lva1-app6892
Materiaali 26.10.2015 pidetylle Aalto-yliopiston kauppakorkeakoulun analytiikan kurssille aiheesta "Analytiikka bisneksess盲". Luento k盲y korkealla tasolla l盲pi keskeisi盲 tai muuten vain pinnalla olevia aiheita analytiikasta ja Big Datasta. T盲rkeimpi盲 viestej盲 ovat: - Analytiikan ja analyytikon teht盲v盲n盲 on ratkoa bisnesongelmia - Big Data tuo analytiikan hyvin erityisi盲 ominaisuuksia, joita ei esiinny pienemm盲ss盲 mittakaavassa. N盲iden ominaisuuksien ymm盲rt盲minen on kriittist盲 analytiikan onnistumiselle - Analytiikan k盲ytt枚枚notto on enemm盲n kiinni ihmisist盲 kuin teknologiasta - Data ja analytiikka on nykyisin keskeinen omistuser盲 monille yrityksille. Siksi datalle ja analytiikalle pit盲盲 muodostaa oma strategiansa ja sit盲 hallita kuten mit盲 tahansa bisneskriittist盲 p盲盲omaa. ]]>

Materiaali 26.10.2015 pidetylle Aalto-yliopiston kauppakorkeakoulun analytiikan kurssille aiheesta "Analytiikka bisneksess盲". Luento k盲y korkealla tasolla l盲pi keskeisi盲 tai muuten vain pinnalla olevia aiheita analytiikasta ja Big Datasta. T盲rkeimpi盲 viestej盲 ovat: - Analytiikan ja analyytikon teht盲v盲n盲 on ratkoa bisnesongelmia - Big Data tuo analytiikan hyvin erityisi盲 ominaisuuksia, joita ei esiinny pienemm盲ss盲 mittakaavassa. N盲iden ominaisuuksien ymm盲rt盲minen on kriittist盲 analytiikan onnistumiselle - Analytiikan k盲ytt枚枚notto on enemm盲n kiinni ihmisist盲 kuin teknologiasta - Data ja analytiikka on nykyisin keskeinen omistuser盲 monille yrityksille. Siksi datalle ja analytiikalle pit盲盲 muodostaa oma strategiansa ja sit盲 hallita kuten mit盲 tahansa bisneskriittist盲 p盲盲omaa. ]]>
Tue, 27 Oct 2015 14:35:16 GMT /slideshow/analytiikka-bisneksess/54433547 NikoVuokko@slideshare.net(NikoVuokko) Analytiikka bisneksess盲 NikoVuokko Materiaali 26.10.2015 pidetylle Aalto-yliopiston kauppakorkeakoulun analytiikan kurssille aiheesta "Analytiikka bisneksess盲". Luento k盲y korkealla tasolla l盲pi keskeisi盲 tai muuten vain pinnalla olevia aiheita analytiikasta ja Big Datasta. T盲rkeimpi盲 viestej盲 ovat: - Analytiikan ja analyytikon teht盲v盲n盲 on ratkoa bisnesongelmia - Big Data tuo analytiikan hyvin erityisi盲 ominaisuuksia, joita ei esiinny pienemm盲ss盲 mittakaavassa. N盲iden ominaisuuksien ymm盲rt盲minen on kriittist盲 analytiikan onnistumiselle - Analytiikan k盲ytt枚枚notto on enemm盲n kiinni ihmisist盲 kuin teknologiasta - Data ja analytiikka on nykyisin keskeinen omistuser盲 monille yrityksille. Siksi datalle ja analytiikalle pit盲盲 muodostaa oma strategiansa ja sit盲 hallita kuten mit盲 tahansa bisneskriittist盲 p盲盲omaa. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-finnishwebversion-151027143516-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Materiaali 26.10.2015 pidetylle Aalto-yliopiston kauppakorkeakoulun analytiikan kurssille aiheesta &quot;Analytiikka bisneksess盲&quot;. Luento k盲y korkealla tasolla l盲pi keskeisi盲 tai muuten vain pinnalla olevia aiheita analytiikasta ja Big Datasta. T盲rkeimpi盲 viestej盲 ovat: - Analytiikan ja analyytikon teht盲v盲n盲 on ratkoa bisnesongelmia - Big Data tuo analytiikan hyvin erityisi盲 ominaisuuksia, joita ei esiinny pienemm盲ss盲 mittakaavassa. N盲iden ominaisuuksien ymm盲rt盲minen on kriittist盲 analytiikan onnistumiselle - Analytiikan k盲ytt枚枚notto on enemm盲n kiinni ihmisist盲 kuin teknologiasta - Data ja analytiikka on nykyisin keskeinen omistuser盲 monille yrityksille. Siksi datalle ja analytiikalle pit盲盲 muodostaa oma strategiansa ja sit盲 hallita kuten mit盲 tahansa bisneskriittist盲 p盲盲omaa.
Analytiikka bisneksess杈� from Niko Vuokko
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Sensor Data in Business /slideshow/sensor-data-in-business/47704890 sensordata-fortuminternalevent2015-03-31-150ppien-150503160857-conversion-gate01
狠狠撸s for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.]]>

狠狠撸s for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.]]>
Sun, 03 May 2015 16:08:57 GMT /slideshow/sensor-data-in-business/47704890 NikoVuokko@slideshare.net(NikoVuokko) Sensor Data in Business NikoVuokko 狠狠撸s for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sensordata-fortuminternalevent2015-03-31-150ppien-150503160857-conversion-gate01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 狠狠撸s for a presentation given at a Fortum&#39;s internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.
Sensor Data in Business from Niko Vuokko
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Sensoridatan ja liiketoiminnan tulevaisuus /slideshow/sensoridatan-tulevaisuus-data-fortum-internal-event-20150331-slide-share-version/46691996 sensordata-fortuminternalevent2015-03-31-slideshareversion-150406134052-conversion-gate01
Finnish slides for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure. I will hopefully translate these into English at some point :)]]>

Finnish slides for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure. I will hopefully translate these into English at some point :)]]>
Mon, 06 Apr 2015 13:40:52 GMT /slideshow/sensoridatan-tulevaisuus-data-fortum-internal-event-20150331-slide-share-version/46691996 NikoVuokko@slideshare.net(NikoVuokko) Sensoridatan ja liiketoiminnan tulevaisuus NikoVuokko Finnish slides for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure. I will hopefully translate these into English at some point :) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sensordata-fortuminternalevent2015-03-31-slideshareversion-150406134052-conversion-gate01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Finnish slides for a presentation given at a Fortum&#39;s internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure. I will hopefully translate these into English at some point :)
Sensoridatan ja liiketoiminnan tulevaisuus from Niko Vuokko
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Introduction to Data Science /slideshow/introduction-to-data-science-25391618/25391618 jyvskyl-lecture1share-130819144749-phpapp02
Two hour lecture I gave at the Jyv盲skyl盲 Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning. See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)]]>

Two hour lecture I gave at the Jyv盲skyl盲 Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning. See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)]]>
Mon, 19 Aug 2013 14:47:48 GMT /slideshow/introduction-to-data-science-25391618/25391618 NikoVuokko@slideshare.net(NikoVuokko) Introduction to Data Science NikoVuokko Two hour lecture I gave at the Jyv盲skyl盲 Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning. See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/jyvskyl-lecture1share-130819144749-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Two hour lecture I gave at the Jyv盲skyl盲 Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning. See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)
Introduction to Data Science from Niko Vuokko
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Industrial Data Science /slideshow/industrial-data-science/25391361 jyvskyl-lecture2share-130819143904-phpapp01
A three hour lecture I gave at the Jyv盲skyl盲 Summer School. The talk goes through important details about the use of data science in real businesses. These include data deployment, data processing, practical issues with data solutions and arising trends in data science. See also Part 1 of the lecture: Introduction Data Science. You can find it in my profile (click the face)]]>

A three hour lecture I gave at the Jyv盲skyl盲 Summer School. The talk goes through important details about the use of data science in real businesses. These include data deployment, data processing, practical issues with data solutions and arising trends in data science. See also Part 1 of the lecture: Introduction Data Science. You can find it in my profile (click the face)]]>
Mon, 19 Aug 2013 14:39:04 GMT /slideshow/industrial-data-science/25391361 NikoVuokko@slideshare.net(NikoVuokko) Industrial Data Science NikoVuokko A three hour lecture I gave at the Jyv盲skyl盲 Summer School. The talk goes through important details about the use of data science in real businesses. These include data deployment, data processing, practical issues with data solutions and arising trends in data science. See also Part 1 of the lecture: Introduction Data Science. You can find it in my profile (click the face) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/jyvskyl-lecture2share-130819143904-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A three hour lecture I gave at the Jyv盲skyl盲 Summer School. The talk goes through important details about the use of data science in real businesses. These include data deployment, data processing, practical issues with data solutions and arising trends in data science. See also Part 1 of the lecture: Introduction Data Science. You can find it in my profile (click the face)
Industrial Data Science from Niko Vuokko
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Metrics @ App Academy /slideshow/metrics-22593266/22593266 metrics-130607040804-phpapp01
I've been teaching AppCademy teams about metrics several times since 2013. This is the latest slide deck. Main goal: dispel convenient default metrics, instead focus on your own business problems and derive metrics to solve them. AppCademy is a 4-week accelerator camp run by AppCampus, a training program for Windows Phone dev teams.]]>

I've been teaching AppCademy teams about metrics several times since 2013. This is the latest slide deck. Main goal: dispel convenient default metrics, instead focus on your own business problems and derive metrics to solve them. AppCademy is a 4-week accelerator camp run by AppCampus, a training program for Windows Phone dev teams.]]>
Fri, 07 Jun 2013 04:08:04 GMT /slideshow/metrics-22593266/22593266 NikoVuokko@slideshare.net(NikoVuokko) Metrics @ App Academy NikoVuokko I've been teaching AppCademy teams about metrics several times since 2013. This is the latest slide deck. Main goal: dispel convenient default metrics, instead focus on your own business problems and derive metrics to solve them. AppCademy is a 4-week accelerator camp run by AppCampus, a training program for Windows Phone dev teams. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/metrics-130607040804-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> I&#39;ve been teaching AppCademy teams about metrics several times since 2013. This is the latest slide deck. Main goal: dispel convenient default metrics, instead focus on your own business problems and derive metrics to solve them. AppCademy is a 4-week accelerator camp run by AppCampus, a training program for Windows Phone dev teams.
Metrics @ App Academy from Niko Vuokko
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Big Data Rampage /NikoVuokko/big-data-rampage-2013-0513 bigdatarampage2013-05-13-130513050042-phpapp02
Presentation for the 45 min. + QA talk I gave at HIIT seminar on 13 May 2013 for local data science researchers.]]>

Presentation for the 45 min. + QA talk I gave at HIIT seminar on 13 May 2013 for local data science researchers.]]>
Mon, 13 May 2013 05:00:41 GMT /NikoVuokko/big-data-rampage-2013-0513 NikoVuokko@slideshare.net(NikoVuokko) Big Data Rampage NikoVuokko Presentation for the 45 min. + QA talk I gave at HIIT seminar on 13 May 2013 for local data science researchers. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/bigdatarampage2013-05-13-130513050042-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation for the 45 min. + QA talk I gave at HIIT seminar on 13 May 2013 for local data science researchers.
Big Data Rampage from Niko Vuokko
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https://cdn.slidesharecdn.com/profile-photo-NikoVuokko-48x48.jpg?cb=1713247442 All-around expert and public speaker in making data systems and data science solve real-world business problems, both conceptually and hands in the mud. I thrive being at the interface between business problem owners and technical capabilities and making sure that this communication works. My experience ranges from designing large cloud-deployed real-time data platforms and predictive lifetime value algorithms to building from scratch software for automated hard rock drill positioning and crowd pattern analysis. I hold an Olympic Bronze Medal in mathematics, PhD in data mining, and MSc in mathematics. Specialties: data science, distributed systems, big data, digital marketing https://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-englishwebversion-151111101026-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/analytics-in-business/54988521 Analytics in business https://cdn.slidesharecdn.com/ss_thumbnails/technologyconvention-drones2015-10-07-150ppi-webversion-151110104838-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/drones-in-real-use/54947014 Drones in real use https://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-finnishwebversion-151027143516-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/analytiikka-bisneksess/54433547 Analytiikka bisneksess盲