�ݺ�ߣshows by User: arcadiadata

�ݺ�ߣshows by User: arcadiadata / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: arcadiadata / Thu, 07 Feb 2019 00:03:46 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: arcadiadata Visualizing Geospatial Data at Scale /slideshow/visualizing-geospatial-data-at-scale/130816738 arcadiamapboxwebinar-final-190207000346
Geospatial data is everywhere today. Your mapping capabilities need to handle the growing volumes of “big data” to deliver location-based insights at any level. Large-scale mapping use cases require a scalable and real-time visualization platform that enables self-service analysis. End users need a fast, interactive system that can immediately display any view of their data on demand.]]>
Geospatial data is everywhere today. Your mapping capabilities need to handle the growing volumes of “big data” to deliver location-based insights at any level. Large-scale mapping use cases require a scalable and real-time visualization platform that enables self-service analysis. End users need a fast, interactive system that can immediately display any view of their data on demand.]]> Thu, 07 Feb 2019 00:03:46 GMT /slideshow/visualizing-geospatial-data-at-scale/130816738 arcadiadata@slideshare.net(arcadiadata) Visualizing Geospatial Data at Scale arcadiadata Geospatial data is everywhere today. Your mapping capabilities need to handle the growing volumes of “big data” to deliver location-based insights at any level. Large-scale mapping use cases require a scalable and real-time visualization platform that enables self-service analysis. End users need a fast, interactive system that can immediately display any view of their data on demand. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arcadiamapboxwebinar-final-190207000346-thumbnail.jpg?width=120&height=120&fit=bounds" /> Geospatial data is everywhere today. Your mapping capabilities need to handle the growing volumes of “big data” to deliver location-based insights at any level. Large-scale mapping use cases require a scalable and real-time visualization platform that enables self-service analysis. End users need a fast, interactive system that can immediately display any view of their data on demand.

Visualizing Geospatial Data at Scale from Arcadia Data

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0 Trends for Modernizing Analytics and Data Warehousing in 2019 /slideshow/trends-for-modernizing-analytics-and-data-warehousing-in-2019/125200851 3trendformodernizinganalyticsanddatawarehousingin2019-181206191141
Brand new research published from Dresner Advisory Services digs deeply into the trends in 2018 around big data analytics. ]]>
Brand new research published from Dresner Advisory Services digs deeply into the trends in 2018 around big data analytics. ]]> Thu, 06 Dec 2018 19:11:41 GMT /slideshow/trends-for-modernizing-analytics-and-data-warehousing-in-2019/125200851 arcadiadata@slideshare.net(arcadiadata) Trends for Modernizing Analytics and Data Warehousing in 2019 arcadiadata Brand new research published from Dresner Advisory Services digs deeply into the trends in 2018 around big data analytics. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/3trendformodernizinganalyticsanddatawarehousingin2019-181206191141-thumbnail.jpg?width=120&height=120&fit=bounds" /> Brand new research published from Dresner Advisory Services digs deeply into the trends in 2018 around big data analytics.

Trends for Modernizing Analytics and Data Warehousing in 2019 from Arcadia Data

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0 A Tale of 2 BI Standards: One for Data Warehouses and One for Data Lakes /slideshow/a-tale-of-2-bi-standards-one-for-data-warehouses-and-one-for-data-lakes-118036860/118036860 ataleof2bistandards-181003223323
The use of data lakes continue to grow, and a recent survey by Eckerson Group shows that organizations are getting real value from their deployments. However, there’s still a lot of room for improvement when it comes to giving business users access to the wealth of potential insights in the data lake. While the data management aspect has been fairly well understood over the years, the success of business intelligence (BI) and analytics on data lakes lags behind. In fact, organizations often struggle with data lakes because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives? In this talk, we’ll discuss: - Why traditional BI tools are architected well for data warehouses, but not data lakes. - Why every organization should have two BI standards: one for data warehouses and one for data lakes. - Innovative capabilities provided by BI for data lakes]]>
The use of data lakes continue to grow, and a recent survey by Eckerson Group shows that organizations are getting real value from their deployments. However, there’s still a lot of room for improvement when it comes to giving business users access to the wealth of potential insights in the data lake. While the data management aspect has been fairly well understood over the years, the success of business intelligence (BI) and analytics on data lakes lags behind. In fact, organizations often struggle with data lakes because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives? In this talk, we’ll discuss: - Why traditional BI tools are architected well for data warehouses, but not data lakes. - Why every organization should have two BI standards: one for data warehouses and one for data lakes. - Innovative capabilities provided by BI for data lakes]]> Wed, 03 Oct 2018 22:33:23 GMT /slideshow/a-tale-of-2-bi-standards-one-for-data-warehouses-and-one-for-data-lakes-118036860/118036860 arcadiadata@slideshare.net(arcadiadata) A Tale of 2 BI Standards: One for Data Warehouses and One for Data Lakes arcadiadata The use of data lakes continue to grow, and a recent survey by Eckerson Group shows that organizations are getting real value from their deployments. However, there’s still a lot of room for improvement when it comes to giving business users access to the wealth of potential insights in the data lake. While the data management aspect has been fairly well understood over the years, the success of business intelligence (BI) and analytics on data lakes lags behind. In fact, organizations often struggle with data lakes because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives? In this talk, we’ll discuss: - Why traditional BI tools are architected well for data warehouses, but not data lakes. - Why every organization should have two BI standards: one for data warehouses and one for data lakes. - Innovative capabilities provided by BI for data lakes <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ataleof2bistandards-181003223323-thumbnail.jpg?width=120&height=120&fit=bounds" /> The use of data lakes continue to grow, and a recent survey by Eckerson Group shows that organizations are getting real value from their deployments. However, there’s still a lot of room for improvement when it comes to giving business users access to the wealth of potential insights in the data lake. While the data management aspect has been fairly well understood over the years, the success of business intelligence (BI) and analytics on data lakes lags behind. In fact, organizations often struggle with data lakes because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives? In this talk, we’ll discuss: - Why traditional BI tools are architected well for data warehouses, but not data lakes. - Why every organization should have two BI standards: one for data warehouses and one for data lakes. - Innovative capabilities provided by BI for data lakes

A Tale of 2 BI Standards: One for Data Warehouses and One for Data Lakes from Arcadia Data

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0 A Tale of 2 BI Standards: One for Data Warehouses and One for Data Lakes /slideshow/a-tale-of-2-bi-standards-one-for-data-warehouses-and-one-for-data-lakes/115885725 randyspresentation-modified1-180922010817
Presentation given by Randy Lea (CRO of Arcadia Data) at Strata Data Conference NYC 2018]]>
Presentation given by Randy Lea (CRO of Arcadia Data) at Strata Data Conference NYC 2018]]> Sat, 22 Sep 2018 01:08:17 GMT /slideshow/a-tale-of-2-bi-standards-one-for-data-warehouses-and-one-for-data-lakes/115885725 arcadiadata@slideshare.net(arcadiadata) A Tale of 2 BI Standards: One for Data Warehouses and One for Data Lakes arcadiadata Presentation given by Randy Lea (CRO of Arcadia Data) at Strata Data Conference NYC 2018 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/randyspresentation-modified1-180922010817-thumbnail.jpg?width=120&height=120&fit=bounds" /> Presentation given by Randy Lea (CRO of Arcadia Data) at Strata Data Conference NYC 2018

A Tale of 2 BI Standards: One for Data Warehouses and One for Data Lakes from Arcadia Data

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0 How Hewlett Packard Enterprise Gets Real with IoT Analytics /slideshow/how-hewlett-packard-enterprise-gets-real-with-iot-analytics/103208585 howhewlett-packardenterprisegetsrealwithiotanalytics-180626-final-180626233216
Learn how HPE uses visual analytics within a data lake to create an “Industrial Internet of Things” model that solves their data analytics problem at scale. ]]>
Learn how HPE uses visual analytics within a data lake to create an “Industrial Internet of Things” model that solves their data analytics problem at scale. ]]> Tue, 26 Jun 2018 23:32:16 GMT /slideshow/how-hewlett-packard-enterprise-gets-real-with-iot-analytics/103208585 arcadiadata@slideshare.net(arcadiadata) How Hewlett Packard Enterprise Gets Real with IoT Analytics arcadiadata Learn how HPE uses visual analytics within a data lake to create an “Industrial Internet of Things” model that solves their data analytics problem at scale. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/howhewlett-packardenterprisegetsrealwithiotanalytics-180626-final-180626233216-thumbnail.jpg?width=120&height=120&fit=bounds" /> Learn how HPE uses visual analytics within a data lake to create an “Industrial Internet of Things” model that solves their data analytics problem at scale.

How Hewlett Packard Enterprise Gets Real with IoT Analytics from Arcadia Data

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0 Unlocking the Power of the Data Lake /slideshow/unlocking-the-power-of-the-data-lake/102471433 arcadiadata-dbta-unlockingthepowerofthedatalake-kim-180531-final-180614201420
You have a data lake — now it’s time to unlock its power. Register for the upcoming webinar “Unlocking the Power of the Data Lake” to learn how. As Hadoop adoption in the enterprise continues to grow, so does commitment to the data lake strategy. Two-thirds of Database Trends and Applications readers are either implementing data lake projects this year or researching and evaluating solutions. Data security, governance, integration, and analytics have all been identified as critical success factors for data lake deployments. To educate this growing audience about the enabling technologies and best practices for unlocking the power of the data lake, Database Trends and Applications is hosting a special roundtable webinar.]]>
You have a data lake — now it’s time to unlock its power. Register for the upcoming webinar “Unlocking the Power of the Data Lake” to learn how. As Hadoop adoption in the enterprise continues to grow, so does commitment to the data lake strategy. Two-thirds of Database Trends and Applications readers are either implementing data lake projects this year or researching and evaluating solutions. Data security, governance, integration, and analytics have all been identified as critical success factors for data lake deployments. To educate this growing audience about the enabling technologies and best practices for unlocking the power of the data lake, Database Trends and Applications is hosting a special roundtable webinar.]]> Thu, 14 Jun 2018 20:14:20 GMT /slideshow/unlocking-the-power-of-the-data-lake/102471433 arcadiadata@slideshare.net(arcadiadata) Unlocking the Power of the Data Lake arcadiadata You have a data lake — now it’s time to unlock its power. Register for the upcoming webinar “Unlocking the Power of the Data Lake” to learn how. As Hadoop adoption in the enterprise continues to grow, so does commitment to the data lake strategy. Two-thirds of Database Trends and Applications readers are either implementing data lake projects this year or researching and evaluating solutions. Data security, governance, integration, and analytics have all been identified as critical success factors for data lake deployments. To educate this growing audience about the enabling technologies and best practices for unlocking the power of the data lake, Database Trends and Applications is hosting a special roundtable webinar. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arcadiadata-dbta-unlockingthepowerofthedatalake-kim-180531-final-180614201420-thumbnail.jpg?width=120&height=120&fit=bounds" /> You have a data lake — now it’s time to unlock its power. Register for the upcoming webinar “Unlocking the Power of the Data Lake” to learn how. As Hadoop adoption in the enterprise continues to grow, so does commitment to the data lake strategy. Two-thirds of Database Trends and Applications readers are either implementing data lake projects this year or researching and evaluating solutions. Data security, governance, integration, and analytics have all been identified as critical success factors for data lake deployments. To educate this growing audience about the enabling technologies and best practices for unlocking the power of the data lake, Database Trends and Applications is hosting a special roundtable webinar.

Unlocking the Power of the Data Lake from Arcadia Data

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0 Are Data Lakes for Business Users Webinar /slideshow/are-data-lakes-for-business-users-webinar/98170684 aredatalakesforbusinessuserswebinar-180522231512
In this webinar, several industry experts discuss the evolution of data lakes and analytical tools, and explore whether business users are really taking advantage of these new data constructs.]]>
In this webinar, several industry experts discuss the evolution of data lakes and analytical tools, and explore whether business users are really taking advantage of these new data constructs.]]> Tue, 22 May 2018 23:15:12 GMT /slideshow/are-data-lakes-for-business-users-webinar/98170684 arcadiadata@slideshare.net(arcadiadata) Are Data Lakes for Business Users Webinar arcadiadata In this webinar, several industry experts discuss the evolution of data lakes and analytical tools, and explore whether business users are really taking advantage of these new data constructs. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/aredatalakesforbusinessuserswebinar-180522231512-thumbnail.jpg?width=120&height=120&fit=bounds" /> In this webinar, several industry experts discuss the evolution of data lakes and analytical tools, and explore whether business users are really taking advantage of these new data constructs.

Are Data Lakes for Business Users Webinar from Arcadia Data

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0 When everybody wants Big Data Who gets it? /slideshow/when-everybody-wants-big-data-who-gets-it-92700587/92700587 arcadiaesgmarketsharekaiserfinalslides1-180402234456
The accelerating supply of big data is converging with accelerating data demand from everyday business users. What does it take to get from Hadoop as a data reservoir to Hadoop as a day-to-day data source for your business and end users? The answer to ‘what’ is ‘how’ and ‘who’. Reducing architectural reliance on ‘small data’ technologies and broadening access to Hadoop hold the key to big data payoff. Join Nik Rouda, Big Data Analyst and blogger at the Enterprise Strategy Group (ESG), as he hosts this webcast featuring guest presentations from real world practitioners Tanwir Danish, VP of Product Development at Marketshare (acquired by Neustar) and Rajiv Synghal, Chief Architect, Big Data Strategy at Kaiser Permanente. Latest research on Hadoop adoption patterns and anti-patterns Putting users at the center of big data utilization and avoiding the data scientist paradox Architectural misconceptions that can tank big data initiatives Security and multi-tenancy strategies to accelerate adoption Retooling skills and organizational thinking when big data is the rule, not the exception]]>
The accelerating supply of big data is converging with accelerating data demand from everyday business users. What does it take to get from Hadoop as a data reservoir to Hadoop as a day-to-day data source for your business and end users? The answer to ‘what’ is ‘how’ and ‘who’. Reducing architectural reliance on ‘small data’ technologies and broadening access to Hadoop hold the key to big data payoff. Join Nik Rouda, Big Data Analyst and blogger at the Enterprise Strategy Group (ESG), as he hosts this webcast featuring guest presentations from real world practitioners Tanwir Danish, VP of Product Development at Marketshare (acquired by Neustar) and Rajiv Synghal, Chief Architect, Big Data Strategy at Kaiser Permanente. Latest research on Hadoop adoption patterns and anti-patterns Putting users at the center of big data utilization and avoiding the data scientist paradox Architectural misconceptions that can tank big data initiatives Security and multi-tenancy strategies to accelerate adoption Retooling skills and organizational thinking when big data is the rule, not the exception]]> Mon, 02 Apr 2018 23:44:56 GMT /slideshow/when-everybody-wants-big-data-who-gets-it-92700587/92700587 arcadiadata@slideshare.net(arcadiadata) When everybody wants Big Data Who gets it? arcadiadata The accelerating supply of big data is converging with accelerating data demand from everyday business users. What does it take to get from Hadoop as a data reservoir to Hadoop as a day-to-day data source for your business and end users? The answer to ‘what’ is ‘how’ and ‘who’. Reducing architectural reliance on ‘small data’ technologies and broadening access to Hadoop hold the key to big data payoff. Join Nik Rouda, Big Data Analyst and blogger at the Enterprise Strategy Group (ESG), as he hosts this webcast featuring guest presentations from real world practitioners Tanwir Danish, VP of Product Development at Marketshare (acquired by Neustar) and Rajiv Synghal, Chief Architect, Big Data Strategy at Kaiser Permanente. Latest research on Hadoop adoption patterns and anti-patterns Putting users at the center of big data utilization and avoiding the data scientist paradox Architectural misconceptions that can tank big data initiatives Security and multi-tenancy strategies to accelerate adoption Retooling skills and organizational thinking when big data is the rule, not the exception <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arcadiaesgmarketsharekaiserfinalslides1-180402234456-thumbnail.jpg?width=120&height=120&fit=bounds" /> The accelerating supply of big data is converging with accelerating data demand from everyday business users. What does it take to get from Hadoop as a data reservoir to Hadoop as a day-to-day data source for your business and end users? The answer to ‘what’ is ‘how’ and ‘who’. Reducing architectural reliance on ‘small data’ technologies and broadening access to Hadoop hold the key to big data payoff. Join Nik Rouda, Big Data Analyst and blogger at the Enterprise Strategy Group (ESG), as he hosts this webcast featuring guest presentations from real world practitioners Tanwir Danish, VP of Product Development at Marketshare (acquired by Neustar) and Rajiv Synghal, Chief Architect, Big Data Strategy at Kaiser Permanente. Latest research on Hadoop adoption patterns and anti-patterns Putting users at the center of big data utilization and avoiding the data scientist paradox Architectural misconceptions that can tank big data initiatives Security and multi-tenancy strategies to accelerate adoption Retooling skills and organizational thinking when big data is the rule, not the exception

When everybody wants Big Data Who gets it? from Arcadia Data

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0 Big Data vs. Big Risk: Real-Time Trade Surveillance in Financial Markets /slideshow/big-data-vs-big-risk-realtime-trade-surveillance-in-financial-markets/92371077 hortonworksarcadiajointwebinaroct6final1-180330003215
Who’s winning the deep forensic analysis ‘arms race’ for compliance? Real-time trade surveillance in global financial markets has created a data tsunami. With greater volumes of data comes greater compliance risk. CNBC reports U.S. Banks have been fined over $200B since the financial crisis. How are compliance teams fighting back to make more of the data and stay out of regulatory hot water? Rapid response to suspect trades means compliance teams need to access and visualize trade patterns, real time and historic data, to navigate the data in depth and flag possible violations. Join Hortonworks and Arcadia for this live webinar: we’ll cover the use case at a top 50 Global Bank who now has deep forensic analysis of trade activity. The result: interactive, ad hoc data visualization and access across multiple platforms – without limits on historic data – to detect irregularities as they happen. ]]>
Who’s winning the deep forensic analysis ‘arms race’ for compliance? Real-time trade surveillance in global financial markets has created a data tsunami. With greater volumes of data comes greater compliance risk. CNBC reports U.S. Banks have been fined over $200B since the financial crisis. How are compliance teams fighting back to make more of the data and stay out of regulatory hot water? Rapid response to suspect trades means compliance teams need to access and visualize trade patterns, real time and historic data, to navigate the data in depth and flag possible violations. Join Hortonworks and Arcadia for this live webinar: we’ll cover the use case at a top 50 Global Bank who now has deep forensic analysis of trade activity. The result: interactive, ad hoc data visualization and access across multiple platforms – without limits on historic data – to detect irregularities as they happen. ]]> Fri, 30 Mar 2018 00:32:15 GMT /slideshow/big-data-vs-big-risk-realtime-trade-surveillance-in-financial-markets/92371077 arcadiadata@slideshare.net(arcadiadata) Big Data vs. Big Risk: Real-Time Trade Surveillance in Financial Markets arcadiadata Who’s winning the deep forensic analysis ‘arms race’ for compliance? Real-time trade surveillance in global financial markets has created a data tsunami. With greater volumes of data comes greater compliance risk. CNBC reports U.S. Banks have been fined over $200B since the financial crisis. How are compliance teams fighting back to make more of the data and stay out of regulatory hot water? Rapid response to suspect trades means compliance teams need to access and visualize trade patterns, real time and historic data, to navigate the data in depth and flag possible violations. Join Hortonworks and Arcadia for this live webinar: we’ll cover the use case at a top 50 Global Bank who now has deep forensic analysis of trade activity. The result: interactive, ad hoc data visualization and access across multiple platforms – without limits on historic data – to detect irregularities as they happen. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/hortonworksarcadiajointwebinaroct6final1-180330003215-thumbnail.jpg?width=120&height=120&fit=bounds" /> Who’s winning the deep forensic analysis ‘arms race’ for compliance? Real-time trade surveillance in global financial markets has created a data tsunami. With greater volumes of data comes greater compliance risk. CNBC reports U.S. Banks have been fined over $200B since the financial crisis. How are compliance teams fighting back to make more of the data and stay out of regulatory hot water? Rapid response to suspect trades means compliance teams need to access and visualize trade patterns, real time and historic data, to navigate the data in depth and flag possible violations. Join Hortonworks and Arcadia for this live webinar: we’ll cover the use case at a top 50 Global Bank who now has deep forensic analysis of trade activity. The result: interactive, ad hoc data visualization and access across multiple platforms – without limits on historic data – to detect irregularities as they happen.

Big Data vs. Big Risk: Real-Time Trade Surveillance in Financial Markets from Arcadia Data

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0 RegTech: Leveraging Alternative Data for Compliance /slideshow/regtech-leveraging-alternative-data-for-compliance/92370763 regtech-leveraging-alt-data-complaince-180330002442
Leading banks and asset managers are leveraging internal and external alternative data sources to improve compliance and regulatory oversight. Join Richard Johnson of Greenwich Associates and Paul Lashmet of Arcadia Data for an informative panel discussion with industry experts from Nordea and RBC Capital Markets discussing how to: Rapidly access and analyse numerous different data sources Develop RegTech solutions while managing total cost of ownership Optimize internal data management through Big Data capabilities Enhance compliance processes using alternative data Meet heightened regulatory expectations around timeliness and quality of data]]>
Leading banks and asset managers are leveraging internal and external alternative data sources to improve compliance and regulatory oversight. Join Richard Johnson of Greenwich Associates and Paul Lashmet of Arcadia Data for an informative panel discussion with industry experts from Nordea and RBC Capital Markets discussing how to: Rapidly access and analyse numerous different data sources Develop RegTech solutions while managing total cost of ownership Optimize internal data management through Big Data capabilities Enhance compliance processes using alternative data Meet heightened regulatory expectations around timeliness and quality of data]]> Fri, 30 Mar 2018 00:24:42 GMT /slideshow/regtech-leveraging-alternative-data-for-compliance/92370763 arcadiadata@slideshare.net(arcadiadata) RegTech: Leveraging Alternative Data for Compliance arcadiadata Leading banks and asset managers are leveraging internal and external alternative data sources to improve compliance and regulatory oversight. Join Richard Johnson of Greenwich Associates and Paul Lashmet of Arcadia Data for an informative panel discussion with industry experts from Nordea and RBC Capital Markets discussing how to: Rapidly access and analyse numerous different data sources Develop RegTech solutions while managing total cost of ownership Optimize internal data management through Big Data capabilities Enhance compliance processes using alternative data Meet heightened regulatory expectations around timeliness and quality of data <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/regtech-leveraging-alt-data-complaince-180330002442-thumbnail.jpg?width=120&height=120&fit=bounds" /> Leading banks and asset managers are leveraging internal and external alternative data sources to improve compliance and regulatory oversight. Join Richard Johnson of Greenwich Associates and Paul Lashmet of Arcadia Data for an informative panel discussion with industry experts from Nordea and RBC Capital Markets discussing how to: Rapidly access and analyse numerous different data sources Develop RegTech solutions while managing total cost of ownership Optimize internal data management through Big Data capabilities Enhance compliance processes using alternative data Meet heightened regulatory expectations around timeliness and quality of data

RegTech: Leveraging Alternative Data for Compliance from Arcadia Data

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0 How to Scale BI and Analytics with Hadoop-based Platforms /slideshow/how-to-scale-bi-and-analytics-with-hadoopbased-platforms/92370546 forrester-arcadia-webinar-03-02-combinedsew-final-180330001903
You’re using Apache Hadoop and cloud-based data platforms, but can your BI and analytics tools keep up? Can you provide fast, secure, self-service access to all the data business users want? Analyzing big data poses multiple challenges. Highly parallel distributed data architecture is one solution, but until recently it has been mostly limited to databases, not business intelligence (BI) application servers. Join this informative webinar with guest speaker Boris Evelson, VP and principal analyst at Forrester Research, and Priyank Patel, co-founder and chief product officer at Arcadia Data. Enterprise architects, data scientists, and application development and delivery (AD&D) pros will learn: What is a distributed BI platform? How is it different from existing BI tools? How to scale BI and visual analytics for users without moving data What features matter most for distributed BI platforms for Hadoop How to unify security natively in Hadoop without more administration]]>
You’re using Apache Hadoop and cloud-based data platforms, but can your BI and analytics tools keep up? Can you provide fast, secure, self-service access to all the data business users want? Analyzing big data poses multiple challenges. Highly parallel distributed data architecture is one solution, but until recently it has been mostly limited to databases, not business intelligence (BI) application servers. Join this informative webinar with guest speaker Boris Evelson, VP and principal analyst at Forrester Research, and Priyank Patel, co-founder and chief product officer at Arcadia Data. Enterprise architects, data scientists, and application development and delivery (AD&D) pros will learn: What is a distributed BI platform? How is it different from existing BI tools? How to scale BI and visual analytics for users without moving data What features matter most for distributed BI platforms for Hadoop How to unify security natively in Hadoop without more administration]]> Fri, 30 Mar 2018 00:19:03 GMT /slideshow/how-to-scale-bi-and-analytics-with-hadoopbased-platforms/92370546 arcadiadata@slideshare.net(arcadiadata) How to Scale BI and Analytics with Hadoop-based Platforms arcadiadata You’re using Apache Hadoop and cloud-based data platforms, but can your BI and analytics tools keep up? Can you provide fast, secure, self-service access to all the data business users want? Analyzing big data poses multiple challenges. Highly parallel distributed data architecture is one solution, but until recently it has been mostly limited to databases, not business intelligence (BI) application servers. Join this informative webinar with guest speaker Boris Evelson, VP and principal analyst at Forrester Research, and Priyank Patel, co-founder and chief product officer at Arcadia Data. Enterprise architects, data scientists, and application development and delivery (AD&D) pros will learn: What is a distributed BI platform? How is it different from existing BI tools? How to scale BI and visual analytics for users without moving data What features matter most for distributed BI platforms for Hadoop How to unify security natively in Hadoop without more administration <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/forrester-arcadia-webinar-03-02-combinedsew-final-180330001903-thumbnail.jpg?width=120&height=120&fit=bounds" /> You’re using Apache Hadoop and cloud-based data platforms, but can your BI and analytics tools keep up? Can you provide fast, secure, self-service access to all the data business users want? Analyzing big data poses multiple challenges. Highly parallel distributed data architecture is one solution, but until recently it has been mostly limited to databases, not business intelligence (BI) application servers. Join this informative webinar with guest speaker Boris Evelson, VP and principal analyst at Forrester Research, and Priyank Patel, co-founder and chief product officer at Arcadia Data. Enterprise architects, data scientists, and application development and delivery (AD&D) pros will learn: What is a distributed BI platform? How is it different from existing BI tools? How to scale BI and visual analytics for users without moving data What features matter most for distributed BI platforms for Hadoop How to unify security natively in Hadoop without more administration

How to Scale BI and Analytics with Hadoop-based Platforms from Arcadia Data

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0 Accelerating Data Lakes and Streams with Real-time Analytics /slideshow/accelerating-data-lakes-and-streams-with-realtime-analytics/92368743 combined451arcadiawebinar25102017shant-v2-180329233916
As organizations modernize their data and analytics platforms, the data lake concept has gained momentum as a shared enterprise resource for supporting insights across multiple lines of business. The perception is that data lakes are vast, slow-moving bodies of data, but innovations like Apache Kafka for streaming-first architectures put real-time data flows at the forefront. Combining real-time alerts and fast-moving data with rich historical analysis lets you respond quickly to changing business conditions with powerful data lake analytics to make smarter decisions. Join this complimentary webinar with industry experts from 451 Research and Arcadia Data who will discuss: - Business requirements for combining real-time streaming and ad hoc visual analytics. - Innovations in real-time analytics using tools like Confluent’s KSQL. - Machine-assisted visualization to guide business analysts to faster insights. - Elevating user concurrency and analytic performance on data lakes. - Applications in cybersecurity, regulatory compliance, and predictive maintenance on manufacturing equipment all benefit from streaming visualizations.]]>
As organizations modernize their data and analytics platforms, the data lake concept has gained momentum as a shared enterprise resource for supporting insights across multiple lines of business. The perception is that data lakes are vast, slow-moving bodies of data, but innovations like Apache Kafka for streaming-first architectures put real-time data flows at the forefront. Combining real-time alerts and fast-moving data with rich historical analysis lets you respond quickly to changing business conditions with powerful data lake analytics to make smarter decisions. Join this complimentary webinar with industry experts from 451 Research and Arcadia Data who will discuss: - Business requirements for combining real-time streaming and ad hoc visual analytics. - Innovations in real-time analytics using tools like Confluent’s KSQL. - Machine-assisted visualization to guide business analysts to faster insights. - Elevating user concurrency and analytic performance on data lakes. - Applications in cybersecurity, regulatory compliance, and predictive maintenance on manufacturing equipment all benefit from streaming visualizations.]]> Thu, 29 Mar 2018 23:39:16 GMT /slideshow/accelerating-data-lakes-and-streams-with-realtime-analytics/92368743 arcadiadata@slideshare.net(arcadiadata) Accelerating Data Lakes and Streams with Real-time Analytics arcadiadata As organizations modernize their data and analytics platforms, the data lake concept has gained momentum as a shared enterprise resource for supporting insights across multiple lines of business. The perception is that data lakes are vast, slow-moving bodies of data, but innovations like Apache Kafka for streaming-first architectures put real-time data flows at the forefront. Combining real-time alerts and fast-moving data with rich historical analysis lets you respond quickly to changing business conditions with powerful data lake analytics to make smarter decisions. Join this complimentary webinar with industry experts from 451 Research and Arcadia Data who will discuss: - Business requirements for combining real-time streaming and ad hoc visual analytics. - Innovations in real-time analytics using tools like Confluent’s KSQL. - Machine-assisted visualization to guide business analysts to faster insights. - Elevating user concurrency and analytic performance on data lakes. - Applications in cybersecurity, regulatory compliance, and predictive maintenance on manufacturing equipment all benefit from streaming visualizations. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/combined451arcadiawebinar25102017shant-v2-180329233916-thumbnail.jpg?width=120&height=120&fit=bounds" /> As organizations modernize their data and analytics platforms, the data lake concept has gained momentum as a shared enterprise resource for supporting insights across multiple lines of business. The perception is that data lakes are vast, slow-moving bodies of data, but innovations like Apache Kafka for streaming-first architectures put real-time data flows at the forefront. Combining real-time alerts and fast-moving data with rich historical analysis lets you respond quickly to changing business conditions with powerful data lake analytics to make smarter decisions. Join this complimentary webinar with industry experts from 451 Research and Arcadia Data who will discuss: - Business requirements for combining real-time streaming and ad hoc visual analytics. - Innovations in real-time analytics using tools like Confluent’s KSQL. - Machine-assisted visualization to guide business analysts to faster insights. - Elevating user concurrency and analytic performance on data lakes. - Applications in cybersecurity, regulatory compliance, and predictive maintenance on manufacturing equipment all benefit from streaming visualizations.

Accelerating Data Lakes and Streams with Real-time Analytics from Arcadia Data

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0 BI on Big Data Presentation /slideshow/bi-on-big-data-presentation/90811172 shanthovsepianarcadiadatabionbigdatapresentation-180315175502
Shant Hovsepian, CTO of Arcadia Data and a panel of experts details the trade-offs between a number of architectures that provide self-service access to data, and industry researcher Mark Madsen discusses the pros and cons of architectures, deployment strategies, and customer examples of BI on big data. Topics include: - Traditional BI platforms based on semantic layers and SQL/MDX generation - Server and desktop BI tools based on direct mapping of data - Distributed BI platforms (e.g., MPP and data native) - OLAP- and SQL-on-Hadoop engines]]>
Shant Hovsepian, CTO of Arcadia Data and a panel of experts details the trade-offs between a number of architectures that provide self-service access to data, and industry researcher Mark Madsen discusses the pros and cons of architectures, deployment strategies, and customer examples of BI on big data. Topics include: - Traditional BI platforms based on semantic layers and SQL/MDX generation - Server and desktop BI tools based on direct mapping of data - Distributed BI platforms (e.g., MPP and data native) - OLAP- and SQL-on-Hadoop engines]]> Thu, 15 Mar 2018 17:55:02 GMT /slideshow/bi-on-big-data-presentation/90811172 arcadiadata@slideshare.net(arcadiadata) BI on Big Data Presentation arcadiadata Shant Hovsepian, CTO of Arcadia Data and a panel of experts details the trade-offs between a number of architectures that provide self-service access to data, and industry researcher Mark Madsen discusses the pros and cons of architectures, deployment strategies, and customer examples of BI on big data. Topics include: - Traditional BI platforms based on semantic layers and SQL/MDX generation - Server and desktop BI tools based on direct mapping of data - Distributed BI platforms (e.g., MPP and data native) - OLAP- and SQL-on-Hadoop engines <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/shanthovsepianarcadiadatabionbigdatapresentation-180315175502-thumbnail.jpg?width=120&height=120&fit=bounds" /> Shant Hovsepian, CTO of Arcadia Data and a panel of experts details the trade-offs between a number of architectures that provide self-service access to data, and industry researcher Mark Madsen discusses the pros and cons of architectures, deployment strategies, and customer examples of BI on big data. Topics include: - Traditional BI platforms based on semantic layers and SQL/MDX generation - Server and desktop BI tools based on direct mapping of data - Distributed BI platforms (e.g., MPP and data native) - OLAP- and SQL-on-Hadoop engines

BI on Big Data Presentation from Arcadia Data

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0 A Tale of Two BI Standards /slideshow/a-tale-of-two-bi-standards/90811171 randyleaarcadiadatatwobistandardspresentation-180315175501
Data lakes often fail because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives? In this talk, we’ll discuss: - Why existing BI tools are architected well for data warehouses, but not data lakes. - The pros and cons of each architecture. - Why every organization should have two BI standards: one for data warehouses and one for data lakes.]]>
Data lakes often fail because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives? In this talk, we’ll discuss: - Why existing BI tools are architected well for data warehouses, but not data lakes. - The pros and cons of each architecture. - Why every organization should have two BI standards: one for data warehouses and one for data lakes.]]> Thu, 15 Mar 2018 17:55:01 GMT /slideshow/a-tale-of-two-bi-standards/90811171 arcadiadata@slideshare.net(arcadiadata) A Tale of Two BI Standards arcadiadata Data lakes often fail because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives? In this talk, we’ll discuss: - Why existing BI tools are architected well for data warehouses, but not data lakes. - The pros and cons of each architecture. - Why every organization should have two BI standards: one for data warehouses and one for data lakes. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/randyleaarcadiadatatwobistandardspresentation-180315175501-thumbnail.jpg?width=120&height=120&fit=bounds" /> Data lakes often fail because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives? In this talk, we’ll discuss: - Why existing BI tools are architected well for data warehouses, but not data lakes. - The pros and cons of each architecture. - Why every organization should have two BI standards: one for data warehouses and one for data lakes.

A Tale of Two BI Standards from Arcadia Data

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0 Four Key Considerations for your Big Data Analytics Strategy /slideshow/four-key-considerations-for-your-big-data-analytics-strategy/90566507 four-key-considerations-big-data-analytics-strategy-180313222814
Learn 4 of the key things to consider as you create your big data analytics strategy from John Meyers (Enterprise Management Associates) and Steve Wooledge (Arcadia Data).]]>
Learn 4 of the key things to consider as you create your big data analytics strategy from John Meyers (Enterprise Management Associates) and Steve Wooledge (Arcadia Data).]]> Tue, 13 Mar 2018 22:28:13 GMT /slideshow/four-key-considerations-for-your-big-data-analytics-strategy/90566507 arcadiadata@slideshare.net(arcadiadata) Four Key Considerations for your Big Data Analytics Strategy arcadiadata Learn 4 of the key things to consider as you create your big data analytics strategy from John Meyers (Enterprise Management Associates) and Steve Wooledge (Arcadia Data). <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/four-key-considerations-big-data-analytics-strategy-180313222814-thumbnail.jpg?width=120&height=120&fit=bounds" /> Learn 4 of the key things to consider as you create your big data analytics strategy from John Meyers (Enterprise Management Associates) and Steve Wooledge (Arcadia Data).

Four Key Considerations for your Big Data Analytics Strategy from Arcadia Data

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0 https://cdn.slidesharecdn.com/profile-photo-arcadiadata-48x48.jpg?cb=1554328591 Arcadia Data provides the first native visual analytics software that runs within modern data platforms for the scale, flexibility, performance and security users need to glean meaningful and real-time business insights and design data-centric applications in the era of big data and IoT. Arcadia Enterprise is purpose-built to analyze large volumes of data without moving it, filling the gap between self-service BI and advanced analytics for use cases like cyber security, connected devices, and customer intelligence. The Arcadia Data platform is deployed by some of the world’s leading brands, including Procter & Gamble, HPE, Royal Bank of Canada, Kaiser Permanente and Neustar. www.arcadiadata.com/ https://cdn.slidesharecdn.com/ss_thumbnails/arcadiamapboxwebinar-final-190207000346-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/visualizing-geospatial-data-at-scale/130816738 Visualizing Geospatial... https://cdn.slidesharecdn.com/ss_thumbnails/3trendformodernizinganalyticsanddatawarehousingin2019-181206191141-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/trends-for-modernizing-analytics-and-data-warehousing-in-2019/125200851 Trends for Modernizing... https://cdn.slidesharecdn.com/ss_thumbnails/ataleof2bistandards-181003223323-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/a-tale-of-2-bi-standards-one-for-data-warehouses-and-one-for-data-lakes-118036860/118036860 A Tale of 2 BI Standar...