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AtScale

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  • Modernizing Business Intelligence on Big Data Modernizing Business Intelligence on Big Data Surya Mukherjee, Senior Analyst at OVUM, Dave Mariani, Founder & CEO, AtScale Recorded: Sep 13 2016 61 mins
    How do you bridge the gap between high expectations of entrenched BI users and the rapidly changing big data landscape? Diverse data types are now mainstream in every organization and analytics are a ubiquitous enterprise priority. Many companies struggle with reconciling the investment of proven BI with the power of modern big data lakes. But the solution is more obvious than you think.

    Join this session to learn from Surya Mukherjee of OVUM as he shares:

    ● Why the BI-Big Data gap is smaller than it seems
    ● How to leverage your SQL / OLAP / BI investments together with big data for immediate value
    ● What to do and what to avoid for success with BI on Big Data (with real-life customer stories)
  • How to Drive A BI on Hadoop Evolution How to Drive A BI on Hadoop Evolution Eric Sit,Quotient Technology (aka Coupons.com) - Director of Engineering, BI & Data Platform Recorded: Aug 3 2016 58 mins
    How Quotient's Data Leader Drove a BI on Hadoop Evolution

    Recorded Live: Aug 3, 2016

    As a leading site in the highly transactional online offers market, Quotient (aka Coupons.com) processes millions, and stores billions, of transactions daily. Immediate insight into what, when, and how those transactions take place is key to maintaining customer happiness and a competitive edge.

    How did Quotient innovate in the face of exploding data, while enhancing the value of existing investments in BI tools and skillsets? According to Eric Sit, Quotient’s Director of BI and Data Platforms, the key was starting a BI on Hadoop evolution.
  • The Ideal Architecture for BI on Big Data The Ideal Architecture for BI on Big Data Scott Gidley, VP of Product Management - Zaloni Recorded: Aug 1 2016 46 mins
    Watch this recorded online session and learn how to reconcile the changing analytic needs of your business with the explosive pressures of modern big data.

    Leading enterprises are taking a "BI with Big Data" approach, architecting data lakes to act as analytics data warehouses. In this session Scott Gidley, Head of Product at Zaloni is joined by Josh Klahr, Head of Product at AtScale. They share proven insights and action plans on how to define the ideal architecture for BI on Big Data.

    In this recorded session you will learn how to

    Make data consumption-ready and take advantage of a schema-on-read approach
    Leverage data warehouse and ETL investments and skillsets for BI on Big Data
    Deliver rapid-fire access to data in Hadoop, with governance and control
  • Turbo-Charge BI on Hadoop Turbo-Charge BI on Hadoop Josh Klahr, VP of Product, AtScale Recorded: Aug 1 2016 45 mins
    Turbo-Charge BI on Hadoop: The Time is Now

    Want to turn your Hadoop cluster into a super-powerful, analytics data warehouse? Need to run BI queries on Hadoop at top speed?

    Watch this recording of a live best practice session. You'll see how leading companies are super-charging their BI on Hadoop by combining the power of Tableau with the scale of Impala, and accelerating it all with AtScale. In this session, leaders from Cloudera and Tableau share a real-world perspective on

    How to get super-fast performance from BI queries on Hadoop
    Deliver powerful self-service visualization directly on Hadoop
    Leverage existing BI and Hadoop investments to deliver more value to more users
  • Going the Full Hadoop for BI: Why EBates Did It Going the Full Hadoop for BI: Why EBates Did It Mark Stange-Tregear, Ebates, Director of Analytics Recorded: Jun 21 2016 51 mins
    How do you manage data and deliver insights when data volumes are exploding? Does this modern data challenge require more than a ‘traditional’ approach?

    With 30 million+ members globally and hundreds of terabytes of data, Ebates' BI Team moved to a non-traditional approach as a matter of necessity. They defined what a non-traditional approach looks like and kept their Tableau business users happy.

    In this recorded session, EBates BI leader, Mark Stange-Tregear, shares why and how his team successfully transitioned from traditional BI on a traditional data-warehouse, to "all in" self-service BI on Hadoop. Mark shares

    Why: Why he chose to run BI on Hadoop at Ebates
    How: How Ebates made the transition; the plan, challenges and end-goals
    What: What he actually did, what he achieved, and lessons learned
  • How Amex's BI Leader Scaled BI for Big Data How Amex's BI Leader Scaled BI for Big Data Bryan Harrison, American Express - VP of Credit and Operational Risk Recorded: May 3 2016 53 mins
    This session features Amex's VP of Credit and Operational Risk BI, Bryan Harrison. At Amex, Bryan's BI team does risk and fraud analytics on billions of daily transactions to protect the business and its customers.

    How do you give 1000's of analysts access to big data from tools they already love and use --- like Tableau and Excel --- to do critical, real-time analytics?

    In this recorded session, Bryan shares best practices to achieve BI nirvana

    No more data movement - Maintain data fidelity
    No more pre-aggregation - Get nimble, move faster
    No more build and refresh on cubes - Save time & resources
  • 5 Ways To Scale BI on Hadoop 5 Ways To Scale BI on Hadoop Hal Lavendar, Chief Architect, Cognizant; Nino Bice, Principal Architect, Microsoft Recorded: Apr 26 2016 47 mins
    Watch this recording of a recent live online session, featuring Josh Klahr, VP of Product Management at AtScale shedding light on top challenges of scaling BI on Hadoop. He is joined by Nino Bice, Principal Product Manager at Microsoft, and Hal Lavendar, AVP and Chief Architect at Cognizant Technologies. Nino and Hal will share 5 key ways to meet those challenges head-on. In this session, you will learn how to:

    Address the top 5 challenges of scaling BI on Hadoop
    Overcome obstacles and bridge the BI and big data gap
    Achieve scale, speed and success with BI on Hadoop
  • Blueprint: A Modern Data Architecture for BI on Hadoop Blueprint: A Modern Data Architecture for BI on Hadoop Seetha Chakrapany, Director of Analytic and CRM Systems, Macy's Recorded: Mar 10 2016 60 mins
    How Macy's Big Data Leader Innovated for Scale, Speed and Simplicity

    Watch this recording of a live online session, featuring Seetha Chakrapany, Director of Analytic and CRM Systems at Macy's sharing his perspective on modernizing data architecture to enable BI on Hadoop. He's joined by Dan Kogan, Director of Product Marketing for Technology Partners at Tableau, and Eric Thorsen, Vice President, Industry Solutions at Hortonworks. They share trends and insights from the BI and Hadoop sides of the equation.

    In this recorded session, we also cover the critical questions and answers that BI and data infrastructure leaders will need to consider:

    What are the decision triggers for a change to data architecture?

    How and why do you get started with BI on Hadoop?

    What questions do you need to ask related to both the business and the technology?

    Plus, we share best practices to achieve Hadoop nirvana: Manage your big data while giving analysts self-serve access to that data, via existing BI tools.
  • How Yellow Pages Does BI on Hadoop How Yellow Pages Does BI on Hadoop Richard Langlois, Director of Enterprise Data, Yellow Pages Recorded: Sep 18 2015 75 mins
    Yellow Pages published its first directory in 1908: it was Google before Google. It has now become an end-to-end marketing powerhouse, partnered with the largest brands in the world to connect millions of businesses to their prospects and customers.

    When Richard Langlois, Yellow Pages’ Director of Enterprise Data, embarked on their Big Data journey, the team hadn’t had any experience with Hadoop. Using AtScale, Tableau, and Cloudera, the Yellow Pages team built data services for its advertisers and internal sales and marketing team.

    Watch this interactive webinar to find out how to:

    Go from Zero-to-Hero in months by implementing a solid Hadoop Roadmap
    Enable self-service BI on Hadoop without compromising performance or security
    Leverage existing skillset to deliver value to more users, faster, while maintaining control

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