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Harness the Power of Big Data

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  • IBM PureData System for Analytics - Simple is STILL better IBM PureData System for Analytics - Simple is STILL better IBM Recorded: Jan 5 2015 2 mins
    A lot of things can be simple. And simple can be good in a lot of ways. Because when something is simple, it’s faster. It’s smarter. It’s lighter. It’s stronger. That’s why the IBM PureData System is designed with ‘simple’ in mind. It’s optimized and fine-tuned with built-in expertise for easy delivery of data to today’s demanding applications – leaving the complexity behind. The IBM PureData System – just another way in which simple is still better.
  • IBM PureData Analytics for Mid-Sized Companies IBM PureData Analytics for Mid-Sized Companies IBM Recorded: Jan 5 2015 3 mins
    The PureData System for Analytics Mini Appliance gives mid-sized companies rich analytics capabilities without straining their budget, all in a single and easy-to-manage system. As an appliance, it’s data-load-read in hours and is easy to install.
  • How Modern is Your Data Warehouse? How Modern is Your Data Warehouse? William McKnight, McKnight Consulting Group Recorded: Oct 22 2014 61 mins
    Clients are looking to modernize their data warehouse environments to boost performance, add capacity, meet new analytic requirements and incorporate new technologies to take advantage of big data. Incorporating data warehouse appliances, next generation database technology, and new technologies - like in-memory, stream computing, or Hadoop – help organizations gain new business insights across all data, build confidence in those insights and optimize their warehouse infrastructure.

    Data warehouse modernization is about leveraging solutions that build on existing investments rather than replacing them, enabling organizations to analyze more information, deliver insight faster and drive new analytic capabilities.

    Join this webcast to learn more about the challenges facing organizations and how you can modernize your data warehouse to capitalize on big data.
  • Essential Guide to Using Data Virtualization for Big Data Analytics Essential Guide to Using Data Virtualization for Big Data Analytics Mike Gualtieri, Principal Analyst, Forrester Recorded: Oct 22 2014 64 mins
    Business is driving the need for better Analytics - historical, real-time, predictive, and cognitive - across a number of domains including customer, product, operations and more to become more competitive. Mirroring that, the data available to companies for such analytics is exploding in volume and complexity. Companies are adopting a myriad technologies from traditional data warehouses, OLAP tools, DW appliances, Big Data / Hadoop systems and streaming real-time analytics platforms to take advantage of these opportunities.

    While each specialized analytics platform deliver the most value in specific areas, yet other overall value to the business is maximized when they are combined into an integrated Analytics Platform using Data Virtualization as an essential component of your overall Analytics strategy. It provides cross platform logical views of data and analytic insights across the enterprise and enables flexibility to adapt to new business needs, technology migrations and data sources.

    Things you will learn:
    - Key business drivers and patterns for Advanced Analytics
    - Blueprint for an Integrated Analytics Platform and Logical Data Warehouse
    - Combining Best in class Analytics Platforms from IBM with Denodo Data Virtualization
    - Successful Use Case Patterns
  • Build Confidence in Big Data Build Confidence in Big Data Judith Hurwitz, President and CEO, Hurwitz & Associates Recorded: Oct 21 2014 59 mins
    Big data won't deliver big benefits to your organization if you don't trust it. Before you can put it to work, you need to find the information you need, understand it and assess its quality, building confidence. Integrating it with other data, consolidating it into a unified view, managing it across its lifecycle, and preserving its privacy and security can help you harness the power of the data for both analytics and ongoing operations.

    Join this webcast to learn how other organizations are doing just that with solutions from IBM InfoSphere. You'll get insights into their strategies as well as the practical steps for getting started with integration and governance for all your data.
  • eHarmony Adopts IBM PureData System to Reduce Data Processing by 4 Times eHarmony Adopts IBM PureData System to Reduce Data Processing by 4 Times eHarmony and IBM Recorded: Oct 21 2014 3 mins
    eHarmony processes more than 3.5 million matches daily and serves over 51 million registered members. By leveraging IBM PureData System, they were able to decrease processing time from hours to minutes, enabling faster insights into user data and ultimately adding business value.
  • Bon Ton Optimizes the Client Experience with IBM PureData for Analytics Bon Ton Optimizes the Client Experience with IBM PureData for Analytics Bon Ton and IBM Recorded: Oct 21 2014 2 mins
    Bon Ton is able to provide customers with an innovative and convenient shopping experience by understanding what customers want before they walk into the stores thanks to IBM PureData for Analytics. After implementing an IBM Big Data & Analytics solution, Bon Ton is now able to advertise and promote products that their customers want at the price they want.
  • How to Calculate Data Confidence How to Calculate Data Confidence Rodney Brown, UBM, David Corrigan, IBM InfoSphere, Nathaniel Rowe, Aberdeen Group Recorded: Sep 18 2014 64 mins
    Data confidence is an abstract notion in most organizations. Yet it is critical in order to make your front line workers trust and act upon big data and analytic insight, as even the most game-changing analytics will have no impact if your team doesn't use them, because they don't trust in the data or the insights. Learn about compelling new research that identifies the critical criteria to measure and score confidence levels in customer data to make better business decisions. You will also learn about a new online tool that provides a fast and easy way for attendees to obtain their score.

    View this webinar to learn how to:
    - Calculate data confidence and improve the adoption of big data & analytics
    - Utilize data confidence scores to align resources to new big data & analytics projects
    - Calculate and share data confidence in your big data projects

    Moderator: Rodney Brown, Editor, UBM

    Panelists:
    David Corrigan, Director of Product Marketing, IBM InfoSphere;
    Nathaniel Rowe, Research Analyst, Aberdeen Group
  • Optimizing Your Data Warehouse for Big Data Optimizing Your Data Warehouse for Big Data Stephen Faig, Nancy Hensley, Deirdre Mahon Recorded: Sep 9 2014 60 mins
    Since the eighties, companies have invested millions of dollars designing, implementing and updating enterprise data warehouses as the centerpiece of their business intelligence systems. The founding principle of the data warehouse was the same one we share today: to use data to drive better business decisions. But the data sources have grown, not just in sheer volume, but in varieties outside the domain of traditional data warehousing. To remain competitive in the era of big data, businesses need to augment their data warehouse to achieve faster, more efficient and more scalable analytical processes.

    Is your data warehouse a big data building block or a bottleneck? Join us for this special roundtable webcast on optimizing your data warehouse for big data. Don't miss this opportunity to gain a deeper understanding of the key trends driving the future of data management and analysis.

    Moderator: Stephen Faig, Business Development Manager, Unisphere Media

    Panelists:
    Nancy Hensley, Director, Marketing & Strategy Database & Systems, IBM
    Deirdre Mahon, VP Marketing, RainStor
  • The Next Generation of Big Data: New IBM Information Management Cloud Solutions The Next Generation of Big Data: New IBM Information Management Cloud Solutions IBM Recorded: Sep 8 2014 23 mins
    "The increasing prevalence of cloud, mobile, and social technologies is opening the floodgates of data generation and analysis. Leading companies are able to create actionable insight from big data and analytics to deepen client engagement, go after new markets, and respond to the needs of the business faster. They are driving innovation across the enterprise faster, and using cloud at the core of their business strategy to innovate iteratively and with more agility.

    Learn about IBM's new and expanded Information Management capabilities now delivered in the cloud, including: Hadoop based analytics, stream processing, in-memory computing, data management, and information integration and governance. Data is critical for a competitive advantage, and clients can take advantage of these new technologies today to deploy and deliver analytics and insights in an agile way, without sacrificing security and privacy. "

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