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Upcoming

David Stodder

Achieving Faster and More Agile BI and Analytics with Virtual Data Processing

Speed, agility, and intelligence are competitive advantages that nearly all organizations seek. To seize these advantages, organizations require timely, diverse, complete, and accurate data. Unfortunately, traditional data warehouse extraction, transformation, and loading (ETL) processes are not fast enough. They put too much burden on ETL developers to understand every nuance of every data source, and it’s getting worse as Hadoop and other big data sources become part of the mix. How can organizations take advantage of new big data sources to deliver complete and diverse views of data—and get beyond the limits of traditional data warehouses?

Date: August 27, 2014

Time: 9:00AM PT

David Stodder


Claudia Imhoff

Five Hot Trends for Enabling Your Data Management and Decision-Making Environment

Big data analytics, mobile devices, cloud-based solutions, self-service BI, and predictive analytics—these are the major trends impacting today’s decision-making environments. Exciting, yes, but enabling these trends can also be quite disruptive to traditional data management processes and the implementers, analysts, and decision makers themselves.

Date: August 28, 2014

Time: 9:00AM PT

Claudia Imhoff


Fern Halper

Forward Looking BI: The next step in the analytics journey

Reports and dashboards that utilize historical data to gain insight are just the beginning of a company’s analytics journey. Advances in technology including predictive capabilities can help organizations gain competitive advantage by helping them discover trends, patterns, and relationships in data and guide their next course of action. In the past, predictive analytics has been the realm of statisticians and other quantitative individuals and was often separated from BI activities.

Date: September 9, 2014

Time: 9:00AM PT

Fern Halper


Philip Russom

Data Management Best Practices in the Age of Big Data and Real-Time Operations

The incremental movement toward real-time operation is the most influential trend today in data-driven IT disciplines such as business intelligence (BI), data warehousing (DW), and data integration (DI). From a technology viewpoint, collecting, processing, and delivering data is hard enough; doing it in real time requires effort that is downright Herculean. Thanks to the big data phenomenon, the volume of data continues to swell, exacerbating the situation.

Date: September 10, 2014

Time: 9:00AM PT

Philip Russom


Claudia Imhoff

Architecture Matters: Real-Time In-Memory Technologies Do Not Make Data Warehousing Obsolete

For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well-thought-out architecture for designing and implementing large-scale DW environments. The benefits from these architectures are well documented, but enterprises are faced with new and disruptive demands from their business users. The question becomes: How do we maintain a stable analytical environment, yet bring in the technological innovations so desperately needed?

Date: September 11, 2014

Time: 9:00AM PT

Claudia Imhoff


Colin White

The Role of Hadoop in BI and Data Warehousing

Increasing interest in using Hadoop for data management, transformation, and analysis has led to significant development efforts by commercial vendors to enhance and extend the open source Apache Hadoop framework and offer a range of different Hadoop solutions. Many of these solutions can be used to enhance and extend the current BI and data warehousing environment.

Date: September 16, 2014

Time: 9:00AM PT

Colin White


David Stodder

Making Data Beautiful for Business Users: Tips for Creating Rich, Visual, and Actionable User Experiences

Data “democratization” is here. Data is in demand today from an ever-widening community of users who seek data-driven insights to inform critical decisions and actions. To move business intelligence and analytics beyond just the specialists, applications must be “beautiful” and the user experience must be rich, visual, interactive, and actionable.

Date: September 23, 2014

Time: 9:00AM PT

David Stodder


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    Channels by Topic

    • Agile BI »
      Includes:
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      Includes:
      • Advanced Analytics
      • Diverse Data Types
      • Massive Volumes
      • Real-time/Streaming
      • Hadoop
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    • Business Analytics »
      Includes:
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      Includes:
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      Includes:
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      Includes:
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    • Data Management »
      Includes:
      • Data Quality
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      • ETL
      • CDI
      • Master Data Management
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    • Data Warehousing »
      Includes:
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      Includes:
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      Includes:
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      • BPM, CRM, SCM
    • Master Data Management »
      Includes:
      • Business Definitions
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      • ETL, EAI, EII
      • Replication
      • Data Governance

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