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Upcoming

Philip Russom

New Directions in Enterprise IT Architecture: Achieving Business Value via New Data, Hadoop, and NoSQL

Organizations today need to manage, analyze, and visualize diverse data sources such as machines, sensors, social media, Web applications, and so on. Fully leveraging granular data from these sources drives insights into customer behavior, business operations, information security, risk management, and competition, which in turn increase growth, efficiency, and competitive success.

Date: December 2, 2014

Time: 9:00AM PT

Philip Russom


Colin White

How Secure is Hadoop?

Hadoop is rapidly moving from prototyping and standalone solutions to an important component of the enterprise IT ecosystem. At the same time, the volume of data being managed by Hadoop systems in support of enterprise data hubs and refineries, as well as analytic applications, is growing rapidly.

Date: December 3, 2014

Time: 9:00AM PT

Colin White


Fern Halper

Five Innovations in Advanced Analytics

As the value of advanced analytics becomes better-known, many companies face challenges in getting started. A primary challenge is lacking the skill set to make advanced analytics happen. As the market evolves, innovations occurring in software, infrastructure, and organizational practices can open up analytics to new users. These include making analytics easier to use, algorithmic innovations, semantics and analytics, organizational innovation, and the cloud.

Date: December 9, 2014

Time: 9:00AM PT

Fern Halper


Barry Devlin

From Data Discovery to Adaptive Decision Making

Modern businesses must be faster, more flexible, and more responsive than ever before. Traditional BI, focused on predefined reports and rear-view queries, will no longer suffice.

Date: December 10, 2014

Time: 9:00AM PT

Barry Devlin


Fern Halper

Next-Generation Analytics and Platforms for Business Success

More and more, companies are looking to advanced analytics to compete effectively. These analytics include predictive analytics, text analytics, geospatial analytics, big data analytics, and more. As part of this analytics ecosystem, organizations also have to contend with the infrastructure to support the analytics. Appliances, analytics platforms, and unified information architectures have become an important component of this equation. This developing analytics ecosystem can be quite complex.

Date: January 13, 2015

Time: 9:00AM PT

Fern Halper


Philip Russom

Modernizing the Operational Data Store with Hadoop

Operational data stores (ODSs) are currently experiencing a dramatic evolution, as are many data platforms and practices within data warehousing and enterprise data management. The evolution of the ODS is driven mostly by users’ increased usage of big data and advanced analytics, but also by changing practices in data archiving, data staging, and data integration. The result is that ODSs today manage greater data volumes, handle more diverse data, and serve more practical uses than ever before

Date: January 29, 2015

Time: 9:00AM PT

Philip Russom


On Demand

Claudia Imhoff

Enabling Statistics for Everyone: Building an Easy and Sustainable Analytics Infrastructure

The real value of a decision-making environment is not in the creation of reports or simple multi-dimensional analytics. It is in the creation and use of the more sophisticated analytics like statistics and data mining. And the way to support these critical capabilities is by extending the traditional data warehouse environment to include data sets in more fluid, less controlled components in addition to the enterprise data warehouse.

Claudia Imhoff


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