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RESEARCH & RESOURCES

Featured Webinars

Upcoming Webinars

  • Expert Panel: Real-Time Analytics Use Cases and Architectures

    In this expert panel, TDWI senior research director James Kobielus will discuss the chief enterprise use cases for real-time analytics and the principal architectural considerations for data, analytics, and IT professionals seeking to optimize their infrastructures for these applications. December 9, 2024 Register

International Broadcasts

TDWI Webinars on Big Data, Business Intelligence, Data Warehousing & Analytics

TDWI Webinars deliver unbiased information on pertinent issues in the big data, business intelligence, data warehousing, and analytics industry. Each live Webinar is roughly one hour in length and includes an interactive question-and-answer session following the presentation.


On Demand

Modernizing the Traditional BI Environment

Key BI industry growth areas are focused on big data, advanced analytics, cloud computing, and supporting mobile workers. When they are marketing and writing about using these technologies, vendors, the press, and analyst organizations usually focus on building new and leading-edge systems and applications.

Colin White


BI in the Cloud

The cloud services model offers much in the way of potential benefits to businesses in terms of efficiency and cost savings. It’s no wonder that many enterprise applications have moved to public, private, or hybrid clouds. Although business intelligence applications have been slower to move to the cloud—usually because of data security concerns—this is starting to change.

Fern Halper, Ph.D.


Introducing the TDWI Big Data Maturity Model

Many end-user organizations are currently commencing or expanding solutions for big data and big data analytics. These organizations want to understand how to approach big data and where they stand relative to other companies, especially their competitors. In late October 2013, TDWI launched its Big Data Maturity Model Assessment Tool, which can help to guide IT and business professionals on their big data journey. The assessment looks at companies across five dimensions that impact maturity, including organization, infrastructure, data management, analytics, and governance.

Fern Halper, Ph.D., Krish Krishnan

Content Provided by TDWI, IBM, Cloudera, MarkLogic, Pentaho


Predictive Analytics for Accelerating Business Advantage

Predictive analytics is quickly becoming a decisive advantage for achieving desired business outcomes, including higher customer profitability, stickier websites, more relevant products and services, and more efficient and effective operations and finances. Predictive analytics involves methods and technologies to help organizations spot patterns and trends in data, test large numbers of variables, develop and score models, and mine data for unexpected insights. Sources for predictive analytics are expanding to include machine data and semi-structured and unstructured data, making it important to include text analytics and mining in technology portfolios.

Fern Halper, Ph.D.


Geospatial Analytics for Business Value

More and more, companies are looking to a variety of data types and new forms of analysis in order to remain competitive. Geospatial data is emerging as an important source of information, both in traditional and big data analytics. Companies are using geospatial data and geospatial analytics in applications ranging from marketing to operations. The analytics are moving past mapping to more sophisticated use cases.

Fern Halper, Ph.D.


Data Exploration and Analysis in the Age of Big Data: Finding Information and Gaining Results Faster than You Thought Possible

Organizations today are seeking to drive deep analysis, detect patterns, and find anomalies across terabytes or petabytes of raw big data. Whether you’re trying to discover the root cause of the latest customer churn or the hidden costs that are eroding the bottom line, you need analytic tools and techniques that work well with unstructured and multi-structured data in its original raw form. Apache Hadoop is maturing as a loosely coupled stack for inexpensive batch storage, where you don't need to know data formats or schemas to store and process the data.

Philip Russom, Ph.D.


The Role and Benefits of In-Memory Computing for BI Analytics

There is considerable buzz in the IT industry about in-memory technologies. At the same time, there is considerable confusion about the role and benefits of these technologies in business intelligence processing and performance. A major reason for this confusion is that in-memory computing means different things to different people.

Colin White


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