RESEARCH & RESOURCES

Featured Webinars

  • Enabling Data Science to Be Data Science: Strategies for Increasing Self-Service Data Science

    Data science offers great potential for what it can contribute to business strategy and operations—that is, if data scientists are actually able to do data science rather than spend most of their time on data management and preparation. TDWI finds that most data science projects spend the majority of time on these areas rather than on development of analytics, models, and algorithms. To increase business value, organizations need solutions that will flip this ratio. January 23, 2018 Register

  • Ask the Expert on The UX Guide to Analytics
    TDWI Members Only

    Enterprise analytics spans a wide array of categories but they all have one thing in common, they require human interaction to realize value. However, much of that value is often left on the table. Factors such as user interviews, persona design, stakeholder buy in, wireframing, iteration, adoption and feedback are underutilized and greatly increase the risk of user disengagement and stakeholder frustration. Analytics managers and dashboard creators can miss the opportunity to leverage user motivations to drive success. January 25, 2018 Register

  • Making Predictive Analytics Work – 5 Keys to Successful Model Deployment and Management

    Organizations are excited about predictive analytics and machine learning for a number of reasons. Companies want to better understand customer behavior. They want to better predict failures in their infrastructure. The uses for predictive analytics are extensive and growing. February 8, 2018 Register

Upcoming Webinars

  • Enabling Data Science to Be Data Science: Strategies for Increasing Self-Service Data Science

    Data science offers great potential for what it can contribute to business strategy and operations—that is, if data scientists are actually able to do data science rather than spend most of their time on data management and preparation. TDWI finds that most data science projects spend the majority of time on these areas rather than on development of analytics, models, and algorithms. To increase business value, organizations need solutions that will flip this ratio. January 23, 2018 Register

  • Ask the Expert on The UX Guide to Analytics
    TDWI Members Only

    Enterprise analytics spans a wide array of categories but they all have one thing in common, they require human interaction to realize value. However, much of that value is often left on the table. Factors such as user interviews, persona design, stakeholder buy in, wireframing, iteration, adoption and feedback are underutilized and greatly increase the risk of user disengagement and stakeholder frustration. Analytics managers and dashboard creators can miss the opportunity to leverage user motivations to drive success. January 25, 2018 Register

  • Making Predictive Analytics Work – 5 Keys to Successful Model Deployment and Management

    Organizations are excited about predictive analytics and machine learning for a number of reasons. Companies want to better understand customer behavior. They want to better predict failures in their infrastructure. The uses for predictive analytics are extensive and growing. February 8, 2018 Register

  • Extending Your Data Warehouse Environment with Hadoop: Bringing Enterprise and External Data Together

    Surveys run by TDWI show that roughly a fifth of mature data warehouse environments now include Hadoop in production. Hadoop is becoming entrenched in warehousing because it can improve many components of the data warehouse architecture—from data ingestion to analytics processing to archiving—all at scale with a reasonable price. February 27, 2018 Register

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

Getting to the Next Level with Visual Analytics and Governed Data Discovery

Dull reports and static bar charts are old news: Business users today are excited about modern visual analytics, data discovery, and intuitive business intelligence. Tools, applications, and cloud-based services are making it easier for users to derive powerful, actionable insights from a widening array of data. Users across organizations may finally have an alternative to limited spreadsheets and BI reports – and to waiting in IT’s backlog for developers to give them what they need.

David Stodder


Delivering Business Value Faster with Visual Data Discovery

Hidden inside data are insights that could change the game for your business – that is, if your decision makers can discover and apply them in time to make a difference! Nothing is more frustrating to business users than having to wait out long IT development cycles for business intelligence (BI) tools and data warehousing systems just to gain access to the data they need right now. Fortunately, with the advent of visual analytics and discovery tools, the journey to data insight is getting easier and faster. Cloud computing is accelerating time to business value even further by giving organizations the option of bypassing the delays and difficulties of on-premises deployment.

Fern Halper, Ph.D., David Stodder


When Worlds Collide: Using the Data Lake to Connect Old and New Technologies

Legacy information technology environments usually consist of aging components, typically acquired over time to address specific business needs. While these systems met past needs, emerging opportunities and business pressures have motivated organizations to consider innovative data management technologies.

David Loshin


Data Warehouse Modernization in the Age of Big Data Analytics

Data warehouses (DWs) and requirements for them continue to evolve. DWs are more relevant than ever, as they support operationalized analytics, and wring business value from machine data and other new forms of big data. Hence, it’s important to modernize a DW environment, to keep it competitive and aligned with business goals, in the new age of big data analytics. Yet, user organizations struggle to stay educated about trends and take the right action to modernize their DW investments. Many users need to catch up by deploying a number of upgrades and extensions to their existing DW environments and by adopting modern development methods. Once caught up, they need a strategy for continuous modernization.

Philip Russom, Ph.D.

Content Provided by TDWI, IBM, Pentaho, SAP, SAS, TimeXtender


Empowering Business Users with Analytics and Data Discovery

Demand is accelerating across organizations for better and faster access to data. Business executives, managers, and frontline users in operations want the power to move beyond the limits of spreadsheets so they can engage in deeper analysis and use data insights to transform all types of decisions. Newer tools and methods are making it possible for organizations to meet the demands of nontechnical users by enabling them to access, integrate, transform, and visualize data without traditional IT hand-holding.

David Stodder


Rapid Deployment of Advanced Behavioral Analytics

The continued growth of interactive businesses combined with the explosive diffusion of online, mobile, and IoT (Internet of Things) touch points has enabled organizations to develop business applications involving millions, if not orders of magnitude more interactions and transactions. The success of the business, though, depends on driving the customers and users toward profitable transactions. Examples include purchasing products viewed on an eCommerce web site, recommending an article to a friend, or triggering automated controls within an industrial environment to avoid a part failure. These are examples of scenarios that are informed through behavioral analytics.

David Loshin


Are You Ready for Hadoop? Introducing the TDWI Hadoop Readiness Assessment

A recent TDWI survey shows that Hadoop clusters in production are up 60 percent over two years. This is no surprise because use cases for Hadoop in data warehousing, business intelligence, and analytics are well established. In addition, applications of Hadoop for archiving, content management, and operational applications are emerging into prominence. These developments show that Hadoop usage is diversifying broadly across and within mainstream enterprises, such that Hadoop will eventually be a common platform for many purposes in many IT portfolios.

Fern Halper, Ph.D., Philip Russom, Ph.D.

Content Provided by TDWI, IBM, Cloudera, MapR, MarkLogic, Teradata


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