TDWI Webinars

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.


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.

Date: May 25, 2016

Time: 9:00AM PT

Fern Halper, David Stodder

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.

Date: May 31, 2016

Time: 9:00AM PT

David Stodder

Agile, Fast, and Flexible: Five BI and Data Management Strategies for Meeting New Business Challenges

A signature quality of leading companies is their ability to generate data-driven insights quickly so that they can proactively shift strategies to take advantage of new opportunities. They use data to learn sooner how customer preferences are changing, how to adjust when markets are shifting, and how they can reduce inefficiencies in operations so that resources are deployed the right way.

Date: June 9, 2016

Time: 9:00AM PT

David Stodder

Data Preparation for the Rest of Us!

Data preparation for analytics used to reside solely within the IT teams with savvy technical resources. With businesses leaning towards self-service analytics, business analysts and data scientists need data prepared their way on their schedule, not based on IT availability, to drive business forward. Data preparation does not replace traditional data integration or ETL but is complementary to existing business intelligence solutions and allows the business user to easily access the integrated data and combine it with other sets of data thereby realizing the ROI on your BI and analytics investment beyond what your IT teams can deliver.

Date: June 16, 2016

Time: 9:00AM PT

Claudia Imhoff

Accelerating Analytic Insights via the Hybrid Cloud

More often, organizations are looking to the cloud for analytics. The cloud can provide flexibility, elasticity, and convenience. Organizations are using the cloud for a range of business use cases from reporting and sandboxes to production and IoT analytics, and much more. Cloud analytic services offerings are evolving too and becoming more popular – especially with business customers. As a Service (aaS) offerings can target specific subject areas such as churn-detection-as-a-service or fraud-detection-as-a-service. These can help to jump start improved business outcomes much faster than in-house efforts.

Date: June 23, 2016

Time: 9:00AM PT

Fern Halper

On Demand

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