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.


Upcoming

David Loshin

Next-Generation Information Intelligence and Business Analytics

The rate of innovation in the data warehousing, business intelligence, and analytics space has been accelerating over the past few years. The commercialization of massive-scale data management and computing platforms, coupled with a lowered barrier to entry, means that more organizations are exploring newer ways to leverage descriptive and predictive models to drive profitable business decisions.

Date: July 9, 2015

Time: 9:00AM PT

David Loshin


Colin White

The What, Why, and How of a Data Lake

The growing hype surrounding the idea of a data lake (or data refinery) to enhance the data warehousing environment and to support big data is creating significant confusion in the marketplace. The main idea of a data lake is to act as a data landing area for the raw data from the many, and ever increasing number of, data sources in organizations. The data can then be transformed and distributed to downstream systems as required.

Date: July 21, 2015

Time: 9:00AM PT

Colin White


Colin White

Using the Cloud as a Platform for Data Warehousing

Cloud computing is a hot topic as organizations look to take advantage of the agility and pay-as-you-go model the cloud offers. Data warehousing is undergoing significant change—an increasing number of organizations are using the cloud for data warehousing at the same time as they begin to take advantage of new sources of data, advances in business analytics, and new database technologies. However, determining which projects are best suited to cloud-based computing and selecting a cloud solution are not easy tasks.

Date: July 22, 2015

Time: 9:00AM PT

Colin White


Fern Halper

Making Advanced Analytics Simpler: Challenges, Opportunities, and Value

There is no doubt that analytics, and even more advanced analytics is becoming easier to perform. Point and click, drag and drop, and semantic, audio, and other visual interfaces are making advanced analytics such as predictive analytics less complicated. Organizations have taken notice. In recent TDWI survey results, respondents stated that business analysts and business users are becoming and will continue to become the new users for more advanced techniques, outstripping more quantitative staff.

Date: July 23, 2015

Time: 9:00AM PT

Fern Halper


David Loshin

Enterprise Data Warehouse Modernization and Big Data Analytics

Most legacy enterprise data warehouse (EDW) architecture can satisfy many routine workloads associated with operational querying, reporting, and analytics. However, the accelerated growth of data volumes, diversified types of both structured and unstructured data streams, have motivated many business intelligence stakeholders to consider newer technologies that can accommodate these workloads. Today, companies are being asked to support more advanced predictive and prescriptive analytics while also maintaining a nearly flat budget.

Date: July 28, 2015

Time: 9:00AM PT

David Loshin


David Stodder

Visual Analytics for Making Smarter Decisions Faster

Business users today want to move past the limits of spreadsheets and canned business intelligence (BI) reporting to gain a richer, more personalized experience with data. Users want to explore data and discover new insights they can apply readily to improve business strategies, processes, operations, and customer engagement.

Date: August 4, 2015

Time: 9:00AM PT

David Stodder


Fern Halper

Practical Predictive Analytics for the Line-of-Business Analyst

Can business analysts effectively use predictive analytics? Adoption of predictive analytics and other advanced analytics has increased for a number of reasons, including a better understanding of the value of the technology and the availability of computing power. Economic factors are also a driving force in utilizing predictive analytics for business as companies strive to remain competitive. 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.

Date: August 20, 2015

Time: 9:00AM PT

Fern Halper