RESEARCH & RESOURCES

Featured Webinars

  • Practical Predictive Analytics – Results of New TDWI Best Practices Research

    Predictive analytics is now part of the analytics fabric of organizations. TDWI research indicates that it is in the early mainstream phase of adoption. Yet, even as organizations continue to adopt predictive analytics and machine learning, many are struggling to make it stick. Challenges include lack of skills, executive and organizational support, and data infrastructure issues. June 21, 2018 Register

  • Modern Data Architectures to Support Modern Analytics

    Many organizations today are scrambling to meet the needs of new data types and analytics. TDWI research shows that companies are often analyzing data from multiple sources, including structured data, unstructured data, real-time streaming data, location data, and transactional data. They are making use of new techniques such as text analytics and machine learning, and they are moving towards self-service analytics. The traditional data warehouse or data mart is often limited in its ability to support these modern analytics in a fast and friendly way. July 12, 2018 Register

  • How to Design a Data Lake with Business Impact in Mind

    A quarter of organizations surveyed by TDWI in 2017 say they already have a data lake in production, while another quarter say their lake will be in production within 12 months. Although data lakes are still rather new, user organizations have adopted them briskly. Why has the data lake gotten so popular, so fast? July 24, 2018 Register

Upcoming Webinars

  • Practical Predictive Analytics – Results of New TDWI Best Practices Research

    Predictive analytics is now part of the analytics fabric of organizations. TDWI research indicates that it is in the early mainstream phase of adoption. Yet, even as organizations continue to adopt predictive analytics and machine learning, many are struggling to make it stick. Challenges include lack of skills, executive and organizational support, and data infrastructure issues. June 21, 2018 Register

  • Modern Data Architectures to Support Modern Analytics

    Many organizations today are scrambling to meet the needs of new data types and analytics. TDWI research shows that companies are often analyzing data from multiple sources, including structured data, unstructured data, real-time streaming data, location data, and transactional data. They are making use of new techniques such as text analytics and machine learning, and they are moving towards self-service analytics. The traditional data warehouse or data mart is often limited in its ability to support these modern analytics in a fast and friendly way. July 12, 2018 Register

  • How to Design a Data Lake with Business Impact in Mind

    A quarter of organizations surveyed by TDWI in 2017 say they already have a data lake in production, while another quarter say their lake will be in production within 12 months. Although data lakes are still rather new, user organizations have adopted them briskly. Why has the data lake gotten so popular, so fast? July 24, 2018 Register

  • Achieving High-Value Analytics with Data Virtualization

    Analytics projects are critical to business success, and as a result, they are growing in size, number, complexity, and perhaps most important, in their data requirements. TDWI finds that data scientists, business analysts, and other personnel need to view and access data that resides in multiple sources, both on premises and in the cloud, to draw insights from data relationships and discover important patterns and trends. July 31, 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

Modernizing Your Data Warehouse Environment

“Throw the baby out with the bathwater!” We hear that a lot. Changing business environments and competitive pressures have driven companies to seek a new edge from innovative technologies such as specialized data stores and the cloud. Today’s business intelligence (BI) and analytics implementation experts face disruptive decisions as they strive to support their business users’ shifting and diverse analytical needs. Increasing volumes and sources of data (on premises and in the cloud), technology adoption, more complex data integration and quality issues, and lower data latencies are just a few of the challenges that must be addressed.

Claudia Imhoff, Ph.D.


Harnessing the Power of Embedded Analytics for Financial Services

Firms in financial services and many other industries are under pressure to improve efficiency, productivity, and decision-making power. For both daily operational and strategic decisions, organizations need to draw insights quickly from quality data so that they can understand and act on changes in markets, regulations, operations, customer behavior, fraud patterns, and the competitive landscape. Financial services firms need to be smarter and faster to survive in an industry where business models are changing and old ways of managing risk are out of date.

David Stodder


Marketing Analytics Meets Artificial Intelligence

The world of marketing and the world of advanced analytics have been winding towards each other for years. TDWI research indicates that marketing is often one of the first areas in an organization that makes use of advanced analytics. Marketers understand the value that analytics can provide to understand customers and the customer journey. Marketing analytics provides insight gathered from data analysis that can make marketing more efficient and effective.

Fern Halper, Ph.D., David Stodder


Combat Rising Integration Complexity with dPaaS

Today's integration complexities are supersized. Businesses must contend with unprecedented volumes and varieties of data at a time of growing IT resource scarcity and aging integration software. Throw into the mix the high demands—and even higher expectations—placed on analytics as a way of driving business performance, and it's easy to see why many integration environments are overwhelmed and underperforming.

David Loshin


10 Best Practices for Running Your Business Smarter with Advanced Analytics

In today’s competitive environment, organizations not only want to analyze the past, they also want to understand the present and predict the future. Likewise, organizations want to gain insights from a wide variety of data, ranging from structured, transactional data and unstructured text to spatially enhanced data or machine data from the Internet of Things. TDWI research indicates that many organizations are at an inflection point with analytics—they are making the move from visualizations and dashboards to more advanced analytics such as predictive analytics, text analytics, geospatial analytics, graph engines,and streaming analytics.

Fern Halper, Ph.D.


Data Warehouse Modernization and Analytics for the Digital Enterprise

More and more, organizations want to base decisions on facts, have complete views of customers, manage operations by the numbers, predict and plan strategically, and compete on analytics. As a foundation for achieving these goals, organizations need a modern infrastructure for data warehousing and business analytics.

Philip Russom, Ph.D.


Faster BI for the Masses: How Search Can Make Analytics More Accessible

Business intelligence is critical to getting answers from data, but for many users it is also a huge source of frustration. Since its beginning, the mission of BI has been to make it faster and easier to locate the right data, query it, and return meaningful answers for reporting and analysis. Newer data visualization and discovery tools have improved the user experience, and data warehouses and data lakes have added terabytes to the data within reach. Yet, it still can be a slow and difficult process to get to the most relevant data without help from technical experts. Users often have to wait for their answers and unless the technical experts also have a strong understanding of the business, the answers are usually inadequate—and the process starts all over again.

David Stodder


TDWI Membership

Get immediate access to training discounts, video library, BI Teams, Skills, Budget Report, and more

Individual, Student, & Team memberships available.