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RESEARCH & RESOURCES

Featured Webinars

  • From Migration to Modernization: Boosting Your Data Infrastructure for Success

    Join this TDWI webinar, with Fern Halper, TDWI’s VP of research; Arnab Sen, VP of data engineering at Tredence; and Sami Akbay, group product manager – data and analytics at Google, to learn how to transition from legacy systems to modern, cloud-based infrastructures, democratize data across the organization, boost operational efficiency, and enable advanced technologies for sustained growth. October 22, 2024

  • Driving Data Quality at Scale with High-Performance Observability

    In this webinar, TDWI senior research director James Kobielus will discuss the value of observability, lineage analysis, and other tools for driving data quality at scale in the cloud. October 24, 2024

  • Building Sophisticated AI Business Applications in the Cloud

    In this webinar, TDWI senior research director Fern Halper will provide an overview of best practices for building sophisticated, high-performance, and low-latency AI business applications in the cloud. October 29, 2024

Upcoming Webinars

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

BI, Analytics, and the Cloud: Strategies for Business Agility

Cloud computing is a major trend that offers advantages in terms of flexibility, dynamic scalability, and agility. Even so, there’s been a lot of marketing hype. The reality is that, until recently, cloud has been slow to take off for business intelligence (BI) and analytics. Organizations have been concerned about security, performance, functionality, and other critical issues. TDWI Research is now seeing a significant shift as more organizations show willingness to experiment with BI and analytics in the cloud and are moving into deployment.

Fern Halper, Ph.D., David Stodder


Governing Big Data and Hadoop

Big data presents significant business opportunities, when leveraged properly. And yet, big data also presents significant business and technology risks, when it is poorly governed or managed.

Philip Russom, Ph.D.


Enabling Self-Service Analytics with Intelligent Data Integration

One of the strongest trends in information technology (IT) today is self service, which puts the power of creating data-driven solutions in the hands of the business user. This way, IT organizations are offloaded; they needn’t create unique datasets, reports, and analyses per user, which frees up IT’s time for other tasks. Furthermore, a broad range of end-users – mostly mildly technical business people – needn’t wait for help from IT, thereby giving them greater agility and creativity, while reducing the time to value and allowing them to apply their business expertise to a well-targeted solution. Therefore, self service is a win-win situation – but only if key pieces of technology are in place.

Philip Russom, Ph.D.


Business, IT, and Self-Service Data Preparation: Can We Talk?

One of the hottest trends today is self-service data preparation. Following the path of front-end tools for self-service business intelligence (BI) and visual analytics, self-service data preparation is aimed at providing nontechnical business users with the ability to explore data and choose data sets to fit their BI and analytics requirements. The goal is to reduce IT hand-holding—an ambitious one considering that, according to TDWI research, in most organizations IT manages nearly all data preparation steps, which can include data ingestion and collection, data transformation, data quality improvement, and data integration. Self-service data preparation thus represents a significant and potentially destabilizing change for IT and the way that IT and business work together.

David Stodder


Land O’Lakes: How Free-Form Data Lakes Are Complementing Structured Data Warehouses

As the data warehouse environment (DWE) continues to evolve, one of its strongest trends is the diversification of data platforms. A rigorously structured relational data warehouse is still at the heart of the DWE, but it is being joined more and more by other platform types, including data platforms based on columns, appliances, graph, streaming data, and open source.

Philip Russom, Ph.D.


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


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