RESEARCH & RESOURCES

Featured Webinars

Upcoming Webinars

  • Using Data Exploration to Accelerate Traditional and Data Science Analytics Processes

    Learn about visual data exploration's role in analytics cycles and streamlining processes, integrating it with data preparation, and how data exploration can speed time to insight. November 27, 2018 Register

  • Automating Modern Data Lake Pipelines

    Data management challenges can often make finding value in an on-premises or cloud data lake extremely difficult. Learn about the evolution of the modern data lake, how to make it efficiently ingest data in real time, and how data lake pipelines can be automated. November 29, 2018 Register

  • Open Source for Predictive Analytics and Data Science: Trends, Opportunities, and Challenges

    Learn about the pros and cons of open source for predictive analytics and data science. We’ll discuss the trends in open source analytics, commercial versus open source options for analytics, and how vendors support open source analytics. December 4, 2018 Register

  • Emerging Trends for the Data-Centric Organization

    Learn about key data-centric trends, including the role of the citizen analyst and its emergence as the nontechnical data champion, the importance of educating and training for data awareness, the value of self-service, the changing role of IT, and why you need data governance. December 5, 2018 Register

  • Best Practices for Managing and Monitoring Open Source Predictive Models

    Building a predictive analytics/machine-learning model is far earlier than deploying one, which can take six months or more. Learn how to overcome deployment challenges and monitor models in production. the role open source plays, and what technologies can help support deployment of these models. December 6, 2018 Register

  • Best Practices for Real-Time Analytics for High Data Volumes

    Learn about hybrid transactional/analytical processing, an alternative architecture that can simultaneously balance transactional and analytical processing. We’ll explain how you can reduce traditional (ETL), manage data storage according to usage, and perform in-memory data management. December 6, 2018 Register

  • What’s Ahead in Analytics in 2019?

    Experts discuss the hottest trends in analytics, including: predictive analytics/machine learning/AI, self-service analytics, robotic process automation, and intelligent and automated analytics. December 10, 2018 Register

  • Squeeze Every Drop of Business Value from Your Data Lake

    Data catalogs contribute ease, precision, and productivity of analytics, self-service, and governance to modern data platforms. Learn how a catalog can inventory data in a data lake for self-service data exploration and data-driven operations and help users find the right data quickly. December 11, 2018 Register

  • What’s Ahead in Data Management in 2019?

    Data is evolving into larger volumes from new sources in a wide array of structures, containers, and interfaces. An expert panel discusses data management trends, including new data platforms (Hadoop, cloud computing, and columnar databases), cloud data management, advancements in data catalogs and metadata, and data governance and stewardship. December 18, 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

End Your Data Struggle: How to Seamlessly Analyze Disparate Data

Many organizations today are struggling to get value from their data and advanced analytics initiatives. The struggle begins with data diversity, as organizations are trying to support new apps, customer channels, sensors, and social media outlets. Each source may have its own data structure, quality, and container (in the form of files, documents, messages). The struggle is exacerbated by the exploding volume of data that must be captured, processed, stored, and delivered to the right users in a state that is fit for their own individual needs.

Philip Russom, Ph.D.


Creating Value with Unified Governance

Certainly, every business leader wants to have trusted, secure, consistent and usable information. But data volumes and systems complexity has been increasing for years and most organizations rarely prioritize data governance, so why care now? We’re at the brink of a perfect storm of unprecedented IT megatrends. The convergence of Cloud, Social, Mobile and Big Data foreshadows the upcoming tsunami of data ripe with potential business value. But it will also make the frustrating complexity of your traditional on-premises transactional data management challenges appear amazingly “manageable” in contrast.

Claudia Imhoff, Ph.D.


Take a Dive into the Data Lake

Many organizations have a serious interest in data lakes, at the moment, because of the business analytics and new data-driven practices that lakes promise. Yet, these organizations still aren’t quite ready to take a dive into a data lake. Whether they are unable to define standard structures, align and maintain business meanings, or create a governance strategy, these companies struggle to anticipate what truly lies beneath the surface of the data lake.

Philip Russom, Ph.D.


Rethinking Enterprise BI in a Self-Service World: Balancing User Freedom with Enterprise IT Responsibilities

Both product and tech leaders have always recognized that business intelligence (BI) is most valuable when it is pervasive, contextual, and actionable. A new generation of solutions -- embedded BI – provides unprecedented power to weave reporting and analytics into the fabric of apps and business processes.

David Stodder


Achieving Integration Agility, Scale, and Simplicity via Cloud-Based Integration Platform-as-a-Service

Many firms have mandates to move to clouds, control IT costs, integrate disparate applications, deliver data-driven solutions faster, and provide integration infrastructure for hybrid data ecosystems.

Philip Russom, Ph.D.


Embedded BI: Why It Works and How to Do It

Both product and tech leaders have always recognized that business intelligence (BI) is most valuable when it is pervasive, contextual, and actionable. A new generation of solutions -- embedded BI – provides unprecedented power to weave reporting and analytics into the fabric of apps and business processes.

David Stodder


Ask the Expert About Data Science
TDWI Members Only

The data and analytics landscape is changing. Although many organizations are still analyzing structured data from their data warehouse, TDWI research indicates organizations have increasing interest in analyzing disparate kinds of data. This data is often large in volume and can require modernizing data infrastructures and platforms. The industry around big data and data science and the emerging role of the data scientist is one result of this evolution/revolution.

Fern Halper, Ph.D.


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