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TDWI Best Practices Awards: Recognition for Innovative Data and Analytics Implementations

TDWI's Best Practices Award Categories

We have simplified the category structure for our 2021 Best Practices Awards based on feedback from prior years. The new Data Management category focuses on management of information resources; the BI and Analytics category focuses on the use of information resources.

Descriptions of these categories appear below, along with topics of particular interest to the TDWI judges.

  • Data Management – TDWI research shows a growing number of businesses now recognize that information can be both an asset and a liability. The data warehouse is enjoying a resurgence in emphasis as organizations commit to driving business results through data, and the data lake has emerged as a crucial expansion that facilitates new data resources and processes that extend beyond traditional consumption paradigms. Large numbers of business are re-architecting their data management practices, driven in equal parts by new business objectives; emergent technologies such as cloud data management platforms, virtualization, and real-time data integration; new consumption paradigms including data science and self-service; and the adoption of formal data quality and governance goals.

    This best practices award category focuses on the strategy, architecture, processes, and implementation of solutions that manage data resources and make them available for the development of information products or consumption by analysts. TDWI is particularly interested in hearing from organizations that are building unified data warehouse and data lake environments; transitioning into a combination of full- and self-service programs leveraging emergent technologies; implementing modern data pipelines that go beyond the batch ETL processes of the past to include multidirectional flows and real-time processing; leveraging new technologies including cloud platforms, virtualization, metadata repositories, and automated deployment and monitoring tools; and incorporating nonrelational data resources.
  • BI and Analytics – As emphasis on driving business decisions through data-driven insight increases, the business intelligence and data science programs that drive these decisions are rapidly transforming and their audiences within the business are growing. Access to data within the business is fast becoming an expectation of any line-of-business worker through prebuilt consumables such as dashboards and reports as well as resources for self-service analytics users. Data science teams are developing formal processes as they expand their scope to address more of the enterprise, and their insights are powered by ever-evolving ML and AI technologies and automated ML. Data literacy has become a key focus for information workers as self-service programs expand, dashboards incorporate production analytics, and business applications incorporate data-based decision processing.

This best practices award category focuses on the strategy, architecture, processes, and implementation of solutions that consume data resources to generate insights for business consumption, both through central programs such as BI and analytics teams and through distributed or semi-autonomous members of the larger business community. TDWI is particularly interested in hearing from organizations that are leveraging new solutions that allow business users to find, analyze, and share data on their own; next-generation dashboards that incorporate traditional key performance indicators alongside behavioral and predictive outputs from data science; the operationalization and management of advanced analytics including models that leverage AI and autoML; efforts in organizations to expand overall data literacy and the explainability of data science products; programs that seek to avoid bias in analytic models; the valuation of analytics as measured in improvement of business key performance indicators; and case studies that highlight how BI and analytics have demonstrated tangible, measurable impact on business KPIs.