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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 Best Practices Awards based on feedback from prior years. The new Data Management category focuses on management of information resources; the 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 – As organizations strive to become more competitive and meet new business objectives, they are often re-architecting their data management practices to include emergent technologies such as cloud data platforms, semantic layers, 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 better insights as well as the development of data products. 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.
  • Analytics – As emphasis on driving business decisions through data-driven insight increases, the analytics 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 self-service analytics. 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. Modern data analysts are emerging who can use tools such as automated ML to help them build models. Data literacy has become a key focus for information workers as self-service programs expand, and businesses move to data-as-a-product paradigms.

    This best practices award category focuses on the strategy, implementation, and operationalization of new analytics solutions to solve business problems. TDWI is particularly interested in hearing from organizations that have had success with self-service analytics for business users as well as those that are utilizing more advanced analytics, such as machine learning, and putting models into production. We are interested in how organizations are making use of large volumes of diverse data for business advantage; emerging analytics deployments, including new data products; or emerging analytics technologies such as generative AI. Surprise us with your impactful innovations!