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TDWI's Best Practices Award Categories

  • Advanced Analytics and Data Science – Reporting and dashboards are the most common form of analytics today, and will continue to be so. However, TDWI wants to hear from organizations that have gone beyond reporting into advanced forms of analytics, namely those based on data mining, statistical analysis, predictive and prescriptive techniques, artificial intelligence, Natural Language processing techniques, and more. Analytic applications based on these commonly support fraud detection, risk quantification, customer targeting, cross-sell recommendations, predicting part failures, and more. These analytic applications often require “big data”—that is, multi-terabyte data volumes.
  • Emerging Technologies and Methods – Emerging Technologies and Methods – This category is a catch-all for the many new techniques that are gaining acceptance in BI, DW, and DM, including cloud computing, Hadoop, Spark, data virtualization, open source software, Web 2.0, social media, mobile BI, self-service BI and data preparation, stream mining, IoT, cognitive computing, and more. This category also includes real-time and right-time data (streams), technologies (event processing), and business practices (operational business intelligence). TDWI wants to hear from early adaptors who’ve succeeded with these new technologies and methods, as well as how these complement or extend existing solutions for BI, DW, and DM. Also of interest are innovative best practices, such as agile and lean development methods.
  • Enterprise Data Warehouses – Data warehouses are more relevant than ever to the organizations that depend on them to provision complete, clean, and consistent data for reporting, dashboards, analytics, operational BI, and so on. The continued relevance of the data warehouse is due largely to users’ evolution of designs and architectures, coupled with many new data warehouse platform options from the vendor and open-source communities. These innovations are critical to keeping up with big data, emerging analytics, new sources and data types, economic pressures, agility, and modern data-driven business programs. This award category is a sounding board for successful users’ data warehouse innovations for real-time functions, virtualization and the logical data warehouse, the integration of Hadoop and other open source, architectures for hybrid multi-platform data warehouse environments (DWEs), and other approaches that extend and modernize the data warehouse.
  • Data Management Strategies – The data that goes into solutions for BI, DW, and analytics are only as good as the data management solutions that collect, aggregate, improve, and audit the data. The same is true of many operational and transactional applications. Whether for BI/DW or operational systems, an end-to-end data management strategy involves a long list of disciplines, including data integration, quality, profiling, exploration and discovery, master data management, event processing, replication and data sync, and more. TDWI is interested in uses of these and other DM disciplines that push the envelope with real-time, system interoperability, large data volumes, and non-relational data. Equally of interest are organizations that coordinate data standards, governance, and team productivity across multiple DM disciplines.
  • Big Data – One of the most influential trends in BI, DW, DM, and analytics is to apply these disciplines to so-called “big data.” TDWI is eager to hear from organizations that are working with various types of big data, especially data from web applications, social media, machines, sensors, streams, devices, grids, surveillance equipment, geospatial systems, and the Internet of Things (IoT). Also of interest are the new platforms that capture, manage, and process big data, such as the Hadoop family of products, MapReduce, Spark, Storm, NoSQL databases, and various open-source products. Some types of big data stream in real time, so TDWI is equally interested in users that manage streaming big data with technologies for event processing, messaging, and operational intelligence.
  • Business Intelligence, Visual Analytics, and Data Discovery – This category is focused on tools and platforms that business users employ to access, analyze, visualize, and share data insights. The goal is to use software to improve data use and enable data-informed decision making. In recent years, user excitement has grown as tools and platforms have been evolving to provide greater ease of use and self-service capabilities. Before, users of business intelligence (BI) tools were primarily well-trained business and data analysts, IT developers, and power users. Now, as BI has become more “democratized,” nontechnical users across organizations are able to work with visual analytics and data discovery tools for a variety of use cases and objectives.

    A vital technology driving this evolution is data visualization. Using this technology, tools can support a growing variety of ways to see and interact with data and communicate data insights, including through dashboards, heat maps, geographical representations, and more as visualization libraries expand. Growing out of data visualization is the concept of “data storytelling”; this is a set of practices for connecting multiple visuals with narrative for interpreting data findings, discussing why they are valid and significant, and inviting conversation about them. Users of all types can employ data storytelling to communicate analytic conclusions and show how they were reached.

    This TDWI Best Practices Awards category is focused on excellence in the use of BI, visual analytics, and data discovery tools, platforms, and cloud- or software as a service (SaaS) products. Judges will be evaluating how well users in organizations have employed these technologies and practices to achieve objectives, including by applying visualization and data storytelling to communicate analytic insights. Contestants are invited to provide examples of (or links to) data visualizations with their entries.

  • BI and Analytics on a Limited Budget – All types of organizations face constraints in developing and deploying business intelligence (BI), analytics, and data warehousing systems. Budget constraints are often the toughest because they limit the technology and people resources that can be devoted to solving challenges and meeting goals. Small and midsize businesses (SMBs) and government and non-profit organizations are always hampered by budget constraints, but they are not the only ones: many lines of business (LOBs), divisions, and departments of larger organizations must also pursue their BI and analytics goals without fully adequate funding, IT support, or budgets of their own to bring in talent and the latest technologies. They must stretch resources and foster productive, collaborative teams that can do more with less.

    This TDWI Best Practices Awards category focuses on innovation and excellence in achieving BI and analytics goals despite serious budget limitations. Judges will be evaluating how project sponsors and managers have been able to deliver real and sustained value to their organizations within considerable budget constraints. Fortunately, trends are moving in positive direction for SMBs and other organizations with limited budgets. Cloud and platform- or software-as-a-service options are allowing many things to be possible that would have previously required major, on-premises IT infrastructure. Self-service BI, analytics, and data management platforms are enabling users to do more with little or no IT support and guidance. Judges will look at how awards entrants are making use of new options as well as getting full value out of existing technologies. They will also look at implementation of innovative ways of collaborating to achieve objectives, such as the use of agile methods, to improve quality and effectiveness so that resources are not wasted.