TDWI Checklist Reports
TDWI Checklist Reports provide an overview of success factors for a specific project in business intelligence, data warehousing, or a related data management discipline. Companies may use this overview to get organized before beginning a project or to identify goals and areas of improvement for current projects.
November 14, 2017
This Checklist Report examines how seven industries are using analytics to drive value. These industries include finance, insurance, retail, healthcare,manufacturing, utilities, and technology/software/Internet.
November 10, 2017
When we design and develop data management solutions, one of the first and most important steps is to catalog the data that will be captured, managed, analyzed, and shared. This TDWI report will examine the many components and functions of a modern enterprise data cataloging facility.
November 1, 2017
Open source has become popular, especially for big data and data science, because it is a low-cost source community for innovation, which appeals to many data scientists and analytics application developers— especially those who like to code.This TDWI Checklist Report discusses some best practices for evaluating open source analytics.
September 29, 2017
It is a competitive advantage to know more about your customers and to apply this knowledge to marketing, sales, support, and the development of products and services. By gathering together the assortment of big data available to them and applying advanced analytics and data science techniques, organizations can gain a detailed, contextual understanding of customers’ paths to purchase, what types of marketing strategies are most effective, and how customers influence -- and are influenced by -- other customers.
September 26, 2017
The consistent demand for data quality software and new cloud implementation options indicates that more organizations are considering whether to use the cloud to introduce new data quality software, increase their data quality tool users, save on infrastructure costs, minimize the time to rollout of the tools, and build trust in their enterprise’s information assets—the ultimate goal of data quality efforts.
September 12, 2017
For years, TDWI has seen an increasing number of organizations make strategic commitments to the cloud as a preferred computing platform. These commitments involve a wide range of use cases, from operations to analytics to compliance. However, the best practices of data management don’t disappear just because data and workloads shift to the cloud.
August 2, 2017
Data integration and data quality are technical disciplines, but there’s more required than technology. DI/DQ must also coordinate with and align to business processes and goals. The assumption is that businesspeople should be involved in defining quality metrics, standards, and process rules. This report will drill down into the modern best practices associated with emerging data sources, data platforms, and business use cases.
July 27, 2017
All organizations, no matter how big their budget, must overcome barriers in order to realize value from data faster. Those that have historically experienced centralized, IT-centric BI implementations must transition to flexible environments that embrace the increased use of self-service technologies.
June 29, 2017
Augmenting the conventional EDW design with Hadoop and Hive can help optimize your EDW by expanding usability, improving performance, improving results, and reducing overall costs.