RESEARCH & RESOURCES

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.


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TDWI Checklist Report | Seven Industries Using Analytics for Business Value

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.


TDWI Checklist Report | The Data Catalog's Role in the Digital Enterprise: Enabling New Data-Driven Business and Technology Best Practices

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.


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TDWI Checklist Report | Open Source for Analytics: Trends, Opportunities, and Challenges

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.


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TDWI Checklist Report | Best Practices for Maximizing the Potential of Mobile BI and Analytics

September 29, 2017

Mobile computing offers an unusual opportunity for organizations to innovate with new ways of improving employee productivity, partner and customer relationships, sales and service, and business transactions.


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TDWI Checklist Report | Six Strategies for Moving Enterprise Analytics to the Cloud

September 29, 2017

In the era of analytics, more businesses are taking advantage of ever-increasing amounts of data to become more competitive. The challenge is real and increasingly, business leaders are utilizing cloud services (including compute, storage, and analytics to scale) to support their needs.


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TDWI Checklist Report | Six Strategies for Advancing Customer Knowledge with Big Data 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.


TDWI Checklist Report | Cloud Data Quality Tool Considerations

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.


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TDWI Checklist Report | Data Management Best Practices for Cloud and Hybrid Architectures

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.


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TDWI Checklist Report | Modern Data Integration and Data Quality Practices for Digital Business Requirements

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.


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