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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 | The Cloud Data Integration Primer

June 29, 2018

A number of newly mature trends are making cloud-based data integration platforms, technologies, and user best practices more relevant than ever.


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TDWI Checklist | Five Data Management and Analytics Best Practices for Becoming Data-Driven

June 12, 2018

It can be difficult to create an organization that thrives on data and analytics. This TDWI Checklist Report discusses best practices to build a program and an infrastructure for becoming data-driven.


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TDWI Checklist | Strategies for Improving Big Data Quality for BI and Analytics

May 18, 2018

Organizations dependent on big data for a wide range of business decisions need data quality management that can improve the data so it is fit for each desired purpose. This TDWI Checklist Report offers six strategies for improving big data quality.


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TDWI Checklist Report | The Automation and Optimization of Advanced Analytics Based on Machine Learning

May 8, 2018

Machine learning is being used today to solve well-bounded tasks such as classification and clustering. Note that a machine learning algorithm learns from so-called training data during development; it also learns continuously from real-world data during deployment so the algorithm can improve its model with experience. This report will drill into the data, tool, and platform requirements for machine learning with a focus on automating and optimizing ML's development environment, production systems, voracious appetite for data, and actionable output.


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TDWI Checklist Report | Modernizing Data Warehouse Infrastructure

March 30, 2018

Users ignore the modernization of deep warehouse infrastructure at their peril. Without it, they may achieve complete, clean, and beautifully modeled data, but without the ability to scale to big data, iterate data models on the fly, enable flexible self-service access, operate continuously and in real-time (as warehouses must in global businesses), and handle new data types and workflows for advanced analytics.


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TDWI Checklist Report | Data Architecture for IoT Communications and Analytics

March 30, 2018

The foundation of a successful IoT implementation is a technical architecture that blends network connectivity with an information architecture for streaming, ingesting, filtering, and capturing data. This checklist explores some fundamental aspects of the data architecture necessary for IoT success.


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TDWI Checklist Report | Seven Best Practices for Machine Learning on a Data Lake

March 30, 2018

As organizations collect and analyze increasing amounts of data, they are turning to the data lake as the platform to perform more advanced analytics such as machine learning. This TDWI Checklist Report presents best practices for advanced analytics on a data lake.


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TDWI Checklist Report | Six Strategies for Balancing Compliance with Data Value

March 6, 2018

Businesses can only seize new data-driven opportunities if they recognize sensitive data and handle it responsibly. This report focuses on how targeted improvements to specific data management best practices and technology can contribute significantly to your success with GDPR compliance, as well as data governance and data-driven programs in general.


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TDWI Checklist Report | Data Management for Data Lakes in the Cloud

February 21, 2018

A lake or cloud can breathe new life into established enterprise data architectures (data warehouses, marketing channel data, digital supply chains) or create new and different ones (analytics labs and sandboxes, ecosystems of cloud-based operational applications). This report discusses the leading data management (DM) best practices you need for data lakes to be successful when deployed in the cloud.


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