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TDWI Upside - Where Data Means Business

Big Data


Data Quality in the Age of Big Data

Traditional data quality best practices and tool functions still apply to big data, but success depends on making the right adjustments and optimizations.

CEO Q&A: Data Quality Problems Will Still Haunt Your Analytics Future

Data quality issues become even more important as machine learning use grows. DataOps and data wrangling help enterprises address this vital problem.

The Machine Learning Data Dilemma

Machine learning applications are dependent on, and sensitive to, the data they train on. These best practices will help you ensure that training data is of high quality.

Most Companies Are Not Ready for Ethical Intelligence

Adding property rights to inherent human data could provide a significant opportunity and differentiator for companies seeking to get ahead of the data ethics crisis and adopt good business ethics around consumer data.

Considerations on the Path to Cloud Acceptance

Thinking about three key aspects of the cloud can accelerate your adoption of the technology.

Nordisk Movie Studio Drives Data with a Small Team and a Big Vision

Modernizing their data warehouse presented a host of problems for a Denmark media company.

Data Digest: Applying Machine Learning, Food Retail Data, Animals and AI

How to start using machine learning for your enterprise, how food retailers are using big data, and how behavior studies can affect AI research.

Data Lake Platform Modernization: 4 New Directions

Early adopters of the data lake have arrived at a maturation stage where they need to modernize their platforms before expanding their implementations.

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