TDWI Articles

Staffing, Roles, and Careers


Microsoft's Power BI Is Surprisingly Excel-Friendly

Since it introduced Power BI publisher for Excel, Microsoft has been working to enhance it with new features and to fix bugs highlighted by users.

Data Digest: Shadow IT and Biased Algorithms

Today learn why users turn to shadow IT solutions and why trusting blindly in data analytics may perpetuate biases.

We've Already Failed at Big Data -- Now What?

If your team has been taking "too long" to finish its big data project, here are five steps to take now to regain trust and respect and show the business benefits of your work.

Analysts Don't See Great Value in New Data Types

According to new survey, data from research firm Clutch, most users of BI data analytics tools find traditional data types more valuable than new data sources. Is this really a surprise?

Self-Service Data Access: The Foundation for Emerging Analytics

New practices such as self-service data prep, exploration, and discovery don't work well (or at all) without new ways of making data more accessible.

Profile: So You Want to Be a (Data Science) Rock Star

Data scientist Nathan Hamilton explains that a strong grasp of statistics and a creative, problem-solving imagination have made him a successful data scientist.

Protecting Personal Information: Differential Privacy and Data Science

In many cases, it's still possible to extract personal info from anonymized data. Thanks to changing regulations, differential privacy and other new techniques for obscuring sensitive data are going to start getting a lot more attention.

You Found a Data Scientist -- Now What? The Case for Building a Center of Excellence

Hiring a data scientist doesn't mean your work is done. Building a center of excellence and ensuring good relations with IT are both valuable steps toward a successful analytics program.

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