Upside


Data Digest: Open Source Intelligence, Cloud Computing Dangers

The best ways to make open source data easier to find, why open source code is better than proprietary code, and mitigating risks when migrating to cloud computing.

Why the Customer Journey Matters More Than Ever

The customer journey really is coming back, argues industry luminary Jill Dyché, chiefly because competition for customers in the digital marketplace is insanely competitive.

12 Real-World Solutions for IoT Analytics

Our interviews with a dozen vendors that have a strategic focus on the Internet of Things and the analytics products to support it reveal that IoT analytics is more than a passing fad or the latest buzzword

Advanced Analytics: Believe the Hype

By 2018, Gartner projects that advanced analytics will underpin the competitive efforts of more than half of all large organizations.

Data Warehouse Modernization: Developing the Implementation Road Map

Drastic transitions in your environment can't happen overnight. To ensure success, develop a phased approach to migrate to your new environment.

Data Digest: Data Quality Teamwork, Modern Data Integration, Data Deduplication Best Practices

What high-quality data means and how to achieve it by working as a team, tips on de-duping multiple areas of the enterprise, from cloud servers to data, and a new paradigm for data integration.

Drill-Down, Interactivity Come to PowerBI on iOS, Windows Mobile

Users of Microsoft Corp.'s PowerBI visual discovery software can breathe a deep sigh of relief. At long last, they'll be able to view reports on their mobile devices.

AlphaGo, Artificial Intelligence, and a Machine-Learning Renaissance

A recent AlphaGo victory is being touted as a Big Win for artificial intelligence (AI). It's a no less important win for machine learning, which might be in the midst of a renaissance.

The Best Job in America: Data Scientist

Glassdoor recently released their review of the 25 best jobs for 2016. At the top of the list is the vaunted data scientist. What does it take to be a successful data scientist?