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TDWI Upside - Where Data Means Business

Big Data


Cazena: Managed Big-Data-as-a-Service Made Easy

If you don't know where to start with big-data-as-a-service, upstart player Cazena says it has just the thing for you. Cazena markets managed data mart and data lake services -- with a twist.

Data Digest: Data Science Languages, Understand Big Data Growth, Executive Big Data Survey

What are the most popular programming languages for data science, how can big data be both growing and not growing, and what executives think about current big data initiatives.

Q&A: Transform Company Culture by Transforming How Workers Approach Data

Creating a data-driven company involves changing how data is viewed and used, both by top management and by curious, trained office workers. Frank Bien, CEO of Looker, explains how leading firms have transformed company culture by helping employees use data more effectively.

IBM Doubles Down on AI

Despite the attraction of consumer-facing AI, IBM's focus on practical business applications may yet win the race for widespread AI adoption.

How a Small Insurance Firm Uses Big Data to Level the Playing Field

Large insurance companies are very good at aggregating data to analyze risk, but not so good at using big data to improve the front-end customer experience. That presents an opportunity for smaller firms, explains a digital marketing expert at insurance start-up Insureon.

Power BI Gets an Analytics Infusion

Microsoft's Power BI cloud platform got an analytics refresh to close out the year. In addition, Power BI now supports DirectQuery for both Spark and Azure Analysis Services.

The Year Ahead: 2017 Predictions for Analytics

Adoption of analytics across the enterprise is occurring at breakneck speed, and there is no sign of slowing down. In 2017, we'll witness a critical point as organizations seek analytics that extract greater value from all available data.

It's the End of the Data Warehouse as We Know It

According to TDWI survey data, about half of all enterprises expect to replace their data warehouse systems -- in some cases, their analytics tools, too -- over the next three years. What should they replace them with?

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