TDWI Upside - Where Data Means Business

Data and Business Leadership

Why Data Science Must (And Will) Be Automated

Data science today is extremely labor-intensive. The automated or quasi-automated features widely used in self-service BI aren't commonplace in data science, but Gartner says that's about to change.

Data Scientist Skills for Success

With the increasing demand for data science professionals, what skills are necessary to succeed in our new digital world?

When Businesses Go Around IT for Analytics

Business people have been going around IT organizations for about as long as they've been dealing with them. In a recent report, Gartner tackles the emerging problem of going around IT for analytics.

Repeatability: The Key to Scaling Data Science

When it comes to embedding analytics insights into your business, technology is the easy part. Figuring out what to do and how to do it is much harder.

Time to Federate Enterprise Resource Planning

Future businesses will be defined by new efficiencies, strategies, and business models created with data-driven knowledge. If companies wish to maintain traditional on-premises ERP solutions, they will face costs and compromises.

Why Your Top Analysts Are About to Quit -- And How to Keep Them

Four steps you can take to retain top talent by ensuring your analysts stay productive and engaged in their work.

What's Next for Your Customers?

Marketing is evolving from communication to the masses to communication to the one. By using a recommendation engine, you can determine the next best step for each customer journey and use that to increase customer loyalty and revenue.

Three Paths to Value in Data Science

Organizations are using many strategies to gain bottom-line value from big data and data science. Three major trends stood out in TDWI's recent research.

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