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Practical Data Science


Money-Making Analytics (Part 4): Why Collaboration is the Critical Success Factor

How to drive collaboration and training on your money-making analytics project. Now that you’ve finalized strategy, selected technology, and designed your analytics to be action oriented and simple, this final step will help you set the right cadence and collaboration across the organization.

Money-Making Analytics (Part 3): Choosing an Action-Oriented Decision-Making Framework

How can you ensure that your analytics will drive users to make decisions? Now that you’ve finalized your strategy and selected the right technology, your third step will help you create analytics that enable taking action.

Infographic: Operationalizing and Embedding Analytics for Action

Where are enterprises embedding analytics into devices? Who's using these analytics and what types of data are being examined? These and other key questions are answered in TDWI's latest infographic.

How to Improve Big Data ROI

ROI may look to be a high bar for specific data projects, but a holistic approach to data can provide ample opportunities to recoup big data technology investments.

Data Hunting: Mastering the Big Data Challenge

The data is out there. It’s time to use it effectively to bring your big data strategy to life.

Money-Making Analytics (Part 2): Evaluating the Technology and Tools

Now that you have finalized your analytics strategy and key stakeholders, you must choose the best technical solution for your company. Learn how to establish the right technical elements to enable the existing company culture, and not fight it.

Money-Making Analytics (Part 1): Soul Searching and Analytics Strategy Selection

The first step is most important and focused on understanding your company culture, the people you need to involve in an analytics project, and the questions you need to ask provides a framework for conceptualizing and prioritizing your analytics and your project road map.

Embedding and Operationalizing Analytics for Action: Three Important Takeaways

Close to 50 percent of TDWI survey respondents said they embedded models or algorithms into business processes in some way. What can we learn from these respondents?

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