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This is part two in our five part series on the essential capabilities of the competitive data-driven enterprise.

For decades, data integration and modeling have been done in either of two likely places: The enterprise ETL or Data Warehouse environment (IT Developers) or Excel (Analysts). Currently the status quo is being challenged in some of the following ways that highlight the importance of empowering domain and subject matter experts to wrangle and model their own data. Read more

If your organization is seeking to better manage its information as a corporate asset that is to be valued and capitalized, you’re likely focused on implementing programs that will catalyze measurable business results from mountains of business information that may be the product of the last decade or more of digital transformation initiatives. Read more

According to ‘The Economist’, data is the new oil. It is now the world’s most valuable resource. The volume of data available to organizations to capture, store, and analyze has changed the ways in which organizations address innovation, and analytics is a true competitive differentiator.

Unfortunately, business analysts, data scientists, and other line of business users performing self-service analytics are spending a majority of their time preparing data for analysis rather than actually garnering and sharing the insights to be found in it (1), even with the help of self-service data prep tools like Alteryx, Trifacta, and Tableau’s Maestro (coming soon). Read more