Juice Analytics

JULY 6, 2018

Putting data on a screen is easy. Making it meaningful is so much harder. Gathering a collection of visualizations and calling it a data story is easy (and inaccurate). Making data-driven narrative that influences people.hard. Here are 25 more lessons we've learned (the hard way) about what's easy and what's hard when it comes to telling data stories: Easy: Picking a good visualization to answer a data question Hard: Discovering the core message of your data story that will move your audience to

Slice and Dice 90

Slice and Dice Predictive Modeling Visualization Data-driven 90

IBM Big Data Hub

JULY 5, 2018

Natural disasters seem inescapable, leaving us feeling vulnerable in the hands of nature. How is this possible, given all the data and technology that surrounds us today? Can’t experts get better at prediction, and even try to stave off more natural calamities or more effectively reduce the loss of resources?

Analytics 45

Analytics Technology 45

CIO Business Intelligence

JULY 2, 2018

Swimming in data Image by Getty Images There is golden knowledge in the sea of data that businesses are swimming in. Being able to fish out the business intelligence you need—when you need it—is the key to steering your ship.

Visualization 45

Visualization Business Intelligence IT 45

Paul Turley

JULY 6, 2018

Please join Power BI authors and community leaders for an afternoon and evening of deep learning. Featured presenters include “Guy In A Cube” Adam Saxton and international author and Excel MVP, Matt Allington.

Deep Learning 40

Deep Learning 40

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DataRobot Blog

JUNE 30, 2018

by Jen Underwood. Both data-driven organizations and analytics software vendors today face a wide spectrum of complex challenges navigating an entirely new world of cloud app data sources. From security to agility, scale, Read More.

Strategy 40

Strategy Data-driven Software Analytics 40

IBM Big Data Hub

JULY 2, 2018

So what happens now when we go beyond the frontiers of the data warehouse and into the world of the data lake? – the world of Hadoop, of NoSQL, the world of schema on read, of discovering the data as is? For many organizations, the holy grail is to reap the benefits of the data lake while retaining a degree of control and governance. While it is desirable to have the broadest possible range of diverse data, the data on which the business runs must have the appropriate levels of provenance and li

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Data Lake Data Warehouse IT 45