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Data Summit 2018

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White Paper

Data Preparation: Don't Try to Be Data-Driven Without It
Data Preparation: Don't Try to Be Data-Driven Without It

Become a more data driven organization without the high cost of data science driven analytics platform.

E-book

IDC InfoBrief: Making Open Source RDBMS Work for the Enterprise
IDC InfoBrief: Making Open Source RDBMS Work for the Enterprise

IDC's research discovered that open source RDBMS spending has nearly tripled since 2014. This info brief shows why DBAs are embracing open source for enterprise databases.

White Paper

Ease the data preparation challenge ― learn new techniques today.
Ease the data preparation challenge ― learn new techniques today.

Learn easy techniques to break down the barriers to big data success. Download this white paper to see how you can make accurate data readily accessible for faster, better decision making.

Technical Brief

Use Self-service Analytics to Build Strong Data Teams Across your Business
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This tech brief explains the difference between a full-service analytics model and a self-service analytics model, making the case for self-service.

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The Four Roadblocks of Data Preparation
The Four Roadblocks of Data Preparation

Ever wish you could automate data preparation, so you could focus more on data analysis? In this complimentary e-book, you’ll learn how to make those frustrating, manual tasks a distant memory.

On Demand Webcast

What’s new in Toad Data Point in 2017
What’s new in Toad Data Point in 2017

During this webcast, we will highlight the new product features added in 2017 to help you better solve ongoing challenges in data access, preparation and reporting. You will learn about our new pivot grid and dimensional viewer, which help you make the m

E-book

Replacing Brio: A Playbook for Data Analysts
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Find out how you can safely move from Brio to an up-to-date self-service data preparation solution

On Demand Webcast

Eliminate data prep roadblocks
Eliminate data prep roadblocks

Ventana Research reports that companies using predictive analytics spend 40 percent of their time preparing data for analysis and 22 percent accessing the data — the least gratifying parts of the analytic process.

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