What is SSDP and Can it Truly Make Analytics Self-Serve?

Sep 6, 2019

SSDP (otherwise known as self-serve data preparation) is the logical evolution of business intelligence analytical tools. With self-serve tools, data discovery and analytics tools are accessible to team members and business users across the enterprise. What is SSDP? SSDP or Self-Serve … Continued

Augmented Data Preparation and Self-Service ETL!

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Sep 4, 2019

What is Self Service Data Preparation? Data prep can slow down analytics and cause delays. Self-service data preparation (when done right) can enable business users to leverage sophisticated, easy-to-use tools for self-serve ETL. Data extraction, transformation and loading (otherwise known … Continued

Augmented Analytics for Every Business and Industry!

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Aug 7, 2018

Is An Augmented Analytics Solution Right for My Organization? Self-Serve Data Preparation is a critical component of augmented analytics. If these terms seem foreign to you, just know that they represent the future of business analysis. As organizations adopt self-serve … Continued

Self-Serve Data Preparation for YOUR Users

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Jun 19, 2018

Self-Serve Data Prep Should be Just That – Self-Serve! Self-serve has many meanings. You can pump your own gas, you can serve yourself at a buffet, and sometimes you can even do your own data preparation. You will notice that … Continued

Why Do You Need Self-Serve Data Preparation?

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Mar 7, 2018

Self-Serve Data Preparation Takes the Headache Out of Data Analytics! Self-Serve Data Preparation (aka augmented data preparation) is all about efficiency and the presentation of sophisticated data preparation tools in an easy-to-use environment. The idea behind self-service data preparation is … Continued

White Paper: Self-Serve Data Preparation Provides Significant Benefit to the Enterprise

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Aug 2, 2017

By providing sophisticated analytical features and algorithms in an easy-to-use self-serve environment, the enterprise enables business users to perform data preparation and test theories and hypotheses and prototype on their own. Rather than preparing data at the central meta-data layer, … Continued

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