How do you make self-service data analysis work for your organization?

Stephanie McReynolds
Stephanie McReynolds VP, Marketing

We are entering an era of self-service analytics. There has been an explosion of data, from social and mobile data to big data, that is fueling new ways to understand and improve customer experience. What has emerged is a whole new set of market imperatives that are changing the way data users tackle data discovery, leading to an increase in self-service analytics, fueling insights and driving innovation.

In this new world, aspects of the analysis process that were once tightly controlled are now more fluid, allowing more people to analyze data but also creating a lot of questions: Can this data be trusted? Has this analysis already been done? Is this data in a form I can use? Where is the data I need? More than 50 percent of data consumers wait months for the services that will answer these types of questions. That’s just too slow for the pace of business.

According to recent Forrester research, insights-driven firms are 69 percent more likely to report year-over-year revenue growth of 15 percent or more. In order for organizations to be more insights-driven, the right data must be accessible to line-of-business workers and executive decision makers.

This new paradigm comes with new rules: Self-service is critical for an insight-driven organization, and in this more fluid data environment, understanding the lineage and context of that data is key to data exploration. But, there is too much data for manual profiling and documentation, requiring new tools with machine learning and new processes to turn data exploration into a reality for enterprises.

On August 25 at 11am PDT, Forrester’s VP and Research Director, Gene Leganza, Alation’s Head of Product, Aaron Kalb, and Trifacta’s Director of Product Marketing, Will Davis, will hold a webinar to discuss “Achieving Productivity with Self-Service Data Preparation.” In the webinar, Leganza will discuss the new imperatives that are defining data exploration, while Kalb will discuss how a data catalog promotes re-use, standardization and answers some of the toughest questions that arise in self-service environments. Davis will discuss how data wrangling makes the self-service analytics process more productive. Register for the webinar to learn how to increase analyst productivity with data prep that’s scaled through data cataloging.

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