Press-release: EasyMorph Announces Record Business Expansion and Adds 100th Customer

TORONTO, April 19, 2018 — EasyMorph Inc., a provider of self-service data preparation software for non-technical business users, announced record growth in its first quarter ending March 31, 2018. The company has achieved its highest revenue since its inception in 2015 and added its one-hundredth customer, a 300% increase in its customer base within the past year.

EasyMorph launched in 2015 with a vision to empower non-technical business users to easily merge, filter and manipulate data from multiple platforms and data sources without having to code or do complex programming. To date, there are over 15,000 downloads of the software with users in 20 different countries.

"We have added our one-hundredth customer in record time and I see it as a confirmation of EasyMorph's vision," said Dmitry Gudkov, Founder of EasyMorph Inc. "Reducing dependency on enterprise IT departments lets our business users solve data-related problems autonomously without delays and bureaucratic hassle."

EasyMorph's agile data preparation self-service solution helps non-technical business users to:

• Extract and aggregate data from multiple platforms and data sources.
• Slice and dice data, group information, calculate new metrics and more without having to code or do complex programming.
• Automate routine file processing. 
• Minimize their reliance on IT departments.

EasyMorph's powerful data preparation and automation capabilities can be used with any business intelligence or data visualization tool including Tableau dashboards, Qlik apps and Excel spreadsheets.

Interested parties can click here to download a free version of EasyMorph.

About EasyMorph

EasyMorph, Inc. provides self-service, agile data preparation at your fingertips. Business users can easily access, combine, prep, and manipulate data from multiple platforms and data sources with no coding required. EasyMorph is optimized for non-technical users to independently conquer and automate tedious data-related tasks quickly and efficiently.