With a massive increase in the consumption of desktop-based self-service analytics tools over the past two to three years, traditional data management and governance practices have largely been overlooked. But analysis is only as good as the data; unsurprisingly, establishing trust in data has become the biggest problem for customers and vendors of self-service analytics today. We frequently find that organizations that develop pockets of desktop analytics tools (without a server component) spend an indiscriminate amount of time in blending, validating, and verifying the data behind reports. Organizations often find themselves forced to switch back to Microsoft Excel for data manipulation. Datawatch, through its product, Monarch, helps bring a self-service angle to data preparation and wrangling.

“Compared to many vendors that are barely past their start-up roots in the self-service analytics world, Datawatch is a 20 year old data management veteran. The vendor has successfully catered to complex data management challenges at very large clients and its software has been battle-tested in regulated verticals such as financial services and healthcare.” – OVUM

Key messages

  • Provides a full range of integration methods and connectors, differentiating on file systems connections and scraping capabilities.
  • Suitable for complex data blending jobs involving multiple, disparate sources.
  • Graphical and easy-to-use interface, even for a new user.
  • Strong data security and governance capabilities.

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