Finding Bad Data in Big Data

Find Bad Data in Data Warehouses, Hadoop and NoSQL stores

Technical Challenge

How do you root out all of the Bad Data that is in your Big Data enterprise data warehouse?

Many companies are using Business Intelligence (BI) to make strategic decisions in the hope of gaining a competitive advantage in a tough business landscape. But Bad Data will cause them to make decisions that will cost their firms millions of dollars.

Most firms test far less than 10% of their data by sampling the data. Therefore, at least 90% of data remains untested. Since bad data exists in all databases, why wouldn’t firms want to test 100% of their data and guarantee that this critical information is accurate? It is time for organizations to take a hard look at the data that their management team is relying on to make strategic decisions.

The QuerySurge Solution

QuerySurge is only testing solution designed specifically for automating the testing Big Data & Data Warehouses.

With QuerySurge, you can:

  • Test across different platforms, including Data Warehouses, Hadoop, NoSQL data stores, databases, flat files, XML and Excel
  • Create Tests easily with no SQL programming, ensuring minimal time & effort to create tests
  • Automate the entire testing cycle, including the kickoff, the tests, the data comparison & auto-emailed results
  • Verify more data & do it quickly, validating up to 100% of all data up to 1,000 x faster
  • Integrate your QuerySurge DevOps efforts with most Build, ETL & Test Management solutions for Continuous Delivery
  • Provide detailed reports, auto-emailed results & data health dashboards to keep your team informed

QuerySurge will eliminate bad data and save your company millions. Don't let Business Intelligence be an oxymoron in your company. Solve the bad data problem with QuerySurge.

But don’t believe us (or our clients). Try it for yourself – it’s free!

Whitepaper

The Data Quality Conundrum

RTTS recently commissioned a study of over 200 companies interested in improving the level of data quality within their Data Warehouse and Business Intelligence projects - See what we found.