Data Validation Assessment

Evaluation of your approach to validating your critical data, along with expert recommendations for improvement & an implementation plan

Your Challenge

Your organization’s data architecture is expanding and changing.  As more data feeds are being added to your systems, your data volume is growing at a geometric pace and now includes new and additional components such as:

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  • Data warehouses
  • Hadoop data lakes
  • NoSQL data stores
  • Data streaming services
  • Data marts
  • Enterprise applications
  • BI and analytics reports
  • Flat file feeds
  • Mainframe feeds
  • JSON files
  • Web services

Or maybe your company has decided to move you data from one vendor to another or from on premises to the cloud.

“On average, poor data quality costs organizations $14.2 million annually.”

- Gartner

“Dirty data costs the average business 15% to 25% of revenue.”

- MIT Sloan Management Review

“Cleaning up data will lead to average cost savings of 33%, while boosting revenue by an average of 31%.”

- PWC survey

The task of validating & testing all the data being collected is overwhelming.  You are struggling with questions such as:

  • How much data needs to be validated/tested?
  • How do I ensure I am testing the proper data permutations?
  • What are the critical data endpoints that need to be tested?
  • How do I verify that the data from my various source systems is propagating through the architecture?
  • How do I validate data in the cloud environments?
  • Is bad data making it into the architecture?
  • How much of the data testing can be automated?

In addition, upper management requiring you to integrate as many of the testing tasks as possible to into your CI/CD DataOps pipeline.

Our Solution

Data Sheet: Finding Bad Data. View Here

See the typical types of data issues in your data warehouse, big data, and BI projects.

Article: Data Quality Solutions & Bad Data: A Case of Misplaced Confidence? Read Here

RTTS’ Data Validation Assessment service provides an expert evaluation of your current data validation process. We also provide recommendations on how to improve your process and a proposal for successful implementation.

Turn-around time
5- 7 business days

Who will benefit
Any company with a need to create a data validation/testing strategy or improve their existing data validation & testing practices as they relate to industry standards.

Components of the Assessment

  • Business analysis
  • Data architecture analysis
  • ETL testing process evaluation
  • DataOps evaluation
  • Resource evaluation (optional)
  • Metrics evaluation
  • Risk assessment

Deliverables

  • Detailed analysis report with recommendations
  • Presentation to your team on findings
  • Proposal for successful implementation

RTTS can help you improve your processes and help you work towards a successful data testing strategy.

Are you interested in learning more or have additional questions?
Please fill out the form below and we will gladly assist you.

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