Key Success Metrics, Benefits, and Results for Data Observability Using DataKitchen Software

At DataKitchen, we would like to share some key success metrics of Data Observability Using DataKitchen DataOps Observability and DataOps TestGen.

Key Success Metrics, Benefits, and Results for Data Observability Using DataKitchen Software

 

Lowering Serious Production Errors

Key Benefit

Errors in production can come from many sources โ€“ poor data, problems in the production process, being late, or infrastructure problems. ย  Reducing the errors your customers find and those they do not are key success metrics of Data Observability Using DataKitchen DataOps Observability and DataOps TestGen.

DataKitchen Customer Quotes

โ€œAfter implementing, we reduced errors to just about one per quarter. We kept adding tests over time; it has been several years since weโ€™ve had any major glitches. This has dramatically increased our teamโ€™s efficiency and our end stakeholdersโ€™ confidence in the data.โ€ โ€” Associate Director, Insights, Top 10 global pharmaceutical company.

โ€œOur vision was to create a flexible, state-of-the-art data infrastructure that would allow our analysts to transform the data rapidly with a very low risk of error. After working with DataKitchen for a while, we noticed almost an absolute absence of data errors we didn’t catch earlier. That was amazing for the team.โ€ย  Director, Data Analytics Team

โ€œWe had some data issues. Databricks was all green. Thanks to Observability, I could diagnose the problem – definitely helped me a lot during the process.โ€ Industrial Data Team Member

Key Statistics with DataKitchen in Place:ย 

70 data sets, billions of rows of data processed monthly, with less than one error per quarter

Related Benefits

  • Increased end-user data trust
  • Reduced number of team data incidents and corresponding team time savings
  • Increase SLA adherence and on-time metrics
  • Wrong data or wrong reports/models are very costly to your business.ย  Data errors can cause compliance risks.
  • Business users lose trust in the data and have an opportunity cost.

 

Find and Respond to Problems Faster

Key Benefit

Problems in complex data systems will happen. ย  Can you identify those problems and find the sources quickly before your customers see them?ย  Given today’s complicated, multi-tool, multi-team data environments, this is challenging.

DataKitchen Customer Quotes

โ€œIt is a huge productivity win when someone on the team no longer needs to log in and monitor runs constantly. I used to be very, very careful when changing anything data-related, but I think youโ€™re starting to see that itโ€™s not that big a deal anymore because [if something goes wrong] we can now figure out what happened pretty quickly, and we can adjust it.โ€œย  Data Engineering lead, Financial Service Company

Key Statistics with DataKitchen in Place:ย 

โ€œWe effectively integrated a huge number of external data sources of varying quality and then updated data delivery frequency from once per day to once every 30 minutes because of automatically generated data processes and data quality production alerts.โ€ย  Global Pharma Company

Related Benefits

  • Improve time to remediation.
  • Lowers โ€˜data downtimeโ€™ when business users are not using the dataย 
  • Lowers the amount of team time on re-work and remediation

ย 

Improved Team Productivity

Key Benefit

In 2022 and 2023, Gartner stated that a 10x productivity edge exists for DataOps- (including data observability) driven data engineering teams. ย  If data teams are not manually chasing production errors and their root causes, they will have more time to add value to your business.

DataKitchen Customer Quotes

โ€œ.. its ability to put a baseline metrics lens over top of the data ecosystem. And by doing that, you can very simply draw attention to areas and provide data, KPIs, and metrics that people will believe.ย  Itโ€™s not you making stuff up anymore. Itโ€™s definitive, and that changes the game, especially for senior leadership.โ€

โ€œDataKitchen helped us completely transform our operations by broadening our testing definition. Testing the DataKitchen way was not limited to checking for basic attributes such as columns and rows; we expanded testing to include data accuracy and continuity. Tests assess important questions, such as โ€œIs the data correct?โ€ When business rules are applied, โ€œDoes the data make sense?โ€ โ€œIs there something new or unusual,โ€ and does the data align with its history and related data sets?โ€ The DataKitchen platform not only makes this level of testing possible but also practical.โ€

Related Benefits

  • Improved Data Quality Validation Testing
  • Example: One data team Increased the number of data quality tests from a dozen to over 10,000 with DataKitchen
  • Improved ability to measure team productivity and challenges
  • Improved data team happiness

 

Conclusion

“Key Success Metrics for DataKitchen DataOps Observability” showcases how DataKitchen’s DataOps Observability significantly reduces production errors, ensuring that data teams and their stakeholders can trust their data while dramatically increasing operational efficiency. Through compelling testimonials from industry leaders, including a Top 10 global pharmaceutical company and a prominent data analytics team, the blog illustrates the profound impact of DataKitchen’s data observability on reducing data errors to nearly zero and bolstering team productivity. With less than one error per quarter across 70 datasets processing billions of rows of data, the benefits extend beyond error reduction to include increased SLA adherence, enhanced end-user data trust, and improved team productivity. Gartner’s research underscores a 10x productivity edge for DataOps-driven teams, highlighting the transformational potential of DataKitchen in expanding the testing scope for data accuracy, continuity, and correctness. This paradigm shift in data observability allows teams to shift from manual error chasing to adding significant business value, fostering innovation and satisfaction among data professionals.

To explore how DataKitchen can redefine data observability for your organization and revolutionize your data operations, we invite you to learn more about our software and its transformative capabilities.

Sign-Up for our Newsletter

Get the latest straight into your inbox

Open Source Data Observability Software

DataOps Observability: Monitor every Data Journey in an enterprise, from source to customer value, and find errors fast! [Open Source, Enterprise]

DataOps Data Quality TestGen: Simple, Fast Data Quality Test Generation and Execution. Trust, but verify your data! [Open Source, Enterprise]

DataOps Software

DataOps Automation: Orchestrate and automate your data toolchain to deliver insight with few errors and a high rate of change. [Enterprise]

recipes for dataops success

DataKitchen Consulting Services


Assessments

Identify obstacles to remove and opportunities to grow

DataOps Consulting, Coaching, and Transformation

Deliver faster and eliminate errors

DataOps Training

Educate, align, and mobilize

Commercial Data & Analytics Platform for Pharma

Get trusted data and fast changes to create a single source of truth

 

dataops-cookbook-download

DataOps Learning and Background Resources


DataOps Journey FAQ
DataOps Observability basics
Data Journey Manifesto
Why it matters!
DataOps FAQ
All the basics of DataOps
DataOps 101 Training
Get certified in DataOps
Maturity Model Assessment
Assess your DataOps Readiness
DataOps Manifesto
Thirty thousand signatures can't be wrong!

 

DataKitchen Basics


About DataKitchen

All the basics on DataKitchen

DataKitchen Team

Who we are; Why we are the DataOps experts

Careers

Come join us!

Contact

How to connect with DataKitchen

 

DataKitchen News


Newsroom

Hear the latest from DataKitchen

Events

See DataKitchen live!

Partners

See how partners are using our Products

 

Monitor every Data Journey in an enterprise, from source to customer value, in development and production.

Simple, Fast Data Quality Test Generation and Execution. Your Data Journey starts with verifying that you can trust your data.

Orchestrate and automate your data toolchain to deliver insight with few errors and a high rate of change.