ROI on Data Observability
How to measure ROI on Data Observability

ROI on Data Observability

How often your data breaks?

This is your fundamental question to justify investment on data observability tools among all other IT budget in 2023.

Simply categorized:

?? I have data outages every week for some new reasons every time - Danger Zone 1

?? My data breaks once or twice in a month, its takes few days to resolve it - Danger Zone 2

?? I have data issues arising couple of times in a Quarter, but it takes weeks to resolve it - Danger Zone 3


If you fall under any of the above, definitely you have a strong proposal to your management on Data Observability budget. One of my customers in Automotive industry in USA faced huge problem in receiving reliable data on time every time. Customer runs 1000's of ingestion and reporting pipelines & have a sizable data engineering team; However, when analytics dashboard broke, half of the analytics team (4) were sitting idle (Productivity loss) and, data engineering team were running amok to detect the root cause of problem (Engineering time spent).


It nearly took 5 days by a team of 2 data engineers to identify that a schema shift has occurred in a particular data table, that was utilized by multiple intermediate transformation tables, which in turn branches out to feed analytics reports. In addition, impact of delayed analytics report is huge; in this case, customer had to share weekly reports to its partners & franchisees.


Simple & Real ROI of Data Observability can be derived as

?[Precious engineering time spent (AVG $25/Hr.) + Wasted Idle time of Analysts (AVG $20/Hr)]

*

[Impact of delayed report($100/Hr.)] (cost varies significantly based on your business)


= ($2000 + $3200) *100 -> ~??500K USD loss (conservatively).


Now is the opportunity to save this 500K USD using a Data Observability product that can

  • Automatically identify & monitor data issues ?
  • Get to the root cause ?
  • Alert the respective teams ?
  • Real time via slack, email, or API's to take immediate action ?


Have you faced any such situations like this, if so, please share in the comment.

Thanks for reading and feel free to share your suggestions.

#dataobservability #datareliability #cloudmonitoring #datatrustworthiness

#dataAnomalies

Geetika Pruthi

Product Analyst @Qualdo.ai | Advanced Data Engineering | Data Reliability, Quality & Data Observability on Cloud

1 年

Well articulated ????

Rasik Suhail

Associate Director @Qualdo.ai @Saturam Inc | Advanced Data Engineering | Data Quality | Data Observability

1 年

Good insights Sara TA It's high time enterprises start investing in Data Observability.

Satheesh Kumar Vadivel

Director , Data & Intelligence

1 年

Very good article Sara TA its important to leverage this Data Observability tools to take proactive actions.

Hasan TM

Director, Digital Go-To-Market Strategy @Qualdo.ai | B2B & SaaS Digital Marketing | Performance Marketing | Demand Generation | AI/ML/Data Enthusiast

1 年

Agree with your points Sara TA! Investing in zero-code Data Observability tools like #Qualdo could be an effective way to save 500K USD or more by proactively monitoring and resolving data issues before they become costly problems. #dataobservability #datareliability #dataengineering #cloud

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