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The Key to Faster Impact Analysis: Automated Data Lineage

Business intelligence databases are dynamic repositories that must often be adjusted based on organizational and or regulatory requirements. To make changes to a system, report, or process, BI developers must first perform impact analysis in order to gauge the potential impact of making such a change on the rest of the environment.

Given the enormous size of the business intelligence and analytics systems (data warehouses, ETLs, analysis tools and reporting tools) controlled by enterprise companies, performing impact analysis is by default a tedious and time-consuming procedure – it can take data teams weeks to comb through data to discover what areas will be affected by the change. How can BI teams reduce this laborious process? The answer hands down is automated data lineage, the key to faster impact analysis.

BI Solutions in Unexpected Areas

To illustrate how an impact analysis problem can keep a company from making progress, let’s look at an issue Octopai resolved for one of its customers.

A couple of years ago, the Department of Transportation discovered a problem with its seven-digit license plate system. There were too many cars on the streets, and licensing officials were running out of numbers for new plates.

To fix this, the Department of Transportation came up with a simple solution. It would increase the number of digits allowed on each plate from seven to eight. With this problem solved, the Department of Transportation sent a memo to insurance companies informing them of the impending change and moved along.

Data Lineage Problems Cause Major Roadblocks

Once the insurance companies began sifting through their databases, they found multiple obstacles to adjusting their databases and accommodating the new plates. As data experts looked through the millions of insured vehicles and license plates in their systems, they found there was no central database for license plate information.

Instead, there was a patchwork system created by different insurance offices and licensing facilities. The biggest obstacle to updating their catalog for the digit change was that the field names inside of different databases varied wildly.

In some places, the license plate would be listed as “license.” In other places, it would be “license plate.” In yet another place it might be simply “LP.”

To find the disparities in the system, create an impact analysis, and begin implementing the changes would take 6-8 months, by even the most generous estimates. With the insurance company’s current data architecture, the process would have no chance of being completed in time for the change.

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Automated Data Lineage Reduces Total Time to a Fraction

Faced with these data limitations, the insurance company reached out to Octopai. Octopai specialists looked at the discrepancies in the various databases and devised an automated data lineage solution that utilized metadata analysis to trace where the data originated and the paths it had taken to reach its current location.

With the implementation of these data lineage tools, the process was streamlined. Performing the impact analysis and making the required changes took a total of three days. Months of tedious data-combing and intensive mapping projects were eliminated once Octopai’s automated BI intelligence platform enabled the BI & Analytics team to identify any errors in the process as soon as they occurred. Automated data lineage and discovery increased the functionality of the entire system, allowing the data analysis team to locate field names, modify them, and view the full lineage of the information that created them.

Automating Metadata for Business Intelligence Elevates Enterprise Organizations

Octopai’s automated data lineage tools represent the pinnacle of modern BI organization. By leveraging the insight that comes with a full understanding of a data’s entire journey, you elevate your organization’s ability to make informed decisions and stay ahead of the competition.

Learn more about how Octopai can help transform your BI department into a team that is ready for the challenges ahead by visiting our resource center.

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Enabling visibility and control of metadata that is scattered across the BI landscape