Metacog provides analytics to education institutions, corporations, and government entities by monitoring and analyzing how individuals tackle open-ended performance tasks to assess whether learning goals have been met.
As result of the quantity of Metacog’s data and speed at which it needs to be processed and analyzed, Metacog was attracted to Apache® Spark™ as a big data engine for its flexibility in performing ETL and developing machine learning algorithms. Yet the company suffered release delays and software defects because thoroughly testing code on Spark clusters proved to be too complex and time-consuming.
With the implementation of Databricks, Metacog created an environment to fully automate their test and release processes, allowing them to achieve a number of benefits:
- Doubling the release cadence from 12 to 24 times a year.
- Achieved 28% infrastructure savings.
- Reduce new personnel onboarding time by 75%.
- Reallocate 20% of engineering time from maintenance to product development.