Xplenty Helps Statiq Process 6X the Amount of Data, Even From a Mountain Top

Industry

Internet

Location

London, UK

Company Size

11-50 Employees

Statiq Case Study

Use Case

Collect and process 2 terabytes of data per day in a fast, efficient way that reduces human error.

While skiing on the French Alps, I got an SMS that my team urgently needed to run an ETL job. I logged into Xplenty's app from my mobile, set up a cluster and ran it. From the top of the snow capped mountain.

Ilya Kazansky, Statiq Founder and CTO

Data Processing at New Heights

The need to run ETL jobs doesn't only occur between the typical 9-5 workday. While on a ski vacation in the French Alps, Statiq Founder and CTO, Ilya Kazansky, was at the top of the top of the mountain about to head down the slopes when he got an urgent message from his engineering team back in the UK. In order for the team to continue working for the day, they needed to run an ETL job. With his cell phone in hand, he opened the Xplenty app, ran the necessary job and then got straight back to skiing (while his team got back to work). With Xplenty on the job, Statiq found an ETL tool that was cost-effective, scalable, and worked seamlessly regardless of whether jobs were being run from the office or the top of the world.

About Statiq

Statiq identifies the connection between people, places and locations over time. Our proprietary geo-location products provide an enhanced view of consumer interactions, enriching data sets to enable businesses to make better informed decisions.

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Challenges

  • Only able to process data infrequently due to lack of time and dedicated resources
  • Manually processing data was generating too many errors
  • Couldn't find a cost-effective ETL tool that was both easy to set up and scaled to meet Statiq's needs

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Solution

  • By implementing Xplenty's ETL service, Statiq was able to process quickly and frequently to provide clients with the freshest data continuously.

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Results

  • Automating the ETL process greatly reduced the time investment needed and eliminated human errors, making data more reliable.
  • Went from processing 10 terabytes of data every 2 months to 2 terabytes per day
  • Faster processing allowed Statiq to deliver the freshest data to its clients.
  • Scalable data processing to meet the growing needs of Statiq

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