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Timeful Chooses Databricks Cloud to Enable Intelligent Time Management With Data Analytics

"Jobs" Feature Enables Company to Automate Monitoring of Key Metrics

April 3, 2015
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SAN FRANCISCO, CA--(Marketwired - Apr 3, 2015) - Databricks -- the company founded by the creators of the popular open-source Big Data processing engine Apache Spark with its flagship product, Databricks Cloud -- today announced that Timeful, a technology company innovating in intelligent time management, has deployed the Databricks Cloud platform to address its dynamic data processing challenges. Utilizing Databricks Cloud has enabled the company to understand Timeful users better with deeper analysis, and deliver a more accurate system for monitoring production recommendation algorithms.

Timeful helps its users manage their time better by tracking commitments, categorizing to-do list items and assisting in the development of good lifestyle habits. Deployed as an application on smart phone devices, Timeful utilizes machine learning to recommend a personalized schedule based on previous behavior, availability, and preferences. With the intensive demands of machine learning, however, came the difficulty in monitoring the quality of production recommendation algorithms and inconsistent access to production data.

The implementation of Databricks Cloud dramatically changed the way Timeful was able to meet several analytics needs including:

  • Faster and more accurate recommendation quality monitoring of terabyte scale data sets.
  • Automation and monitoring of production algorithms with the added ability to alert the engineering team as needed.
  • Providing designers and product managers access to production data to improve product design.
  • Utilization of zero-management capabilities to harness the power of Spark without investing in dedicated DevOps personnel.

"It's fantastic to see the immediate return on investment for Timeful with Jobs, the newest Databricks Cloud feature that automates the scheduling and management of production pipelines to run Spark workloads without any human intervention," said Ali Ghodsi, Co-Founder and Head of Engineering at Databricks. "Timeful's more meaningful and timely connections with its users is just one, albeit rewarding, way we're seeing Jobs improving the end-to-end user experience for our network."

"Databricks Cloud has allowed us to free up data engineers and data scientists to get back to problem solving, rather than acting as the bridge between the data and the rest of the team," said Gloria Lau, VP of Data at Timeful. "Now product managers and designers are able to run commands, collaborate on notebooks, and build and share dashboards all with a few clicks, which has been instrumental in accelerating our product development cycle."

For more information on Databricks Cloud, visit

About Databricks:

Databricks was founded by the team that created and continues to drive Apache Spark, the most active open source project in the Big Data ecosystem. Apache Spark is a powerful open source data processing engine built for speed, ease of use, and sophisticated analytics. Databricks' vision is to dramatically simplify big data processing and free users to focus on turning data into value. Databricks Cloud is a hosted end-to-end data platform powered by Spark. It enables organizations to seamlessly transition from data ingest through exploration and production. Databricks is venture-backed by Andreessen Horowitz and NEA. For more information, visit

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