Harness data-driven insights

All system, application, user, and patient data is backed up nightly and encrypted at the file level. All servers are updated regularly with the latest security patches, and they run on a dedicated network protected by firewalls, intrusion-detection systems, and controlled access points. That's how our Data Engineering service works.

• The business knows that there’s gold in all that data, and your team’s job is to find it. But being a detective with a bunch of clunky tools and difficult to setup infrastructure is hard. You want to be the hero who figures out what’s going on with the business, but you’re spending all your time wrestling with the tools.

• We built Databricks to make big data simple. Apache Spark™ made a big step towards achieving this mission by providing a unified framework for building data pipelines. Databricks takes this further by providing a zero-management cloud platform built around Spark that delivers.

  - fully managed Spark clusters,

  - an interactive workspace for exploration and visualization,

  - a production pipeline scheduler,

  - a platform for powering your favorite Spark-based applications. So instead of tackling data headaches, you can finally focus on finding answers that make an immediate impact on your business.

Yes. We use the very best and the latest in software, technology and infrastructure for our Data Engeneering service. By outsourcing you can save on investing on expensive software and technology as we use the very best in both. All our office have best-of-breed infrastructure.

There are two types of models we're using in Data Engeneering technology: predictive and descriptive. Descriptive models are good to explain what has happened and what is happening. Predictive models explain what would be happening and why. These models are increasingly being utilized to solve problems across finance, marketing, human resource, operations and other business functions.