Mammoth Life Insurance Company Trusts Precisely on AWS for Cloud Modernization

Organizations build data lakes to improve reporting on historical data and capture insights only revealed by machine learning; where models can forecast likely business outcomes and suggest actions that support a desired result.

The construction of a data lake, however, can be a daunting project. Data lakes allow enterprises to import vast amounts of data in real-time. To move that data however, companies need to build data pipelines that collect data from multiple sources and move it into the data lake. Sometimes enterprises want to move the data in its original format, other times they want to transform it in flight. The most powerful data integration solutions support either scenario; allowing companies to scale data of any size, while eliminating the need to define data structures, schema and unwanted transformations.

In 2016, one of the largest mutual life insurance companies in the world embarked on such a project; to build a data lake in the cloud. This company wanted to inject operational data from their mainframe and make that data available to different lines of business to power BI and analytics. Because their on-premises data center was based on Hadoop; they wanted to begin their modernization journey toward AWS.

Their challenge revolved around enabling data visualization and BI on a broad range of organizational data sets. Data preparation related to these types of projects can be time consuming, particularly mainframe data prep; a top priority was to reduce data preparation and data transformation times. With more than 3,000 financial representatives in more than 70 agencies nationwide, the company also wanted to decrease time-to-market for analytics projects associated with this broad initiative. In the spirit of data democratization, they wanted to ensure that any employee could use appropriate data at any time to make decisions with no barriers to access or understanding. Easy data access and consumption was a main driver in promoting employee adoption of the initiative.

In 2017, this dominant insurance company chose Precisely Connect to break down data silos and ingest all their operational data from across the business and replicate it to AWS. In this manner, they created an Amazon-style data marketplace, supported by the data lake, Hadoop, and NoSQL. New projects would reuse and build upon existing data assets with Precisely Connect dynamically adding new data to the data lake with each new project. Connect’s ETL capability quickly ingested hundreds of database tables at push of a button. Change Data Capture technology then pushed changes from DB2 to the data lake in real-time, ensuring that all successive changes in on-prem systems were reflected in AWS, keeping data current, up-to-the minute.

This Fortune 500 company experienced many benefits from their Precisely on AWS solution. They were able to centralize and standardize reusable data assets, making them searchable, accessible, and managed. What’s more, Precisely Connect accelerated data acquisition which helped them meet their requirements for decreased time-to-market for analytics and reporting.

Build data trust and reveal new insights by integrating data from complex on-premises systems into AWS, and leverage addresses to organize and enrich your data for cloud-based analytics, machine learning (ML), and artificial intelligence (AI).  Learn more about Precisely on Amazon Web Services (AWS).