Financial Services & INSURANCE

Leveraging Improved Speed & Immutability of a Data Lake

[CUSTOMER] An automobile insurance company

[BUSINESS NEED] A cumbersome and slow Enterprise Data Warehouse (EDW) solution which adhered to a stringent set of schemas.

The company needed a way to ingest data from various sources & house it in an easily accessible repository. Following this, they also needed to transform the data, storing business-critical metrics & KPIs in data marts, which would then be utilized by business users for analytics, visualization, & advanced data science activities.

Open Source Migration, Architecture & Analysis

[CUSTOMER] A large provider of annuities and life insurance in the United States

[BUSINESS NEED] Increase in cost due to expensive software like SAS or SPSS

Traditionally companies have used software like SAS or SPSS for their analytic workloads and even for data loading and data munging. While these tools have been dominant in the data science domain for a while, open source tools, are becoming more mature, have deeper statistical and machine learning libraries, and the talent pool is increasing significantly.

    Data Management & Analysis on Azure

    [CUSTOMER] A business-to-business-to-consumer life & health insurance company

    [BUSINESS NEED] Data quality management and quality checks

    The company needed to identify ad-hoc solutions to produce weekly results and reports to its partners, set up IT best practices as the company matures, and adopt the right data analytics tools across different departments. Moreover, the company required assistance with setting up a data lake solution for data management across multiple teams.

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