EXECUTIVE SUMMARY
Altair’s client suffered from lack of timely access to necessary data across its various units. Altair personnel led our client through the design and development of a central data repository, known as a Data Lake. This project provided our customer with a gateway into their valuable and untapped data, and was used for projects across all functions and at the executive level.
CHALLENGES
Our client was faced with sifting through massive amounts of information from multiple sources in order to perform many analysis. In particular, it was an arduous task for the investor team to gain access to relevant policy, loss, and claims data. It required IT representatives to manually integrate information and ensure errors were minimized in the process. When data is combined from sources enterprise-wide, it provides a more accurate and complete picture than they have ever had before. When it comes to decision-making, executives want to be informed using all data, including historical data – not just the last few months’ worth.
DATA FOR ALL
An opportunity emerged to aggregate various information sources into a central repository, known as a data lake, allowing for quick access to business users. As data from source systems is aggregated, defining data elements and understanding how they are used becomes an integral step in constructing a data lake. To facilitate broader use, a ‘data dictionary’ was developed that allows users that were unfamiliar with the source data to understand the intent of the information.
RESULTS, RETURN ON INVESTMENTS, AND FUTURE PLANS
Many areas of the company benefited from streamlined access to Data. The lowering of barriers between consumers of data and the repositories they were seeking to access, was the key to streaming business operations workflow.
* Executive Management was able to access data across silos for Investor Relations information and Customer interaction metrics.
* Underwriters/Actuaries have access to almost ALL the data they might require and can leverage the data work of other groups across the company.
* Analysts, data generalists, and stakeholders, such as finance and operations, have access real time data
* Data Scientists used big data sandboxes for analysis of things like checking pricing algorithms against real-time policy/claims data across the enterprise.
* Executive Management was able to access data across silos for Investor Relations information and Customer interaction metrics.
* Underwriters/Actuaries have access to almost ALL the data they might require and can leverage the data work of other groups across the company.
* Analysts, data generalists, and stakeholders, such as finance and operations, have access real time data
* Data Scientists used big data sandboxes for analysis of things like checking pricing algorithms against real-time policy/claims data across the enterprise.
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