Leader in the chemicals industry needed to streamline data from multiple departments in their organization, so that they could process their high-volume of data and perform real-time analytics for understanding future business needs.
Client: A global leader in specialty chemical and ingredients distributor based in the US.
Problem: The client had been working on a legacy data storage platform, which made it challenging to store and analyze data. There were issues relating to data standards amongst the different departments within the enterprise, data duplication and missing data. Due to the legacy data storage platform and the vast amounts of data being collected by the client, they were not able to process the real-time data. The goal therefore was to modernize the data storage platform so that it was more flexible and agile than the traditional data management systems.
VT Solution: We built an AWS data lake solution for the client so that all data collected throughout the organization can be put together. Improving data accuracy, reducing data redundancy, and forming a single source for all the client’s data needs while also allowing client to traceback to the original data sources. The solution is forward looking as it can be scaled to high data volumes in a cost-effective manner, while also featuring support for different types of analytics.
These new capabilities allowed our client to generate effective insights by analyzing historical trends and utilizing machine learning models for predictive analytics to get recommendations and forecasts. In addition, it supported future analysis from within the client’s organization, by allowing in-house data analysts, data scientists, and business analysts to access the data using their choice of analytic tools.
Key Points:
- Achieved the organization’s goal by designing and implementing a single standard data storage system, reducing data redundancy, and improving accuracy.
- Provided a scalable solution that fits the clients need for growth and is personalized to their data requirements.
- Integrated analytical tools to allow easy access for in-house data professionals and analysts to work on the data with their preference of analytical and BI software.
