SITUATION

Our client was leveraging three on-premise data systems to store critical financial data for their wealth management line of business. Cross-referencing customer data across three systems was a time-consuming process. They needed to consolidate these data systems into one easy-to-use and easily updatable platform. We were asked to build a new data analytics platform to consolidate the three data platforms necessary for wealth management to run their business.

Our team brought in the client’s data from mainframe and Salesforce. They built an extensive platform using Power BI and Tableau allowing data to feed into the system in a timely manner. We deployed a team of seven, including a wealth data management lead, lead Azure/data consultant, data designer, and cloud data architecture lead. They took all the client’s native mainframe files and used latest Azure tools, such as Key Vault and Data Factory, to import them. Our team used Databricks to process, store, clean, share, analyze, model, and monetize datasets with solutions from BI to machine learning. This platform unified the data sources in an Azure-based cloud architecture. Our team’s use of Data Lake storage was critical to ensuring that all client data was captured for compliance purposes and to be fed through the FeedHub for client use. Everforth Apex was responsible for setting up a FeedHub to serve as a filter for data to feed through from the multiple sources, filtering out data not relevant to the consumer’s search and ensuring they received the data they were searching for.

RESULTS

Everforth Apex built a single-source platform which allows the customer to better leverage data for analytics and decision making in a faster, more efficient manner. Roughly 100 files flow through the data feeds daily. This improved client efficiency, allowing them to respond to customer requests more quickly while saving time and money.