of rows of data housed and aggregated to support on-demand analytics across the enterprise
data lake consolidates all sources into one repository, replacing a fragmented multi-system environment
business analysts can now self-serve reports on sales, marketing, and advertising without delays
It’s easy to forget how big “big data” can really be. Large organizations produce vast quantities of data every day, sometimes with no practical way to capture, organize and store it all. The result: unwieldy data sprawl that prevents organizations from fully capturing a complete view of their operations.
As a healthcare education, product, and technology firm, our client was no stranger to these barriers. It generated massive amounts of data but had no central repository to organize that data and report on it across the enterprise. OneSix helped create a data warehouse solution that could put an end to our client’s data sprawl problems and establish a foundation to support ongoing analytics efforts.
Because our client produced so much data, OneSix used a centralized data lake approach to effectively house and manage its numerous, high-volume data sources. Our team helped define the data collection and aggregation strategy, as well as develop the solution’s information architecture.
Treasure Data’s cloud-based data management platform served as the basis for the data lake implementation and helped our team set up the automation needed to streamline data capture and aggregation across the enterprise.
With user-friendly dashboards and visualizations built through Tableau (leveraging data directly from the Amazon Redshift data warehouse), our client has the tools to easily generate reports for key stakeholders and guide strategic decision-making.
The new data warehouse solution can house and aggregate billions of rows of data to support end users in an on-demand capacity. The speed and agility of our client’s analytics capabilities have been greatly increased as a result of this new data lake implementation.
Business analysts can report on operational performance related to sales, marketing, advertising and much more. Thanks to OneSix’s help, our client is well-positioned to expand and refine its analytics efforts in the future, continuing to produce valuable insights that produce better business outcomes.
More to explore
OneSix built an AI product recommender that maximizes conversion and lets non-engineering teams tune it through low-code tooling.
OneSix helped a pricing consultancy reduce data processing time from over 10 hours to minutes by implementing a modern ELT pipeline using Azure Data Factory and Snowflake. The solution enhanced agility, scalability, and confidence in pricing insights.
Through a three-phase approach, including a comprehensive assessment, tailored recommendations, and a clear roadmap, OneSix helped the bank set the foundation for improved operational efficiency, enhanced customer experiences, and future-ready data strategies.