Our customer felt as though they were underperforming their competitors. They knew processes needed to change, but weren't sure where to get started.
In a nutshell
The company wanted business data to drive smarter decision making, but they felt hampered by the amount of data ingestion and analysis required to make effective use of business intelligence.
In helping the client organize, clean up, and assess data, Redapt paved the way for intelligent, data-driven decision making.
The customer was drowning in data. They did not have the time to parse data or tell what was important from what was unimportant.
They wanted to move faster with regards to sorting, assessing, and acting upon data. Team members were handling data arriving from different sources with different quality and validity issues, such as missing data fields or bad data. As a result, they spent significant time cleaning data in order to assess it, while fresh data kept accumulating.
The business was falling further behind competitors due to the time required to assess, transform, and analyze data.
The business partnered with Redapt to architect and deploy their modern data platform. This allowed them to get the most amount of data, in the shortest amount of time, while simultaneously improving the quality of that data for business intelligence (BI) purposes.
By using a data lake, the business was able to improve their data yield—mining the already existing data in novel ways to get higher level uses from that data.
Moment of clarity
To regain a competitive advantage, the organization realized they needed to speed up the data ingestion, cleaning, and analysis process to leverage data for in-time decision making.
What the company needed
Redapt surveyed the client about their pain points, considerations, and needs. Noting that cost was a driver, Redapt found an affordable and cost-effective way to leverage BI for smarter decision making.
Redapt incorporated a data lake to quickly intake, store, and analyze data. After fixing the organization’s data storage and management problem, Redapt was able to introduce BI solutions to help the client understand customer behavior, determine trends and insights, and act upon the data in a timely manner.
Redapt believed the data lake approach was the most effective and efficient way to improve the data yield and accuracy, which was the first step to extracting more value from the company’s data.
The end result
The business was able to increase their innovation in key performance metrics while making smarter use of existing data assets. The cost-effective nature of artificial intelligence meant the client could obtain powerful results without overspending.
The most notable improvements were in the area of productivity. Due to the efficient nature of data lakes, team members were able to quickly plug in multiple tools in a very cheap and cost-effective manner instead of spending significant time and resources cleaning, sorting, and analyzing data.
Contact us to gain a little more clarity
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