About Team Insights

Data Engineering Solutions
Case Study 1

Company Background

Sasaran is a leading data and analytics firm dedicated to helping businesses unlock better insights from their data. We specialize in data mesh architectures that allow us to modernize enterprise data and unlock next-gen analytics use cases. We recently worked with a client in the food industry to help them improve sales and inventory.

Sasaran helped this client improve sales by using machine learning algorithms on their data and making it easily accessible for end users. This allowed them to take advantage of new opportunities in their market by providing more accurate insights.

Industry

Manufacturer of pharmaceutical devices

Technology Adopted

MINITAB

Challenges Faced

Our client was facing many challenges with their enterprise data, including a lack of scalability and an inability to access more meaningful insights from their data.

They needed a modern solution that could help them leverage all of their data to improve their sales and inventory.

Our Approach

At Sasaran, our approach was anchored in the creation of a data mesh architecture tailored to revolutionize our client’s enterprise data landscape, unlocking the gateway to advanced analytics use cases. We embarked on a collaborative journey with the client, first identifying the most critical data points.

Subsequently, we engineered a bespoke data mesh architecture, facilitating seamless access and utilization of their data resources in a meaningful manner.

Benefits

Our approach provided several benefits to our client, including:

  1. Improved scalability: Our client was able to scale their data solutions to meet their current and future needs.
  2. Enhanced insights: Our data mesh architecture enabled our clients to access more meaningful insights from their data.
  3. Increased ROI: Our data mesh architecture allowed our clients to get more out of their data, resulting in a higher return on investment.
  4. Improved sales and inventory: Most importantly, our client was able to improve their sales and inventory with greater accuracy and efficiency.