A Data & Analytics platform for optimizing the ADY% of large manufacturing company

Enabled a leading manufacturer to minimize scrap and implement a BI and Analytical platform to improve ADY % quickly

data-analytics-platform-casestudy

About the Client

The client is a leading telecom product manufacturer in India. Working across 3G and 4G networks, the client offers optical fiber cables (OFC), optical ground cables (OPGW), and transmissions to customers.

The Business Challenge

The client wanted to minimize scrap that was at 21% and improve the production efficiency that was at 79%. The client wanted to improve ADY% using static and dynamic parameters with an efficient BI& Analytical platform that would replace all future reporting systems. The client also wanted to focus on requirement gathering and business analysis to validate and resolve data quality issues.

What Aptus Data Labs Did

We created a BI and analytics platform to prepare data and deploy the model quickly with the ability to consolidate and validate key performance indicators of the company. We also built machine learning models for the optimization of ADY %

The Impact Aptus Data Labs Made

The new BI and analytical tool improved the execution performance of the machine learning algorithm by 200%. It reduced the execution time from 8 hours to 4 hours

The Business and Technology Approach

Aptus Data Labs used a methodical process to execute the BI and analytics tool to work out the existing challenge. Aptus Data Labs:

The Reference Architecture We Built

Microsoft-Data-Analytics-platform

Tools used

Microsoft Platform – Visual Studio Team Services, Azure Cloud, Azure SQL Server, Azure Machine Learning, Python, Power BI-Web Browser, Power BI, Power Query, & PowerPivot

The Outcome

The BI and analytics tool increased the model execution performance by 200%. It helped the client to reduce the data preparation and model execution time from 8 hours to 4 hours. It also provided the client with a cost-effective BI solution with report and dashboard function along with 24×7 platform support to manage scrap efficiently and improve ADY% by 200%

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