Enhancing Data quality with Amazon Web Services (AWS)
Headquartered in the US, the client manufactures agricultural, constructional & forestry machinery, diesel engines, drivetrains (axles, transmissions, gearboxes) used in heavy equipment and lawn care equipment.
The client was struggling with business inefficiency due to low quality data. A huge size of data was being processed which affected its quality.
The client possessed a huge size of data which was captured from various sources (like servers, sensors, devices) onto Amazon Web Services. The greater data size affected the data quality which was hampering the business efficiency, decision making and data monetization. The client was facing issues like data duplication, missing values and outliers affecting the downstream user due to inaccurate information.
YASH was required to analyze and measure the data quality of inconsistent agronomic & machine data on a monthly & yearly basis using scalable big data platform on cloud. YASH enabled institutionalization of data quality management, thus making it easier for the business to trust the data and take corrective action for data inconsistency. YASH enabled the business to identify data inconsistency. YASH Cloud CoE also helped the client by providing best practices around data and cost optimization to help them innovate and optimize operational activities and reduce overall costs of operations.
The client had an enhance operational efficiency with a web-based metrics dashboard to view quality of data on a monthly and yearly basis. Their financial efficiency also increased with Amazon Web Services (AWS) and they had a better visibility of agronomic data set.