How Leading Waste Management Company adaption of DQLabs on top of Snowflake led to 10X improvement in data quality and operational efficiency?

How Leading Waste Management Company adaption of DQLabs on top of Snowflake led to 10X improvement in data quality and operational efficiency?

The Client is one of the largest waste management companies in the United States, providing a wide range of waste management services for over 50 years including waste collection, transfer, disposal, and recycling. In order to effectively manage waste, the company must maintain accurate data about the waste streams it collects and processes. However, this can pose challenges for the company in terms of data management and data quality.

Data management challenges for the client include handling large amounts of data from multiple sources, including waste collection trucks, transfer stations, and landfills. This data must be collected, stored, and processed in a manner that is both efficient and secure. Additionally, the company must ensure that the data is accessible to the departments that need it, such as operations, customer service, and billing. Data quality challenges for the client include ensuring the data’s reliability, accuracy, and completeness, as well as addressing potential issues with data integrity and consistency. This can be particularly challenging given the high volume of data generated by the company’s operations. Inaccurate or inconsistent data can lead to problems such as incorrect billing, inefficiencies in processes, revenue loss, and reduced customer satisfaction.

By using DQLabs, We automated the end-to-end business process and were able to continuously monitor the critical data elements with better productivity..

PETER KAPUR

Head of Data Governance, Data Quality, and MDM – Enterprise Analytics & Data Management