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