To execute a deep data quality analysis for a defined group of data assets to validate them for ingestion, modelling, reporting and automated data quality monitoring
Costs from a bad data quality are extensive. Almost one third of data analysts uses more than 40% of their time to check and to validate data used for analysis. Data workers waste almost half of their time trying to find data, hunt and fix issues and finding confirming data sources for those they do not trust. By an estimate up to 20-30 percent of operational expenses are result of bad data quality.
Cloud1 Data Quality Analysis is an agile deep dive data quality analysis project done with close collaboration with business. We combine both business and IT-demands and goals for data quality. During this project we will familiarize your organization to data quality and strengthen the knowledge and know-how among the project team. Project's goal is to find issues in data assets before they end up compromising ML model or data analysis projects or in worst case to be found from production environments.
Offer project produces: For the selected scope evaluation of the level of data quality, proposal of operational actions and tools and finally concrete plan to enhance and monitor the data quality.