The Importance of Data Quality

Data quality is crucial in preventing the corruption of outcomes and ensuring accurate results in data solutions. Bad data can ruin processes and lead to costly resolutions. Telmine was inspired by the need to prevent bad data from entering systems, rather than fixing it afterwards. The complexity and variety of data make it a challenging problem to solve. Data quality issues span across multiple areas of an organization, requiring collaboration among various teams. Addressing data quality is both a technical and people problem, necessitating effective teamwork and communication.