I like to think of data quality management within the context of physical fitness. You can get in shape with hard work, but staying in shape requires good habits. And above all else it's a mindset and a lifestyle. You also have to sweat. At least a little bit. No technology, including data observability, can act as a slimming belt toning your data quality while you lay back and … [Read more...] about Data Quality Management: 6 Stages For Scaling Data Reliability
big data quality
What Good Data Product Managers Do – And Why You Probably Need One
Atul Gupte co-authored this post. The companies we talk to are diligently building their data product or platform. This includes migrating to Snowflake, integrating with Databricks, moving towards a data mesh, or generally investing in their data stack. Increasingly, we are seeing data departments modernize their team structure with data product managers at the helm of such … [Read more...] about What Good Data Product Managers Do – And Why You Probably Need One
You Have More Data Quality Issues Than You Think: Here’s Why.
Say it with me: your data will never be perfect. Any team striving for completely accurate data will be sorely disappointed. Data testing, anomaly detection, and cataloging are important steps, but technology alone will not solve your data quality problem. Like any entropic system, data breaks. And as we've learned building solutions to curb the causes and downstream impact of … [Read more...] about You Have More Data Quality Issues Than You Think: Here’s Why.
6 Reasons Why Companies Fail at Data Governance
This article was written with Teresa Kovich, Principal Consultant at Das42. Everywhere we go in the cloud data space today, we're hearing one message loud and clear: "you should be thinking about data governance". It's a sentiment that we wholeheartedly endorse, but we like to take it a little bit further - you should be thinking about data governance differently. In this … [Read more...] about 6 Reasons Why Companies Fail at Data Governance
Data Integrity: the Last Mile Problem of Data Observability
Data quality issues have been a long-standing challenge for data-driven organizations. Even with significant investments, the trustworthiness of data in most organizations is questionable at best. Gartner reports that companies lose an average of $14 million per year due to poor data quality. Data Observability has been all the rage in data management circles for a few years … [Read more...] about Data Integrity: the Last Mile Problem of Data Observability