What we learned about data quality at the Big Data Expo

Data quality is a critical issue for businesses, but it is not always a top priority. At the recent Big Data Expo, we spoke to a number of businesses about their experiences with data quality. We learned that many businesses are taking a DIY approach to data quality, which can be time-consuming and inefficient. We also learned that data quality is still seen as an engineering challenge, but the business needs to be involved in order to improve it.

Is data quality high enough on the list of priorities?

Interestingly enough these was a limited number of vendors offering specific data quality solutions. This is intriguing because data quality has gained substantial attention lately. On the one hand we would assume regulatory pressure and the ever growing interest in artificial intelligence applications would be a big driving force here. On the other hand this might be explained given research published earlier this year which reports that 70% of respondents struggle to trust their data, citing data quality as their biggest issue, but only 53% rank improving data quality as the top priority.

In-house solutions galore

We spoke to many companies that have taken the DIY route when it comes to data quality. They're crafting in-house solutions using a mishmash of SQL queries, Python scripts, and Power BI. Some dabble in building their own frontends using low-code platforms or even from scratch. As we’ve written before here we believe that a strategic approach here is beneficial to avoid reinventing the wheel and have a standardised approach to data quality in order to grow and scale and grow in step with these firms.

Data Quality: Still in technical territory

Another recurring theme we noticed was that data quality is still often perceived as an engineering challenge or is left to the IT department. The business hasn't quite taken the wheel yet. To enhance data quality technology and business teams need to work together. Hence collaboration and communication are key features of any data quality platform that is worth their salt.

Nevertheless, we feel the future of data quality is bright. As businesses become more data-driven, they will need to invest in improving their data quality. By taking a strategic approach and involving the business, firms can improve their data quality and make better decisions based on data.

Stay tuned for more data quality updates!

Mesoica’s data quality platform is designed to meet the evolving needs of today's organizations. By using our platform, you can continuously monitor data, identify trends, flag regressions, and foster communication and collaboration around data. Our platform is built to scale with your organization's growing data quality maturity needs and provide peace of mind. Start your journey towards becoming a truly data-driven organization today. Visit our website or contact us to learn more about how Mesoica can empower your organization to anticipate, prevent, and continuously improve data quality.