Risky Business: Don’t Ruin Your Organisation by Tolerating Poor Data Quality

Nearly everyone when asked about data quality will say, “our data is terrible”.

Most organisations suffer from poor data quality. We instinctively know the rise of AI and machine learning will only serve to shine the spotlight on data quality issues.

So, when we know our data quality problem is so big, why is nothing done about it?

Being able to measure data quality and show improvement is a sign of cross-functional data maturity. At its core, it is removing risky business practices.

But where do you start, and how do you get there?

That’s what our Data Governance Lead Tim Goswell and Business Transformation Lead James Bell discuss in this webinar:

• Why data quality is often not prioritised
• How to convey the meaning and impact of poor data quality for executives and the business
• How to move data quality from ‘nice to have’ to essential
• Who you need to be talking to in your organisation around data quality
• How do you settle for data quality that’s not 100% – where you do draw the line?
• How to establish personal accountability for data quality
• There are checks and balances for payroll – why not data quality?
• How to create myths and messages around data quality