Roundtable: June

Tackling the challenges of Data Quality

 

Why does data quality matter? Clearly organisations increasingly rely on data-driven decision-making processes, and therefore the integrity, accuracy, and reliability of the data at their disposal become essential. Poor data can lead to poor or incomplete business decisions. AI projects are founded on data and as these projects scale the impact of poor data can result in potentially serious business outcomes.

 

Data professionals understand that data quality challenges encompass a spectrum of issues ranging from inconsistencies and inaccuracies to incomplete or outdated information. Data profiling can help an organisation discover and investigate data quality issues, yet many executives pay lip service to the effort involved in resolving poor data quality.

 

In this round table we’ll discuss ways DataIQ members are approaching the challenges of data quality, how they are building their single version of truth, the tools and techniques being used and how they are helping colleagues use data to make the right business decisions.

 

Why should you attend?

 

• Learn from other practitioners and share your experiences with your peer group.
• Create new contacts with other DataIQ members, extend your professional network into the wider community.

Format

 

• 1 hour, digital roundtable delivered via Teams
• Closed forum, open discussion, recruiter and vendor-free, Chatham House rules
• Small and focused group of senior data leaders

To register for this event, simply email Nishita below and joining instructions will be sent to you directly. 

 

Please be aware there are only limited places available on a first come, first served basis (one seat per member company). Priority will be given to senior data leaders and additional registrations will be added to a waitlist.