How effective is your organization in governing its analytics processes and the responsible analytics teams? Are you taking advantage of analytics derived from Big Data? These are questions we posed to the data management professionals dialed in to the July webinar, Governing Quality Analytics, part of the Data Insights & Analytics educational series from DATAVERSITY.
First San Francisco Partners’ John Ladley led the call and covered these topics in the one-hour webinar:
- Degree of Governance Necessary to Use Analytics Effectively
- Level of Organizational “Maturity” Required to Be Effective (and Be Governed)
- Additional Capabilities Needed for Big Data Governance
- Support Required to Leverage Insights Gained From Big Data Analytics
John said at the call’s kickoff, “Governance is governance is governance. You have data assets that require rules to go along with them, even though there are different influencing factors that tweak governance.”
As a refresher for webinar attendees — and because attendees have varying degrees of knowledge about Enterprise Information Management — John shared our Data Governance definition:
Data Governance is the organizing framework for establishing the strategy, objectives and policy for effectively managing corporate data.
It consists of the processes, policies, organization and technologies required to manage and ensure the availability, usability, integrity, consistency, auditability and security of your data.
John expressed the importance of governing analytics in this way: “You want to exploit a data asset,” he said, “and the more robustly you want to do that, the more we find there needs to be an application of governance for analytics.”
John went on to say that, as your organization gets more effective and sophisticated at exploiting data, it will pull data in from more places (both internally and externally). This will require tighter oversights over quality, sourcing, distribution and the meaning of the data you’re using.
John also reviewed the different types of analytics — descriptive, predictive and prescriptive. (By the way, earlier this year we dedicated a full webinar to the analytic types. Get details here.) He then explained the varying degrees of governance types, including what he calls “DG lite,” Federated Oversight and Active.
Download Governing Analytics Replay
If you missed the Governing Analytics webinar and would like to hear John’s remarks in their entirety, visit DATAVERSITY’S webinar archive.
Curious to know the results of the webinar poll that we conducted on the webinar?
Of those who took time to share their thoughts, here are the responses:
How effective is your organization in governing its analytics processes and the responsible analytics teams?
- 4% – very effective
- 20% – somewhat effective
- 15% – not effective
- 9% – this is not a focus for us today
Is your organization taking advantage of analytics derived from Big Data?
- 16% – yes
- 22% – no
- 9% – not sure
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