Enterprises waste millions of dollars on failed data initiatives because they apply outdated thinking to new data problems, according to Jon Loyens, chief product officer & co-founder, Data World, who offered a presentation titled "Data Governance is Killing Your Business: Time to Fix It," at Data Summit Connect Fall 2020.
Videos of presentations from Data Summit Connect Fall 2020, a free series of data management and analytics webinars presented by DBTA and Big Data Quarterly, are available for viewing on the DBTA YouTube channel.
According to Loyens, all organizations today want to be data-driven, yet outdated practices are holding back data access in organizations. Trying to fix these issues with technology just makes it worse.
Deploying new self-service BI and data science tools and adding a layer of governance over the top typically results in overly complex, rigid processes that benefit the few and make everyone else less productive.
Agile data governance, on the other hand, said Loyens, is a new practice that applies the best of agile and open software development to data and analytics. It iteratively captures knowledge as data producers and consumers work together so that everyone can benefit.
According to Loyens, agile data governance is the process of creating and improving data assets by iteratively capturing knowledge as data producers and consumers work together so everyone can benefit. It adopts the proven best practices of agile and open software development to data and analytics.
To chart a new course to the world of agile data governance, said Loyens, remember three things:
- Culture is key to realizing data value: champion a data-driven culture from the top down
- Governance separates you from the pack: establish straightforward consistent processes to secure collaborative relationship
- Technology is keeping you from being a data-driven enterprise: accelerate investments in the right technologies for your data objectives
To bridge the gap from data producers to data consumers, a new role is necessary: "a data product manager" (knowledge scientist/data steward) who is responsible for the data requirements, makes sure data is used, makes sure data gets used correctly, and understands the business.
The impact of being inclusive
According to Loyens, a sole focus on making your most data-literate users savvier has diminishing returns. However, making your entire organization data literate multiplies data's value by introducing meaning, context, and diverse perspectives.
Intuitive and inclusive tools earn broader and deeper adoption, and people keep using tools that make their lives easier.
In addition, one team's completed analysis project could be another team's starting point. Continuously document your work and keep it accessible so no one else has to start from scratch.