Establishing Data Governance Framework

here's informatica's perspective around a data governance framework this is based on our practical experiences and working with a number of customers across the globe starting with the first strategic drivers it's critical when you're starting out with data governance identify what are the key business drivers you're trying to resolve some examples include regulatory compliance operational efficiency or creating a culture of data or digital transformation you could have several business drivers next focus on the governance outcomes for example data democratization where making data freely accessible for the end users while ensuring quality and privacy standards next you could also have efficient regulatory management where anytime regulators are coming in asking you hey show me data quality of this product of this type typically what we hear is it takes customers few weeks to respond to the regulators why because quality of the product may be measured in multiple systems and applications there may be programming codes consolidating that into a single view is typically hard next you have quality management and also having a 360 view around the data the third piece in the framework is the people this is about creating diversification around the organization representation from business i.t and other groups within the firm then comes the process it could be around process for identifying issues around data remediation policy reviews setting up controls around data so people can have a view into how the data can be used for what purposes and lastly technology here you could have multiple technologies to address these needs for example data governance technology you have data catalog data quality data privacy and other related technologies here the big question for you is how are you implementing a data governance framework what are some of the things that are top of mind i'd love to hear from you now this brings us to the second big piece of the framework which is people here is a good example from new york life they created an organization that represents different pockets of the business at the top they have the enterprise steering committee second they have the enterprise data governance council representing data leaders technology leaders governance leads and representation from the architecture side and next you have the data stewardship here what's interesting is new york life compartmentalized their data by different domains like customer product or vendor so depending on the organization you might compartmentalize your data by domains by business lines by projects so depending on what model fits best at the domain level new york life identified different personas and these are the folks who roll up their sleeves and make data governance a real thing like really operationalizing data governance turning the strategy from the enterprise teams the steering committee into an actual implementation and last comes the data custodians and the enterprise data governance office representation from technology and other groups to ensure data governance meets all the dimensions around metadata management data cataloging data quality and privacy now that we've reviewed the people aspect let's take a closer look at the process aspect which is one of the key ingredients of this framework data governance is not a one-time project it's a continuous journey it's a collaboration between the executives the operational teams and the enterprise as you can see here in this process slide executives contain data governance program sponsors they realize the value in the program and invest in it next we have the enterprise here you have representation from different pockets of the business different leaders who provide the strategic support and objectives and next we have the data governance coe the main component of the coe is to establish data stewardship it might require program management consulting identification of different technologies building a strategy this is a group that really makes data governance a real thing the operationalization of data governance they help you operationalize data governance and as you can see data governance is a continuous journey which requires input from the ground and to the leaders to ensure quick wins are identified data challenges are timely identified and dealt with that was our topic to be where we reviewed business challenges around data governance and how do we establish a data governance framework thank you for watching you

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Length: 5min 11sec (311 seconds)

Published: Mon Jan 11 2021