Data Quality Steward - Increase Your Data Knowledge

High-quality data is key to interpretable and accurate data analytics and the basis for meaningful data-driven decisions. In practical scenarios, data quality is typically associated with data preprocessing, profiling, and cleansing for subsequent tasks like data integration or data analytics.

A steward is a person appointed to supervise or keep order. Data Quality Steward benefits promote a robust and sound data governance program that will facilitate good information governance practices.

Starting Data Quality Steward from SAS Best Practices

Healthcare organizations may need to be thoughtful about the process rather than hastily hiring someone to be a data steward. It is essential to have data stewards fall within the business units rather than solely within IT, noting that data stewards and IT should keep a collaborative relationship based on data needs. Data stewards require data skills, so begin your search by looking at your famous go-to experts.

Look at people who are currently working with data in the following areas:

• Clinical

• Financial

• Coding

• Data

• Technical

• Compliance

Next, hold one of the following models when starting Data Quality Steward from SAS Best Practices:

• Data Steward by Subject Area. In this model, all data steward owns and maintains a discrete data subject area.

• Data Steward by Function. Each data steward focuses on their business using the data.

• Data Steward by Business Process. A model for companies who have a strong sense of their enterprise-level processes. Data stewards are responsible for many data domains or applications for their specific business processes.

• Data Steward by Systems. Data stewards are allotted to the systems that make the data they handle.

• Data Steward by Project. This is practical and fast access to introduce Data Quality Steward. It is often a temporary approach that can be handled through a project management office that assigns data stewards to projects to document work processes documented for performance by other project teams. Once started, it can lead to a more formal way.

There are pros and cons to each of the above models, but it is an opening point to building a more solid data governance program. Some of my students have had the chance to work in IT departments who are taking inventory, also recognized as an information asset inventory of all the applications in their organization - which department owns it, who in the department is responsible for it, which department supports it, level of access required, whether the application receives or transmits PHI.

Here again, is a crucial opening point. An inventory database or spreadsheet is created with the information collected, and then policies and data models can be established and enforced. This exercise would also be an excellent method to identify the go-to experts in the different areas or the possible data stewards to get on board!

Without Data Quality Steward, an organization is missing out on all the value made from the data every day; if only it were designed and put in an order! Data stewards assure the quality of the data through pre-defined accountabilities, standards, and processes for those who work with the data. They are essential to organizations' ability to view their data holistically and leverage that data as an asset for more informed decision-making.

Find People That Best Fit Quality Steward Roles

Given that Data Quality Steward offices cover a few overarching skills within particular business frameworks, companies must invest in finding the best people to steward the data. A data steward must understand the available data assets at a high level, define them, and serve the business purpose. But the depth and meaning of subject and information technology expertise change in Quality Steward roles.

They do daily data cleansing tasks and manage Data Quality to align with data owners’ demands. Technical data stewards have expertise in the data systems used. They help with business data stewards to provide technical support and digital and IT knowledge to automate some Data Quality tasks. Many data steward parts fit a spectrum of business and data engineering requirements.

A data steward that knows what makes good Data Quality assets line up their skill sets as much as potential with the Data Quality Steward roles. Make sure that your organization has the right company fit for overseeing data so that you can be better prepared to tackle whatever lies before your ship in this flood of big data!