For someone that’s been preaching data governance and data quality for more than fifteen years, it’s been fascinating to see how these two topics have been gaining traction in the last few years.

A few weeks back I touched on the difference between data governance and data quality – governance is about “what” and “who”, and data quality is about “how.”

This week, prompted by last week’s Precisely webinar Unlocking Greater Insights with Integrated Data Quality I want to look at the overlap, using a simple example of how this may work in practice.

Report Certification

It’s a common scenario. Two line of business managers generate similar reports, in theory measuring the same metric, and yet are presented with wildly different outcomes.

Certifying a report allows each decision maker to assess the trustworthiness of each report by allowing them to understand:

• Who was involved in the design and sign-off of the report?
• How are the terms, calculations and aggregations derived for each report?
• Where does the data come from and does it reflect the source?
• Can we trust the data?

Let’s look at each of these in turn

Who was involved in the design and approval of the report?

Governance is first and foremost about accountability. The delivery of a single report may involve multiple stakeholders across the organisation including:

• The business sponsor (or owner) who requested the report
• The business analyst and subject matter experts who designed the report
• The data engineer who sourced the data
• The BI developer that developed the report

Governance ensures that these stakeholders (and others that may be involved) collaborate effectively, that it is easy to identify who was involved and what their role and input was, and who approved the final deliverable. Governance makes it easy to engage the right people to clarify points of contention and to assess the rigour of the design process.

How are terms, calculations and aggregations derived for the report?

Conflicting interpretations of business metadata can be one of the most common issues causing mismatched results. In effect, two reports measuring churn can have different results if they calculate churn using different approaches.

Governance ensures that the definitions for each business term used are clearly defined and accessible, that each definition has engaged all the necessary stakeholders, and that definitions are shared across the enterprise where possible.

The governed business metadata generated helps us to understand our report

Where does the data come from?

Another common reality is that two reports may measure similar data from different sources. Sales reflected in the CRM system may only be reflected in the billing engine a month later.

By engaging the right people data governance helps to ensure that our hypothetical reports’ source and data lineage can be properly understood and assessed.

Can we trust the data?

Understanding the source of data is one aspect of trust. The other is data quality!

Data quality means measuring compliance of the data to an agreed (governance) set of standards and rules. For example, if we are not capturing gender indicators in our data then a report segmented by gender is probably going to be inaccurate.

Certifying each report for data quality allows executives to again compare each report with insight as to the level of confidence that they can apply to the outcomes.

Introducing Data360 Govern

Understanding your organization’s data landscape gives you the authority to monitor vital data aligned with key business outcomes. Data360 Govern is a comprehensive governance solution, empowering data consumers to connect data with business objectives.

In Data360 Govern, track business goals in real-time to see how data supports processes, compliance, reports, and metrics. Dashboards and reports offer insights into curated or transactional data, linking data to outcomes.

Data360 Govern collaborates with data quality tools to establish real-time data scoring rules. These rules measure data accuracy and completeness, covering metadata and transactional data for reporting and predicting business results.

Precisely’s business-first approach has led to the platform being positioned as a leader in the 2022 IDC Marketscape report: Data Catalog Software 2022 Vendor Assessment. According to the report, Precisely should be considered “when looking for a business-focused solution with integrated data catalog, data quality, and data integration capabilities.”

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