Data governance is an often overlooked component of an organization’s data strategy. According to a recent article, it’s the most underrated trend in analytics in 2023.

In this blog post, we look at

• what data governance is
• why it is so essential in the context of big data
• why data literacy is the key to a successful data governance strategy

What is data governance?

Data governance refers to the planning, oversight and control over how data is managed and used in an organization. It determines who is accountable for data and data-related processes, who has the right to access data, what they are able to do with data, and under what circumstances.

Essentially, data governance is the system of rules and regulations an organization puts in place to cover all the ways in which data can be handled throughout its lifecycle.

Data governance rarely starts from scratch. Most organizations will have some rules in place when it comes to their use of data, even if they only exist as informal guidelines. But a strategic approach to data governance establishes systemic control, formalizing the way a company works with data and aligning it with their goals and overall mission.

A good data governance strategy will seek to:

• Document a company’s existing data governance structure
• Identify clear roles and responsibilities in an organization
• Create a catalog of data assets and the individuals associated with them
• Define data governance KPIs and ensure that they are monitored
• Establish support for the strategy at all levels of the organization.

Why is data governance crucial in the age of big data?

The way we work has been completely transformed by big data – the unprecedented amount of data that is generated, stored and exploited by organizations. The sheer volume, variety and velocity of data today presents companies with unique challenges that come from storing, maintaining, responding to and making business decisions based on this data.

💡 Learn more about big data and the challenges organizations are presented with in our latest ebook.

Data has never been more valuable, but it has also never been so challenging to manage how data is used. Data governance – a system of rules and oversight for how an organization handles data – has thus become an essential part of any data-driven business.

Particularly in a time of increasing political and economic uncertainty, companies have increasingly sought to base their decisions on the most reliable, up-to-date data available. But in this urgent rush towards data-driven decision making, many organizations have invested huge sums in sophisticated data analytics software. At the same time, they have allowed foundational components of data strategy, like data governance, to fall by the wayside.

A lack of proper data governance can lead to organizations failing to meet the challenges that arise when working with big data and missing out on the opportunities it presents:

• Data quality: Data governance radically improves data quality and reliability by protecting data users from the risk of outdated or erroneous data. As well as leading to missed opportunities, poor-quality data can be a huge drain on employees’ time. According to the recent McKinsey Global Data Transformation Survey, up to 30% of employees’ time is regularly spent on non-value added tasks because of poor data quality and availability.
• Data-related cost savings: Data management and maintenance are costly processes. Good data strategies streamline company processes and create new efficiencies; but without data governance, companies can fail to capture these cost savings. McKinsey identified data governance as among the top three differences between organizations that manage to eliminate millions, or even billions, of dollars of costs from their data ecosystems, and those that don’t.
• Democratization of data: What use is spending huge sums on sophisticated tools to capture and analyze company data if only a handful of people can use them? Data governance ensures that the right people are given the access they need, ensuring users miss fewer opportunities and make better decisions, faster.
• Compliance: Data governance has compliance at its heart – the need for companies to fulfill their regulatory responsibilities. Those who fail to put strong data governance processes in place can expose themselves to regulatory risk, potentially with existential costs to their business.

In sum, the lack of a sound data governance strategy can lead organizations to fail to capitalize on the benefits of the big data ecosystem and to fall short in areas like compliance, data quality and savings. By contrast, a well-defined data governance strategy gives employees across the organization the clarity and confidence to draw on large volumes of data across disparate data sources and to reap the benefits of data analytics.

Why is data literacy so important to data governance?

Data literacy is the ability to understand, evaluate and apply the structures behind data. Data literacy skills help employees derive value from and ultimately make sense of their data, giving them the confidence to put the results of data analysis into practice.

💡 Learn more about data literacy in our latest ebook.

A firm grounding in data literacy across the workforce is vital to the success of data governance initiatives, from implementation to ongoing efforts and uptake, particularly when it comes to the following key areas:

• Identifying areas of responsibility: Data governance relies on making ownership and responsibility for data-related tasks clear. A basic level of data literacy for anyone who works with data (whether they are responsible for creating, maintaining or analyzing that data) is essential for allocating and performing these tasks, and hence to a functioning data governance system.
• Working with the right data: According to some estimates, critical data represents no more than 10-20% of the total data in most organizations. As well as prioritizing important data to work with in terms of analysis, data literacy can help employees prioritize which data requires particularly careful handling and security.
• Developing a holistic, iterative approach: According to experts like the Business Application Research Center (BARC), data governance is not a “big bang” initiative but requires ongoing, organization-wide system change. It requires employees across the company, not just in IT or administration, to have a familiarity with at least basic data literacy to participate in the ongoing work of data governance.
• Bringing everyone in the organization on board: Resistance to change, particularly from higher-levels of the company, can be a major roadblock to data governance. Case studies from consultancies like PwC have shown that among the best ways to support data governance initiatives is by generating excitement for data and data-led decision making. Data literacy skills thus empower employees to both derive everyday benefits from data and to see the need for data governance.

In sum, data governance allows an organization’s data to be shared and used according to common guidelines in a systematic, democratic way. Data literacy gives individuals the confidence to derive value from that data. But the two are mutually reinforcing, creating a culture that brings all employees along and creating an organization where all employees truly understand the need for sound data governance principles.

💡 Curious about how Lyntics can help you to tackle the data governance challenges in your organization? Book a demo and let’s discuss!

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