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Data Governance Definition, Best Practices and Benefits

Any organziation with a data-driven strategy should understand the definition of data governance. In fact, in light of increasingly stringent data regulations, any organzation that uses or even stores data, should understand the definition of data governance.

Organizations with a solid understanding of data governance (DG) are better equipped to keep pace with the speed of modern business.

In this post, the erwin Experts address:

 

 

Data Governance Definition

Data governance’s definition is broad as it describes a process, rather than a predetermined method. So an understanding of the process and the best practices associated with it are key to a successful data governance strategy.

Data governance is best defined as the strategic, ongoing and collaborative processes involved in managing data’s access, availability, usability, quality and security in line with established internal policies and relevant data regulations.

It’s often said that when we work together, we can achieve things greater than the sum of our parts. Collective, societal efforts have seen mankind move metaphorical mountains and land on the literal moon.

Such feats were made possible through effective government – or governance.

The same applies to data. A single unit of data in isolation can’t do much, but the sum of an organization’s data can prove invaluable.

Put simply, DG is about maximizing the potential of an organization’s data and minimizing the risk. In today’s data-driven climate, this dynamic is more important than ever.

That’s because data’s value depends on the context in which it exists: too much unstructured or poor-quality data and meaning is lost in a fog; too little insight into data’s lineage, where it is stored, or who has access and the organization becomes an easy target for cybercriminals and/or non-compliance penalties.

So DG is quite simply, about how an organization uses its data. That includes how it creates or collects data, as well as how its data is stored and accessed. It ensures that the right data of the right quality, regardless of where it is stored or what format it is stored in, is available for use – but only by the right people and for the right purpose.

With well governed data, organizations can get more out of their data by making it easier to manage, interpret and use.

Why Is Data Governance Important?

Although governing data is not a new practice, using it as a strategic program is and so are the expectations as to who is responsible for it.

Historically, governing data has been IT’s business because it primarily involved cataloging data to support search and discovery.

But now, governing data is everyone’s business. Both the data “keepers” in IT and the data users everywhere else within the organization have a role to play.

That makes sense, too. The sheer volume and importance of data the average organization now processes are too great to be effectively governed by a siloed IT department.

Think about it. If all the data you access as an employee of your organization had to be vetted by IT first, could you get anything done?

While the exponential increase in the volume and variety of data has provided unparalleled insights for some businesses, only those with the means to deal with the velocity of data have reaped the rewards.

By velocity, we mean the speed at which data can be processed and made useful. More on “The Three Vs of Data” here.

Data giants like Amazon, Netflix and Uber have reshaped whole industries, turning smart, proactive data governance into actionable and profitable insights.

And then, of course, there’s the regulatory side of things. The European Union’s General Data Protection Regulation (GDPR) mandates organization’s govern their data.

Poor data governance doesn’t just lead to breaches – although of course it does – but compliance audits also need an effective data governance initiative in order to pass.

Since non-compliance can be costly, good data governance not only helps organizations make money, it helps them save it too. And organizations are recognizing this fact.

In the lead up to GDPR, studies found that the biggest driver for initiatives for governing data was regulatory compliance. However, since GDPR’s implementation better decision-making and analytics are their top drivers for investing in data governance.

Other areas in where well governed data plays an important role include digital transformation, data standards and uniformity, self-service and customer trust and satisfaction.

For the full list of drivers and deeper insight into the state of data governance, get the free 2020 State of DGA report here.

What Is Good Data Governance?

We’re constantly creating new data whether we’re aware of it or not. Every new sale, every new inquiry, every website interaction, every swipe on social media generates data.

This means the work of governing data is ongoing, and organizations without it can become overwhelmed quickly.

Therefore good data governance is proactive not reactive.

In addition, good data governance requires organizations to encourage a culture that stresses the importance of data with effective policies for its use.

An organization must know who should have access to what, both internally and externally, before any technical solutions can effectively compartmentalize the data.

So good data governance requires both technical solutions and policies to ensure organizations stay in control of their data.

But culture isn’t built on policies alone. An often-overlooked element of good data governance is arguably philosophical. Effectively communicating the benefits of well governed data to employees – like improving the discoverability of data – is just as important as any policy or technology.

And it shouldn’t be difficult. In fact, it should make data-oriented employees’ jobs easier, not harder.

What Are the Key Benefits of Data Governance?

Organizations with a effectively governed data enjoy:

  • Better alignment with data regulations: Get a more holistic understanding of your data and any associated risks, plus improve data privacy and security through better data cataloging.
  • A greater ability to respond to compliance audits: Take the pain out of preparing reports and respond more quickly to audits with better documentation of data lineage.
  • Increased operational efficiency: Identify and eliminate redundancies and streamline operations.
  • Increased revenue: Uncover opportunities to both reduce expenses and discover/access new revenue streams.
  • More accurate analytics and improved decision-making: Be more confident in the quality of your data and the decisions you make based on it.
  • Improved employee data literacy: Consistent data standards help ensure employees are more data literate, and they reduce the risk of semantic misinterpretations of data.
  • Better customer satisfaction/trust and reputation management: Use data to provide a consistent, efficient and personalized customer experience, while avoiding the pitfalls and scandals of breaches and non-compliance.

For a more in-depth assessment of data governance benefits, check out The Top 6 Benefits of Data Governance.

The Best Data Governance Solution

Data has always been important to erwin; we’ve been a trusted data modeling brand for more than 30 years. But we’ve expanded our product portfolio to reflect customer needs and give them an edge, literally.

The erwin EDGE platform delivers an “enterprise data governance experience.” And at the heart of the erwin EDGE is the erwin Data Intelligence Suite (erwin DI).

erwin DI provides all the tools you need for the effective governance of your data. These include data catalog, data literacy and a host of built-in automation capabilities that take the pain out of data preparation.

With erwin DI, you can automatically harvest, transform and feed metadata from a wide array of data sources, operational processes, business applications and data models into a central data catalog and then make it accessible and understandable via role-based, contextual views.

With the broadest set of metadata connectors, erwin DI combines data management and DG processes to fuel an automated, real-time, high-quality data pipeline.

See for yourself why erwin DI is a DBTA 2020 Readers’ Choice Award winner for best data governance solution with your very own, very free demo of erwin DI.

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Google’s Record GDPR Fine: Avoiding This Fate with Data Governance

The General Data Protection Regulation (GDPR) made its first real impact as Google’s record GDPR fine dominated news cycles.

Historically, fines had peaked at six figures with the U.K.’s Information Commissioner’s Office (ICO) fines of 500,000 pounds ($650,000 USD) against both Facebook and Equifax for their data protection breaches.

Experts predicted an uptick in GDPR enforcement in 2019, and Google’s recent record GDPR fine has brought that to fruition. France’s data privacy enforcement agency hit the tech giant with a $57 million penalty – more than 80 times the steepest ICO fine.

If it can happen to Google, no organization is safe. Many in fact still lag in the GDPR compliance department. Cisco’s 2019 Data Privacy Benchmark Study reveals that only 59 percent of organizations are meeting “all or most” of GDPR’s requirements.

So many more GDPR violations are likely to come to light. And even organizations that are currently compliant can’t afford to let their data governance standards slip.

Data Governance for GDPR

Google’s record GDPR fine makes the rationale for better data governance clear enough. However, the Cisco report offers even more insight into the value of achieving and maintaining compliance.

Organizations with GDPR-compliant security measures are not only less likely to suffer a breach (74 percent vs. 89 percent), but the breaches suffered are less costly too, with fewer records affected.

However, applying such GDPR-compliant provisions can’t be done on a whim; organizations must expand their data governance practices to include compliance.

GDPR White Paper

A robust data governance initiative provides a comprehensive picture of an organization’s systems and the units of data contained or used within them. This understanding encompasses not only the original instance of a data unit but also its lineage and how it has been handled and processed across an organization’s ecosystem.

With this information, organizations can apply the relevant degrees of security where necessary, ensuring expansive and efficient protection from external (i.e., breaches) and internal (i.e., mismanaged permissions) data security threats.

Although data security cannot be wholly guaranteed, these measures can help identify and contain breaches to minimize the fallout.

Looking at Google’s Record GDPR Fine as An Opportunity

The tertiary benefits of GDPR compliance include greater agility and innovation and better data discovery and management. So arguably, the “tertiary” benefits of data governance should take center stage.

While once exploited by such innovators as Amazon and Netflix, data optimization and governance is now on everyone’s radar.

So organization’s need another competitive differentiator.

An enterprise data governance experience (EDGE) provides just that.

THE REGULATORY RATIONALE FOR INTEGRATING DATA MANAGEMENT & DATA GOVERNANCE

This approach unifies data management and data governance, ensuring that the data landscape, policies, procedures and metrics stem from a central source of truth so data can be trusted at any point throughout its enterprise journey.

With an EDGE, the Any2 (any data from anywhere) data management philosophy applies – whether structured or unstructured, in the cloud or on premise. An organization’s data preparation (data mapping), enterprise modeling (business, enterprise and data) and data governance practices all draw from a single metadata repository.

In fact, metadata from a multitude of enterprise systems can be harvested and cataloged automatically. And with intelligent data discovery, sensitive data can be tagged and governed automatically as well – think GDPR as well as HIPAA, BCBS and CCPA.

Organizations without an EDGE can still achieve regulatory compliance, but data silos and the associated bottlenecks are unavoidable without integration and automation – not to mention longer timeframes and higher costs.

To get an “edge” on your competition, consider the erwin EDGE platform for greater control over and value from your data assets.

Data preparation/mapping is a great starting point and a key component of the software portfolio. Join us for a weekly demo.

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Top 7 Data Governance Blog Posts of 2018

The driving factors behind data governance adoption vary.

Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent.

Historically most organizations have approached data governance in isolation and from the former category. But as data’s value to the enterprise has grown, so has the need for a holistic, collaborative means of discovering, understanding and governing data.

So with the impetus of the General Data Protection Regulation (GDPR) and the opportunities presented by data-driven transformation, many organizations are re-evaluating their data management and data governance practices.

With that in mind, we’ve compiled a list of the very best, best-practice blog posts from the erwin Experts in 2018.

Defining data governance: DG Drivers

Defining Data Governance

www.erwin.com/blog/defining-data-governance/

Data governance’s importance has become more widely understood. But for a long time, the discipline was marred with a poor reputation owed to consistent false starts, dogged implementations and underwhelming ROI.

The evolution from Data Governance 1.0 to Data Governance 2.0 has helped shake past perceptions, introducing a collaborative approach. But to ensure the collaborative take on data governance is implemented properly, an organization must settle on a common definition.

The Top 6 Benefits of Data Governance

www.erwin.com/blog/top-6-benefits-of-data-governance/

GDPR went into effect for businesses trading with the European Union, including hefty fines for noncompliance with its data collection, storage and usage standards.

But it’s important for organizations to understand that the benefits of data governance extend beyond just GDPR or compliance with any other internal or external regulations.

Data Governance Readiness: The Five Pillars

www.erwin.com/blog/data-governance-readiness/

GDPR had organizations scrambling to implement data governance initiatives by the effective date, but many still lag behind.

Enforcement and fines will increase in 2019, so an understanding of the five pillars of data governance readiness are essential: initiative sponsorship, organizational support, allocation of team resources, enterprise data management methodology and delivery capability.

Data Governance and GDPR: How the Most Comprehensive Data Regulation in the World Will Affect Your Business

www.erwin.com/blog/data-governance-and-gdpr/

Speaking of GDPR enforcement, this post breaks down how the regulation affects business.

From rules regarding active consent, data processing and the tricky “right to be forgotten” to required procedures for notifying afflicted parties of a data breach and documenting compliance, GDPR introduces a lot of complexity.

The Top Five Data Governance Use Cases and Drivers

www.erwin.com/blog/data-governance-use-cases/

An erwin-UBM study conducted in late 2017 sought to determine the biggest drivers for data governance.

In addition to compliance, top drivers turned out to be improving customer satisfaction, reputation management, analytics and Big Data.

Data Governance 2.0 for Financial Services

www.erwin.com/blog/data-governance-2-0-financial-services/

Organizations operating within the financial services industry were arguably the most prepared for GDPR, given its history. However, the huge Equifax data breach was a stark reminder that organizations still have work to do.

As well as an analysis of data governance for regulatory compliance in financial services, this article examines the value data governance can bring to these organizations – up to $30 billion could be on the table.

Understanding and Justifying Data Governance 2.0

www.erwin.com/blog/justifying-data-governance/

For some organizations, the biggest hurdle in implementing a new data governance initiative or strengthening an existing one is support from business leaders. Its value can be hard to demonstrate to those who don’t work directly with data and metadata on a daily basis.

This article examines this data governance roadblock and others in addition to advice on how to overcome them.

 

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