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What Is Good Data Governance

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What Is Data Governance And Why Is It Important To Your Business

What is Good Data Governance?

Im a fan of getting things done quickly. I walk fast, I talk fast, I drive fast.

But Ill freely admit that doing something fast isnt always the best way.

In fact, there are quite a few things out there that are best done carefully and methodically, if you want the best results.

Crossing the street, for example. Even though I walk quickly, I always stop to look both ways first. Given my high level of impatience, imagine how much faster I could get where Im going if I didnt have to check for cars every time.

But the fact of the matter isdanger is out there cars are on the road. And if one hits me, I wont get where Im going at all, no matter how fast I was walking.

The same applies to your business.

You could get so much more done if you didnt have to follow lots of rules and regulations on how you handle your data.

Employees could access data from anywhere. They could share client data between teams in whatever way got the job done fastest. Your tech team could focus on important projects without having to worry about backing up your data.

But danger lurks in the business world, too. Cyber criminals are out there. They want your data. And their techniques for acquiring it are getting more advanced and more harmful.

So how do you protect your business from the dangers of a world that grows more closely connected all the time?

Lay down ground rules for what your employees can and cant do with your companys data.

In other words, you step up your data governance game.

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2010: 1st Tools To Comply With The Regulation C

With the increasing complexity of data resources/processes on one hand and the first fines for GDPR infringement on the other, companies started to build regulatory compliance processes. The 1st pieces of software to organize Governance and Privacy were born with companies like Alation and Collibra.

The challenge is simple: enforce traceability across the various data infrastructure in the company. Data governance was then a privilege of enterprise-level companies, the only ones able to afford those tools. On-premise data storage makes it expensive to deploy this software. Indeed, companies like Alation and Collibra had to deploy technology specialists on the field to connect the data to their software. The first version of data governance tools aims at collecting and referencing data resources across the organizations departments.

There were several forces at play in this period. It became easier to collect data, cheaper to store it, simpler to analyze it. This led to a Cambrian explosion of the number of data resources. As a result, large companies struggled to have visibility over the work done with data. Data was decentralized, untrustworthy & irrelevant. This chaos brought a new strategic dimension to data governance. More than a compliance obligation, data governance became a key lever to bring about business value.

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What Is Data Governance And Why Is It Important

Did you know: The worlds data volume will grow at a staggering 40% per year? Thats according to the Aureus Analytics report that projects growth trends from 2021-2026. As far back as the early 2000s, enterprises recognized data as a strategic asset of the company to guide strategic decision-making, promote experimentation to learn and improve, and deliver better business results.

But after public data breaches jolted well-known brands like Facebook and Yahoo, data security has become a top priority for enterprises. This led to the demand for regulatory data governance.

Data Governance Vendors And Tools

Data Warehousing &  Governance

Data governance tools are available from various vendors. That includes major IT vendors, such as IBM, Informatica, Information Builders, Oracle, SAP and SAS Institute, as well as data management specialists like Adaptive, ASG Technologies, Ataccama, Collibra, Erwin, Infogix and Talend. In most cases, the governance tools are offered as part of larger suites that also incorporate metadata management features and data lineage functionality.

Data catalog software is included in many of the data governance and metadata management platforms, too. It’s also available as a stand-alone product from vendors such as Alation, Alteryx, Boomi, Cambridge Semantics and Learn more about the features that data catalog software offers, including its governance-related capabilities.

Continue Reading About What is data governance and why does it matter?

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Identify The Roles And Responsibilities

Data governance calls for teamwork with deliverables from all the departments. Clearly defined roles are essential to every data governance program, and it is important to assign levels of ownership across your organization.

Determining who has authority and responsibility will help socialize the data governance program and establish an intelligent structure to tackle data programs as one team. Data governance roles might include data governance council, data managers, data owners, data stewards, and data users, to name a few.

Data Governance In The Cloud

As cloud adoption accelerates, questions inevitably arise about how it impacts data governance. Enterprises have concerns that:

  • Their data will be secure:Businesses may be concerned about storing data in the public cloud. They are still responsible for controlling data governance on the data for their on-premises systems, but need to know that their cloud provider will protect against its exposure or theft when it is stored in the cloud.
  • The cloud vendor will comply with regulations: Enterprise compliance officers and data stewards responsible for adhering to regulations and standards need to feel confident that their cloud vendor will also adhere toGDPR,CCPA,PCI DSS,HIPAA, and other regulations and need to provide them with tools to help vendors comply when their data is in the cloud.
  • They will have visibility and control: Public cloud providers know that their ability to help with data governance can inspire customer trust and massively enhance the customer experience. As a result, leading cloud vendors offer tools for data assessment, metadata cataloging, access control management, data quality, and information security as core competencies to companies that use their platforms.

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Start Small But Consider The Larger Picture

Data governance is built on three pillars: people, process, and technology. A business builds the larger picture when it starts with the people, builds the processes, and finally incorporates technology into the processes.

Without the right people, its difficult to build successful processes needed for the technical implementation of data governance. Hence, identifying or hiring the right people for your solution can be the starting point for an organization. The right people can then help build your processes and source the technology to accomplish the job.

The Straightforward Guide To Data Governance

What Is Data Governance? 2 Minute erwin Expert Explanation

Data governance plays a major role in organizing and protecting your internal data. It acts as a form of insurance that every piece of information you collect is properly stored and distributed within your organization.

In this post, let’s discuss what data governance is and how you can implement a policy at your company.

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Develop A Business Case

Ensuring buy-in and sponsorship from leaders is key when building a data governance practice. But buy-in alone wont fully support the effort and guarantee success. Instead, building a strong business case by identifying opportunities that data quality will bring may be helpful.

Improvements can include an increase in revenue, better customer experience, or efficiency. Leaders can be convinced that poor data quality and poor data management is a problem. But, data governance plans can fall flat if leadership isnt committed to driving change.

Key Challenges To Effective Data Governance

The power of data in driving business growth is well known today. Effective data governance allows organizations to get maximum benefits from their most valuable asset. With high-quality data, businesses are able to gain insights for better business decisions and increase efficiency and productivity.

Moreover, data governance also protects the business from compliance and regulatory issues which may arise from poor and inconsistent data.Gartner predicts that through 2022, only 20% of organizations investing in information governance will succeed in scaling governance for digital business. Here are some common challenges organizations face while establishing data governance frameworks and policies:

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Understand The Value Of Information

Data governance is almost a misnomer because it doesnt necessarily reflect the real value of the insights gleaned from information.

Information is the correlation of data that creates value for an organization, says Marc Johnson, a senior advisor and virtual CIO at healthcare consulting firm Impact Advisors. This includes financial records, patient records, employee records, etc.

Governance needs more than data classification, Johnson says. It needs information classification. Information classification indicates the value to the organization and subsequent impact if lost, stolen, or destroyed. He cites an example of an employee emailing information from a corporate account to a private account.

We had data loss prevention in place to block electronic protected health information from exfiltration, Johnson says. Had we not taken the step to classify information, not just data, we would have blocked a chore task list. If we had not performed the additional due diligence, it could have resulted in tens of thousands of false positives within our systems, resulting in alert fatigue, excessive network traffic, and an unwarranted heightened alarm status in the security operations center.

Data governance requires detailed due diligence to know who has access to what information and how valuable that information is to the organization, its customers, employees, partners, and others.

Implementing A Data Governance Initiative

Data Management vs Data Governance: An Introduction â BMC Software

Data governance is not a big bang initiative and would not work in this fashion. Instead, global initiatives are highly complex and long-term projects. They therefore run the risk that participants might lose trust and interest over time.

It is therefore recommended to start with a manageable or application-specific prototype project and to continue iteratively. In this way, the project remains manageable and experience can be used for more complex projects or to expand the data governance programs in the company.

Typical project steps are:

  • define goals and understand benefits
  • analyze current state and delta analysis
  • derive a roadmap
  • convince stakeholders and budget project
  • develop and plan the data governance program
  • implement the data governance program
  • monitor and control.

These steps are not only to be repeated for each new program, but they also need to be repeated if changes are made.

Before the start of any data governance program, questions about the reasons for the project should always be answered in order to avoid unnecessary additional work. Similarly, existing processes should be evaluated to determine whether they can be adapted to the new requirements within the framework of a data governance program, instead of starting with the perhaps unnecessary development of new processes.

The following tools provide assistance with the implementation of a data governance program:

Data Management Framework

BARC 9-Field Matrix

BARC 9-Field Matrix

Role Models

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Data Standards & Data Rules

A data standard provides a framework and an approach to ensure adherence to a data policy. An example of a data standard could be using theISO 3166 standard for the definition of the codes for the names of countries, dependent territories, special areas of geographical interest, and their principal subdivisions.

A data rule directs or constrains behavior to ensure adherence to data standards, which provides compliance with data policies. An example of a data rule would be an organization that only allows country codes listed in the ISO 3166 Standard. Typically, organizations will look to establish data rules for master and reference data, data definitions and domain development, metadata management, classification, accessibility, and many others.

A data governance program can leverage many data standards. Some of the more notable data standards include:

  • International Organization for Standardization : 3166, 19115, 11179
  • Dublin Core: A basic, domain-agnostic, most widely used metadata standard that can be easily understood and implemented.

Also Read:Top 10 Data Governance Tools for 2021

Roles In The Framework

Chief Data Officer

Chief Data Officers are a fast-growing job over the last few years. Companies are beginning to understand the importance of managing data and implementing a data governance framework, and that means hiring a CDO. The CDO is the company leader of the data governance strategy, and hiring a CDO shows the commitment to data and buy-in from the top to take a data governance program seriously.

Data Owners

Data Owners are the people that have direct responsibility for data. They are involved in the protection and quality of data as a business asset. A data owner will be on the team that uses the data. For example, a member of the finance team should be a Data Owner for the Finance teams data.

Varonis automates the process for Data Owners to manage access to their data. Data Owners know who in their organization should have access to their data, and providing them the tools they need to manage and audit access to data is good data governance.

Data Stewards

Data Stewards are the champions of your data governance strategy. They meet with Data Owners and enforce data governance policies and procedures, as well as train new data owners and employees in data governance.

Data Governance Committees

The Data Governance Committee sets policies and procedures for data governance. This committee works with the CDO to establish the who, what, when, where, and why of data governance.

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Adopt A Data Governance Office

Once your goals are set, you’ll need employees to achieve them. While you could assign one or two people, the most effective way to implement data governance is with a complete team.

Your team should include management, data stewards and liaisons, and any other company stakeholders involved in obtaining or securing data. These people will be considered your “data governance office” and will be in charge of making important managerial decisions.

Good Data Starts With Great Governance

How to write a good Data Governance Policy – Nicola Askham, The Data Governance Coach

November 11, 2019 By Elias Baltassis, Antoine Gourévitch, and Lucas Quarta

It was not that long ago that pundits were ringing in a new era of big data in which all of a companys information, together with the abundance of data available in the world, would come together in a glorious engine of growth for companies everywhere. To their credit, many organizations sat up and took notice. Today, its accepted wisdom that data and analytics provide an essential tool in competitive differentiation.

Still, too many companies embrace data and leave it at just that. To be sure, leading companies in every industryincluding retail, telecommunications, pharmaceuticals, and banking and insurancehave adopted advanced analytical methods and high-performance data-handling capabilities to improve cost performance and increase revenues.

Indeed, many have achieved small, early wins with pockets of analytics applications, but scaling those wins requires internal development of a full set of data capabilities.

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Where Are You On The Data Maturity Curve

Putting in place these building blocks will help establish a solid system for data governance within your organization. And, with each step, a business will become more mature, able to extract more and more knowledge and intelligence from their data. This is what is called the data maturity curve and most businesses who are serious about the role data plays are somewhere on this trajectory. As you think about your own data governance, think about where you currently are on this curve, and what steps you can take to reach higher up.

If youre struggling with how to move further along the data maturity curve, our Sales Consultants will be happy to assist you in finding the right way. Schedule a call now!

What To Include In Your Data Governance Strategy

As discussed, data governance is a broad category. Consequently, there are a number of things included in a strong data governance framework. As a start, it should include policies, rules, procedures, and structures for data management.

To help ensure that these procedures are focused and working towards the right objectives, its a good idea to create some foundational documents to guide the process. These should include:

  • A mission statement
  • Metrics by which the goals will be measured
  • Clear guidelines detailing who is responsible for various aspects of data governance

Further, throughout every phase of this process, its important to document all parts of the framework and share them throughout the organization.

In addition to the above policies and procedures, some enterprises make the decision to utilize data governance software to help with implementation and enforcement. While this isnt a requirement, many organizations decide to utilize this software to help support:

  • Program and workflow management
  • Development of policies
  • Process documentation

Such software can be an effective way to ensure that plans are effectively developed, implemented, and enforced.

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Best Practice #: Track Progress

At the risk of sounding like Captain Obvious, you cant manage what you cant measure. Thats why your data governance program should have a way of reporting that tracks its progress towards the program goals.

While this depends on your governance programs KPIs, it could include anything from updates on lineage mapping to final decisions on the data owners for specific domains and their responsibilities.

How will you track data governance KPIs?

Naturally, the next question is what should we use to track these KPIs?

Several companies still use good ol spreadsheets to track progress and while it works for smaller use cases, its not practical for organization-wide governance initiatives. Thats why its a better idea to invest in technology that automates and simplifies monitoring your data governance efforts.

For instance, you could use a centralized dashboard that:

  • Automates reporting
  • Displays who the data owners are and tag them or ask questions
  • Traces lineage to verify the origins of data sets
  • Maintains a business glossary to add context to your data

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