Bad Data Governance Is Risky
Lack of effective data governance is a security concern for 2 reasons: outside security risks associated with dirty, unstructured data, and regulatory compliance issues.
Bad data, and badly structured data poses a security risk for the simple reason that if you have dirty, unstructured data clogging your database, how can you quickly tell when something goes wrong and how can you efficiently monitor what data is at risk? Good data governance tools and practices make it easier to monitor what is happening across your database, and will make it easier to see what areas may be at risk.
Regulatory compliance and data governance is becoming a hotter topic with each passing day. As people continue to understand the importance of their personal data, governments are beginning to take the ways in which companies store, protect, and use their customers data extremely seriously.
Take GDPR for instance. This regulation, set to come into effect in early 2018, gives EU residents more control over their personal information, including the famous right to be forgotten which enables an EU resident to request that all of their data be deleted from a business database . With a messy, un-governed data swamp it may prove impossible to guarantee that all data regarding a particular individual is deleted when requested. This opens your company to great risk and potentially draconian fines.
Challenge : Data Governance Practices And Data Privacy
One of the benefits of the data governance framework is that across teams, high-quality data is available. However, if not properly managed, this universal access to information could lead to data privacy issues.
Solution: Strict ownership and accountability of data.
Data governance systems should segregate different levels of data with appropriate access rights. For example, the medical records of the customers in healthcare should be considered sensitive data. An organization that utilizes the customer data through a data governance system should properly disclose to their customers what kind of data they are storing and using. There shouldnt be any secondary usage of data. Data that is collected for one purpose should not be used for an entirely different purpose.
The Business Need For A Data Governance Framework
The collapse of companies like Enron, Adelphia and others led the US federal government to establish rules to improve the accuracy and reliability of corporate information. Data governance was a key component of these efforts, as the rules put in place by the Sarbanes-Oxley Act and other regulations required executives to know and be personally responsible for the data that drove their businesses.
What the data world lacked until this time was a true, unassailable driver for governing this data. Sure, some forward-thinking organizations like the manufacturer I spoke to viewed their data as an asset that required care and maintenance. But, regulations like Sarbanes-Oxley, Basel III, Dodd-Frank and others required large organizations to be smarter about their business practices.
Today, it’s possible to tie data governance efforts to a variety of corporate drivers. This does two things for your data governance framework. First, it gives you the necessary buy-in from executives and managers who want to make sure that any initiative maps to a priority item. Second, by tying data governance to a larger organizational goal, you can prove value throughout the process and get more funding and support in the future.
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How To Implement Data Governance In Your Company
The first step in implementing data governance is to identify the sectors that generate the most data, starting with human resources.
In fact, practically all sectors of your company will generate some type of data, but we highlight HR because it is your employees, distributed in different areas of the company, who will deal with different types of customer and partner data, but also because it is in the human resources sector that there is the greatest concentration of personal data.
So, if you start with this sector, the actions needed to create the conditions for structuring data governance will certainly become clearer.
From there, you can target your human resource planning according to your data usage needs.
Areas such as sales, marketing and customer service certainly deal a lot with customer data. But they are not the only ones.
It is important to identify how the company’s areas use the data specifically, so that each employee receives the necessary training according to the requirements of the LGPD.
With human resource planning, it is possible to develop the means of access necessary for adequate access, editing and sharing of information.
Before that, however, you need to make a plan that includes analyzing trends in data governance and the behavior of your competitors.
Thus, you identify what are the challenges to be faced and what benefits will be achieved.
This is when teams must be involved. Without this involvement the challenges will not be overcome.
The Importance Of Good Data Governance In Healthcare
As the healthcare world becomes increasingly digitized, providers and other medical organizations rely more and more on data to drive their decision-making. As a result, data governance in healthcare is a particular and growing concern in the industry, as information becomes an essential tool for business development, treatment planning and more.
The onus is now on organizations to ensure proper handling and management of this critical data to maintain patient and customer privacy while also enabling full leverage of the incredible power it can bring to corporate users.
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Importance Of Data Governance
Data governance is a fundamental part of any organization that works with big dataBig Data in FinanceBig data in finance refers to large, diverse and complex sets of data that help provide solutions to long-standing business challenges and results in consistent, common business processes and responsibilities across the map. It highlights the type of data that needs to be carefully controlled through the organizations data governance strategy. It sets clear rules relating to the roles of individuals with access or who are responsible for data, and the rules must be agreed upon across different departments of the organization.
For example, maintaining the privacy of patient information and health records is especially important in the healthcare industry. For organizations, such as hospitals or individual doctors offices, it is certainly necessary to manage patient data securely as it flows throughout the business.
Benefits And Goals Of Data Governance
What does this mean for my business? What exactly are the benefits of implementing a robust data governance strategy?
With bad data, its impossible to make the right decisions at the right time. Collecting the data isnt enough by itself you need data governance to bring it all together.
This unlocks your business to use data more effectively. Here are some possible use cases for data governance.
- Consistently make confident decisions based on reliable and relevant data for the specific purpose and end-user within your business.
- Comply with data protection legislation and other regulatory requirements by documenting the permissions and usage of data from collection through to use.
- Built a robust data security system in which data ownership and responsibilities are clear for all involved.
- Utilize data to improve profits. This can be simply monetizing the data but can be used to drive revenue in other, less direct ways.
- Build a robust data distribution solution between internal and external data processors.
- Ensure that data is in the right format and as clean as possible before use, to save time performing these tasks at the point of use.
- Build a standardized data structure to ensure the same data is suitable for different tasks in different areas of your organization.
There are many more benefits to implementing a data governance strategy for your business.
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Why We Need A Data Exchange Board To Improve The Eu Data Governance Act
Dec 9, 2020 | News
In collaboration with other organizations of the Data Sovereignty Now movement aNewGovernance, iSHAREworks, INNOPAY, Meeco.me, MyData Global, Sitra and The Chain Never Stops IDSA has written a position paper that explains why the recently published proposal for the EU Data Governance Act is a very good step forward. It also outlines recommendations to further accelerate the development of a governance framework that will provide true control over personal, business and public data.
Role Of Data Governance
The main role of data governance is to ensure that the data quality remains high throughout the complete lifecycle of the data and the controls which are implemented are in line with the organizations business objectives. It is important that information is used both effectively and efficiently and is in line with the companys intentions. Data governance identifies who can take what action, as a result of what data, in which situations, and using what methods.
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What Is Big Data Governance
Before proceeding, you must know What is Big Data? Big Data Governance is the process and management of data availability, usability, integrity, and security of data used in an enterprise. It includes all the steps from storing the data to secure it from any mishap. It is not just only about technology. Responsible for the particular data asset along with the technology.
It is also used in an organization at a maturity level to make sure critical and vital data is managed and protected. This gives clarity of the information which helps in defining the Decision-Making processes around data. It is a strategic, long-term process. It is essential for Finance and Insurance organizations especially those that have regulatory compliance. These organizations are required to have formal data management processes to govern data throughout its life cycle. Data governance can also enable the authorization on the based of classified data to particular users.
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Strategic Data Management Board
This board is the central decision-making board in data governance that aligns and approves the data management strategy, annual objectives and budget. It also tracks the progress of the data management activities and resolves issues that had to be escalated. Oftentimes, the board consists of data definition owners from the business units and managers of the support functions as well as the Head of Data Management / Chief Data Officer. It is possible that these roles already meet in other boards or committees. If so, it should be considered whether an additional strategic data management board is really needed or whether the topics to be discussed can be integrated into the other boards or committees.
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Understanding The Value Of Data
Often there is a lack of clarity on ownership, access, management, and usage, which means that data is stored in systems that may not be accurate. This can result in issues of ROT and general mismanagement, which has an adverse compound effect. Technology investments wont improve the quality and value of present data as data cannot govern itself and must be adequately understood for effective utilization.
Set Up A Data Governance Center Of Excellence
In many of the analytic projects I have been involved in, whether big or small, you have to guide those using the data solution you create.
A center of excellence centralizes resources, guidance, and up-to-date assistance for those using data in your organization. The main outcomes from this are to maintain consistency of delivering high-quality data solutions and to make sure time is not wasted reinventing the wheel with each project.
Resource: Establish a Center of Excellence Power BI This link provides more detail on a Center of Excellence example from the Power BI side of the business.
The following 7 items should be key tenants for your Center of Excellence.
1. Provide Data Governance Principles
This documents your organizations overall approach to data how you collect, what you should collect, how you store it, how long you keep it, and who should have access to it. Having these principles front and center also serve as a reminder to the teams.
2. All Actions and Data Must be Auditable
You need to be able to report and monitor your progress by tracking various metrics. Not only the current status of your data but being able to track it over time. For example, you need to be able to audit based on items in your governance program. Access to usage reports on various data sources, seeing various fields, and sharing reports.
3. People must have Accountability
4. Data Formula and Calculations
5. Data Architectures
6. Data Security & Privacy Policies
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Best Practices For Data Governance
Every organization is different when it comes to data governance. However, we have compiled some essential tips that will apply to some.
- Keep it simple always take a step back and ask yourself if you are overcomplicating things. Data governance needs to meet your goals. To do this, you may need a simpler solution, or it might be easier to change to a data solution that has governance baked in.
- When it comes to your data governance goals, you need to choose clear and measurable targets. Make sure you celebrate when you meet these and understand why it is when you dont.
- Clearly define the roles and responsibilities of everyone who is involved with the data governance strategy. Extend this to everyone within the organization who uses data at any point.
- Internal documentation and definitions of critical data terms are hugely important for data governance. Try and bake this into your employee handbook and make sure its easy to access and makes sense.
- Build a business case for data governance. Sometimes it can be easy to lose track of why you need a data governance solution in the first place. Linking this to clear business goals is a great way to keep data governance relevant in everything that you do as a business.
- Educate key stakeholders and get them to buy into your data governance project.
This should be more than enough to get started with your data governance strategy. Remember, you can use Wult to build powerful, governance ready, data solutions for your business.
If You Dont Know Why It Can Be Easy To Get Side
I’ve seen people make the mistake of spouting things like, oh we’re doing it because it’s best practice or we work in a regulated industry and it’s required, but if you do it for that reason, you’re likely only to do the bare minimum to tick the boxes required by your regulator and you are going to miss out on most of the benefits that are to be had from implementing Data Governance.
People will often spout generic benefits like oh there will be efficiencies or there will be better opportunities if we do data governance, but they can’t explain why when challenged and the consequence of this is that when you’re meeting your stakeholders at the start of a data governance initiative – particularly your senior ones – they want to be able to know what’s in it for me and if you can’t answer that in a way that they really are interested in and benefits them, they’re just not going to be interested.
All this means you are going to really struggle to get stakeholders to buy into your data governance initiative and ultimately that means that you’re not going to get the support you need for it or the funding and everything you’ve done to date is just going to be wasted effort.
And then finally, I would go and search for your data quality horror stories. These are instances where things have gone wrong because either data is missing, or you’ve got poor quality data and things have gone wrong as a result.
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Why Is It Important
Over the past 10 years, companies have begun to move beyond basic reporting to using data to drive competitive advantage. To rise above the competitors in their space, a companys data needs to be well understood, accurate, and complete. Companies need a unified organizational effort and strong data governance in order to achieve these goals.
Strong data governance practices improve data accessibility for users in your organization. With data governance, users consume data in an actionable format, and various departments such as product teams, marketing, and customer support are empowered to use the data to make crucial business decisions.
Without data governance, there is a substantial chance your organizations database or CRM contains flawed data. When data is inaccurate, users lose trust in the information they interact with daily. Trust is a key component of why data quality matters. When data consumers trust the data, the return on investment from your data increases because decision-makers can act confidently when drawing insights from the data.
Data governance increases the value of data to your organization the full potential of your data comes to life. Businesses go from working with data in a limited scope to using data to drive various use cases that bring real value to their team.
What Makes Up A Data Governance System
Data governance frameworks are complex structures. The organizational structure of a data governance program includes the regulations or policies implemented within an organization, such as company procedures or governmental regulations.
Next, it considers the goals or initiatives of the particular business. Since every organization is different, data governance programs will fluctuate despite the core similarities they have with one another.
Success measurement techniques, or milestones, will also be implemented in a data governance system.
This specification of measurement techniques can ensure the consistency of quality standards across an organization.
Another aspect of a data governance initiative is accountability. Strict data vigilance can provide insight as to specific areas of strength or weakness.
Data governance can also examine current business processes and find efficient means of automating aspects of them.
From an operational standpoint, data governance can help identify means of improving accuracy and consistency regarding workflow.
These types of insights can help businesses prioritize their resources and eliminate unnecessary waste.
TIBCO, the data science software leader, provides several helpful resources for business owners and students interested in data science methodology.