Data Architecture With Data Governance: A Proactive Approach
Data Architecture is the physical implementation of the Business Strategy, said Nigel Turner, Principal Consultant in E.M.E.A. at Global Data Strategy, Ltd., speaking at the DATAVERSITY® Enterprise Data Governance Online Conference. Its a key part of the whole continuum that you need to build within an organization to manage data effectively, and Data Governance forms an important bridge between those strategies and the real-world implementation of them in the business.
Data Architecture: What isit?
The DAMA DMBoK2 says that Data Architecture defines the blueprint for managing data assets by aligning with organizational strategy to establish strategic data requirements and designs to meet these requirements. Turner pointed out three key parts of this definition, the first being the word blueprint. What that implies is that any Data Architecture that doesnt have an implementation plan will probably remain on the shelf until the mists of eternity have risen.
The second key part is aligning with organizational strategy. Data Architecture must be directly connected to the goals of the business and how data supports those goals, he said. The third part is about establishing strategic data requirements. Because any effective Data Architecture must be forward-looking.
Citing a DATAVERSITY research report entitled Trends in Data Architecture, by Donna Burbank and Charles Roe, he noted the range of responses to the question: What is Data Architecture?
Components Of A Data Governance Framework
A data governance framework consists of the policies, rules, processes, organizational structures and technologies that are put in place as part of a governance program. It also spells out things such as a mission statement for the program, its goals and how its success will be measured, as well as decision-making responsibilities and accountability for the various functions that will be part of the program. An organization’s governance framework should be documented and shared internally to show how the program will work, so that’s clear to everyone involved upfront.
On the technology side, data governance software can be used to automate aspects of managing a governance program. While data governance tools aren’t a mandatory framework component, they support program and workflow management, collaboration, development of governance policies, process documentation, the creation of data catalogs and other functions. They can also be used in conjunction with data quality, metadata management and master data management tools.
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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Best Practices For Data Governance
Image source: The Data Science Community
There are a number of best practices that can be implemented in an organization to aid in data governance programs. Following them can help organizations to avoid some common challenges and pitfalls associated with data governance. These best practices include:
These five best practices can be extremely helpful in ensuring the viability of your data governance program.
Governance Of Data Innovation: Risks And Rewards For Business Key Takeaways From Our Discussion With The Uk Information Commissioners Office
1.Objectives and Mandate of Global Forces in Data Protection A Convergence: A key point of discussion was the recent convergence in objectives and mandate among global forces in data protection. Both the June 2021 G7 held at Carbis Bay, UK, and the 2019 G20 held in Tokyo had the same theme: to allow a free flow of data with trust. Worldwide, regulators are also converging around a need for data protection legislation, as evidenced by Chinas recent passing of its own data law: the Personal Information Protection Law . The discussion on convergence also highlighted the potential value in more international cooperation. The ICO believes that its current approach to data regulation, on a nation-by-nation basis, can only take data protection laws so far. To unlock the potential of data while maintaining public trust in how it is used requires a reimagining of data laws and the forging of an international solution a form of data Bretton Woods, whereby we rethink data protection in the way that Bretton Woods rethought global financial systems toward the end of World War II.
To access the recording from our recent discussion with the ICO, click here.
Thank you to Sidley Law Clerk Subhalakshmi Kumar for her significant contribution to this Update.
Attorney AdvertisingSidley Austin LLP, One South Dearborn, Chicago, IL 60603. +1 312 853 7000. Sidley and Sidley Austin refer to Sidley Austin LLP and affiliated partnerships, as explained at www.sidley.com/disclaimer.
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Data Governance Or Information Governance
I have come to realize that there is a lot of confusion between data governance and information governance. This has become more noticeable as I am helping organizations set up an information governance product discipline for managing information compliance in Microsoft 365 and other content services platforms.
Hence I decided to ask the experts in this short video and get their take on the definition, boundaries, and dependencies between the two disciplines.
I am hoping this will open up a healthy discussion as every organization has almost two parallel initiatives going on to govern data and information.
Data Governance Goals And Benefits
A key goal of data governance is to break down data silos in an organization. Such silos commonly build up when individual business units deploy separate transaction processing systems without centralized coordination or an enterprise data architecture. Data governance aims to harmonize the data in those systems through a collaborative process, with stakeholders from the various business units participating.
Another data governance goal is to ensure that data is used properly, both to avoid introducing data errors into systems and to block potential misuse of personal data about customers and other sensitive information. That can be accomplished by creating uniform policies on the use of data, along with procedures to monitor usage and enforce the policies on an ongoing basis. In addition, data governance can help to strike a balance between data collection practices and privacy mandates.
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Goals Of Data Governance
The goal is to establish the methods, set of responsibilities, and processes to standardize, integrate, protect, and store corporate data. According to BARC, an organizations key goals should be to:
- Minimize risks
- Improve internal and external communication
- Increase the value of data
- Facilitate the administration of the above
- Reduce costs
- Help to ensure the continued existence of the company through risk management and optimization
BARC notes that such programs always span the strategic, tactical, and operational levels in enterprises, and they must be treated as ongoing, iterative processes.
Overcoming The Challenges Of Scale Across Business Roles
Before any organization embarks on an overhaul of their information governance policies and procedures, its important to consider the challenges first. These can include:
- The complexity and diversity of todays enterprise technology stacks
- The rapid proliferation of data across all business roles and departments
- The new and emerging data privacy regulations at local, state, federal, and global levels
- The need to derive real-time insights from data to maintain competitive advantage
The above responsibilities apply in almost every business role and department. In enterprise environments, matters become exponentially more complex, especially when factoring in the rise of remote teams and multiple branches. Different departments use a wide range of cloud services. For example, marketing teams use on average 120 different services, while HR use around 100, and finance uses 51, according to one recent study. Since each of these services collects and stores information in a unique way, information governance must apply in every area of the organization.
Information Governance no longer belongs exclusively to legal, compliance, and information security teams. Its everyones responsibility. IG professionals need visibility across the full range of information-based services. Business leaders need to maintain complete audit trails of where their data lives and which controls are in place to protect it.
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Understand What Your Information Governance Looks Like Right Now
Governing this information is t’s more than just store everything!
A healthy system includes a documented plan for how decisions are made regarding your organizations data.
How is it acquired or created, stored, archived, or deleted, and how will it be used? And for a plan to be successful, how it ties back to enterprise goals and processes is important.
Want to test your information governance? See where you fit in below:
- We mostly govern our data based on industry regulations, and we dont have a single-source-of-truth for the majority of our data
- Each department controls their data silos without a central policy or plan
- Weve identified core information assets and integrate some data / metadata with a goal of structuring additional types of data
- We have an information governance program which provides quality data for creating better business outcomes
- Weve fully adopted EIM, all information is fully inventoried and focus more on the value of data than quality
Information governance is more than a policy or decision-making framework. Its ability to move an organization to the point where data priorities are based on business need versus IT or regulatory requirements is startlingly powerful. You must also consider how to actively enforce it.
How To Create A Robust Healthcare
Constructing a strong healthcare data governance system can seem like an intimidating task, but sticking to some best practice guidelines can help you get started.
The first step is to identify your business data objectives and create a plan around those goals. What types of data are you collecting, from whom, and how do you expect to use it? This information can help shape the governance system that youll need to manage your data.
Then select a team that knows both the specifics of your field and has a background in data governance. As mentioned, data managers deeply ingrained in the information they oversee can more nimbly and effectively manage that data by spotting irregularities and opportunities in real-time.
Its also important to let your experts develop their own management strategies. When the team creates its own robust processes for data collection, storage, analysis, and security, the result is a more specialized, efficient oversight system that fits within the overall data governance plan.
Once the strategy and processes are in place, its imperative to find technology to run it all that matches your data governance strategy and needs. At the very least, most healthcare organizations will need both data warehousing software and hardware along with data analysis software.
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What Is Information Governance And Why Is It So Important
Every digital interaction between businesses and their customers leaves an auditable trail of data. Sometimes, data is highly sensitive and needs security, privacy, and discovery controls in place. Other times, data has no value and is simply taking up space. Telling the difference between these types of data and knowing where it all lives is one of the biggest challenges organizations face today.
The truth is an overwhelming amount of data is ungoverned making it difficult to know what is of value and what is not. Not only does this mean that sensitive data could be compromised, but also that potentially useful data remains underutilized. Having a robust information governance plan is the solution to these problems. Lets get into what it is and why its important.
What Are Some Information And Data Governance Challenges
Data and information are the lifeblood of modern business. But the sheer amount and variety of them in need of information governance and data management? Those are growing at an exponential rate. Its become a Herculean task for business. Just a couple of the complexities they must deal with?
Coping with the Three Vs:
More companies are reliant on Big Data, which is defined by three key vectors volume, variety, and velocity. All of these are growing rapidly, and mismanaging them can have serious consequences.
As early as 2015, UK-based fraud prevention company Semafone an OnePoll revealed that the overwhelming majority of consumers would not do business with a company that had been breached, especially if it had failed to protect its customers financial data, such as credit card numbers.
- Over 86% percent of respondents were not at all likely or not very likely to do business with an enterprise suffering a data breach involving credit or debit card data.
Today, more employees, stakeholders, and customers in more locations than ever may want or require access to your files and data. Especially if youre a large or global enterprise. Many of them are now working remotely, on a variety of devices, so a company must both ensure access and maintain data security:
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Information Policies And Procedures
Best Practices For Managing Data Governance Initiatives
To the extent that data governance may impose strictures on how data is handled and used, it can become controversial in organizations. A common concern among IT and data management teams is that they’ll be seen as the “data police” by business users if they lead data governance programs. To promote user buy-in and avoid resistance to governance policies, experienced data governance managers and industry consultants recommend that programs be business-driven, with data owners involved and the governance committee making the decisions on standards, policies and rules.
“Only by agreeing to corporate-wide data governance with responsibility by business units will the foundations be laid for successful data management across the enterprise,” Hayler wrote in an article about the need to eliminate incompatible data silos.
Training and education on data governance is a necessary component of initiatives, particularly to familiarize business users and data analysts with data usage rules, privacy mandates and their responsibility for helping to keep data sets consistent. Ongoing communication with corporate executives, business managers and end users about the progress of a data governance program is also a must, via a combination of reports, email newsletters, workshops and other outreach methods.
In a report published in October 2019, Gartner analyst Saul Judah listed these seven foundations for successfully governing data and analytics applications:
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Use Metrics To Show Organizational Improvement
As Peter Drucker so famously said, If you cant measure it, you cant improve it. And, as W. Edwards Deming said, In God we trust, all others must bring data.
These two quotes sum it up.
You must be able to measure your performance. What metrics and goals do you have for information management? See if you can relate:
- We arent really tracking anything, and what we do measure is purely subjective and has little organizational value
- We invest very little in financial metrics but do use some basic stats to justify certain expenses
- The metrics we track are mainly related to tracking project efficiency they dont directly support overall business strategy
- We track distinct metrics for product quality, financial health, and risk, and tie this information to business value
- Intended business outcome is directly tied to information management related metrics
The right metrics for information and data governance must tie back to budgeting, return on investment, and supporting your companys top-line goals.
How will you show that information management improvements directly affect overall organizational performance?
Why Data Governance Is Essential To Success In Healthcare
Data governance is the unifying process that allows healthcare companies to take full control of the data they collect from their clients and patients, extracting the most significant benefit from this data while minimizing the inherent risks associated with holding individuals personal information.
With a team of experienced data governance professionals communicating with an organizations business development team, healthcare organizations can take their data analysis to the next level. They can do this by coming up with solutions and innovations that will keep them ahead of competitors while providing the highest quality of service to their patients.
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Data Governance Vs Data Management
Data governance is just one part of the overall discipline of data management, though an important one. Whereas data governance is about the roles, responsibilities, and processes for ensuring accountability for and ownership of data assets, DAMA defines data management as an overarching term that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data.
While data management has become a common term for the discipline, it is sometimes referred to as data resource management or enterprise information management . Gartner describes EIM as an integrative discipline for structuring, describing, and governing information assets across organizational and technical boundaries to improve efficiency, promote transparency, and enable business insight.