Your organisation is only as good as its people… and its data. According to the 2020 State of Data Governance and Automation report, 70% of respondents spend 10 hours or more weekly on data-related activities that are time-consuming. The most time-consuming culprit is having to search for data. Data governance is an all-encompassing approach to dealing with data securely in order to maximse its value and optimise your team’s time.
The data governance process involves several steps and people to be done properly. Here, we will share how technology can help you master data governance and make the most out of your organisation’s data.
Coming Up
2. Why is Data Governance Important?
3. What are the Goals of Data Governance?
4. What are the Benefits of Data Governance?
5. Who is Responsible for Data Governance?
6. What is the Data Governance Framework?
7. How to Implement Data Governance?
8. How Can Tools Help with Data Governance?
9. What are the Challenges of Data Governance?
10. What are the Pillars of Data Governance?
11. What are Best Practices for Data Governance?
12. Data Management Software and Data Governance
13. Data Management Software Features
14. How to Choose Data Management Software
15. Best Data Management Software
16. How to Manage Compliance Risk
18. What are the Types of Compliance Risk?
19. How Automation Can Reduce Compliance Risk
20. What are the Benefits of Compliance Reporting and Why Is It Important?
What is Data Governance?
Data governance is the practices, processes, and tools used to manage the availability, security, and validity of data across its entire lifecycle. Data governance includes:
- Data quality
- Meta-data
- Documents and content
- Data interoperability
- Data security
- Data storage and operations
- Data architecture
- Data modeling and design
Data governance is ultimately a program and approach that organizations enact to define how they will deal with and use data to the best of their abilities. The process begins by deeply understanding the usage and benefit of data within your business and then expands to how it is collected, stored, transformed, organised, and utilised.
Why is Data Governance Important?
Data governance should be of paramount concern to an organisation of any size for a multitude of reasons. In many cases, an organisation may have a specific defined approach to data within a department.
Data governance broadens the approach to be systematic and organisation-wide. This means that it becomes a function for internal control, transparency, and collaboration.
Data governance makes it possible to:
- Scale the IT landscape across the organisation and standardise processes and data
- Create uniform data that can benefit business decision-making
- Boosted efficiency by being able to repeat processes and reuse data
- Provide better quality data and more confidence
- Reduce compliance risk
- Achieve better data security and protection
- Increase transparency and collaboration between personnel and departments
What are the Goals of Data Governance?
A business is only as good as its people, data, and inherently, its decisions. Decisions are data-backed for a reason–the proof is in the numbers. However, when data exists in silos across an organisation, then decision-making gets messy and inaccurate.
At the heart of its purpose, data governance ensures that data is cohesive and accessible to those who need it, when they need it. Furthermore, not only is the data accessible, but it is also accurate. Through data governance, organisations can create policies and processes by which data is collected, organised, and used. This helps to reduce data errors.
With better data quality, your organisation naturally reduces its risk. Using data automation solutions, your data governance program is seamlessly integrated within your business, reducing errors, increasing oversight and decreasing data management costs.
What are the Benefits of Data Governance?
With a data governance plan in place, business leaders have the information they need to make better decisions, all the while maintaining confidence that their data is secure. Instead of solely focusing on security and choices around singular applications or business units, data governance will scale with a business because it’s like a blueprint for dealing with data.
Across all departments, your team will benefit. For example:
- Sales and marketing: Sales and marketing teams can trust their campaigns and action plans because they will be equipped with quality data and accurate customer information.
- Production: With a data governance plan, you can remove manual work and leverage automation solutions.
- Finance: Finance teams provide valuable insight for every department. Data governance ensures that reporting can be done in a timely and reliable manner. Additionally, finance departments can achieve finance transformation and serve as strategic partners within the business when they have consistent and proper access to valuable data.
- Legal: Data governance is a surefire way to adhere to regulations and minimise compliance risk.
- Management: Data governance is away for managers and executives to have constant oversight and monitoring into their business’ processes, data collection, and usage. This makes it easy to understand the market opportunities and business’ operations.
Who is Responsible for Data Governance?
Since data governance is about the data that everyone within an organisation uses, it will involve your entire team. That being said, these are the common stakeholders involved in designing and maintaining a data governance policy:
- Chief data officer: Given the rise of data, many companies are choosing to hire chief data officers (CDO). They lead the data governance process.
- Data owners: Data owners exist within various departments. They are directly responsible for the state of data. To exemplify, your finance department should have its own Data Owner.
- Data custodians: Data custodians may be hired to help maintain data.
- Data stewards: Data stewards ensure that data policies are upheld on a daily basis. They converse with data owners to review each department’s data processes and usage. They are also responsible for training new hires on the data governance policies. Think of them as your data champions.
- Data governance committee: You can also create a data governance committee that sets policies around data and reviews issues. The committee is led by the chief data officer.
This team is aided by data analysts, compliance specialists, data strategists, and data architects. However, not every business is equipped to hire or afford all of these positions. Instead, you can leverage a data automation solution that will help you to define, roll out, standardise, utilise, and monitor data with little to no human intervention or coding required.
What is the Data Governance Framework?
According to the Data Governance Institute, the data governance framework involves the following 5 W’s:
- Who: This involves the people that create, collect, transform, and use data. From the CDOs to data stewards and employees, each person has their own list of responsibilities in reference to data. Additionally, data automation solutions can be implemented to reduce the stress and burden of these responsibilities off the shoulder of your team members.
- What: Of course, the data is the what. But, it goes deeper than that. It’s all about defining and understanding the type of data your business needs to collect and the purpose for doing so.
- When: What are your data access rights and timelines? Consider the regulations that you must comply to in order to determine what makes the most sense and will reduce your risks the most.
- Where: Many organisations struggle to securely store their data and centralise it. A data automation software solution like SolveXia makes this easy as it provides a centralised, accessible, and cloud-based location to connect all your data.
- Why: Your organisation’s “why,” or reason for collecting and using the data you do, should be communicated to every individual within your business. This allows your team to be involved and understand the bigger picture so goals are aligned.
How to Implement Data Governance?
To deploy data governance within your business, you can start with your “who.” Decide who will be involved and responsible for oversight. Then, work your way into the other details like deciding what data to collect, why, and where you’ll store it. With the structure in place, you continue to develop rules and processes that will adhere to regulations both internally and externally.
It’s useful to document and store where data comes from and how it’s protected. It’s also a good idea to create a plan of action if something goes wrong. You can do this by assessing potential risks, like security breaches, for example.
To cover all these bases, it is most advisable to choose a tool that can help you with data governance (more on this next).
How Can Tools Help with Data Governance?
Data governance tools make it easier to develop and maintain your data governance plans.
The best type of tools are scalable and can integrate into your existing toolstack. Furthermore, cloud-based platforms are beneficial as they lessen your cost when compared with on-premise solutions and allow your team to have quick access to the information they need.
Data governance tools should provide you with the ability to:
- Collect data: Not only should the tool be able to capture data, but it should be able to discover, profile, and automatically detect personal pieces of data.
- Monitor data: The tool can actively review data to ensure it’s up-to-date.
- Improve data: The tool should be able to validate data, cleanse it, and enrich it.
- Document data: For the purpose of compliance, accessibility, interoperability, and searchability.
- Use data: The tool should aid your team and make it easier for your employees to do what they have to.
What are the Challenges of Data Governance?
When it comes to implementing data governance, some organisations and stakeholders may face challenges. The most commonly noted challenges include:
Buy-in:
The first step of creating a successful data governance process will involve monetary investment, time, and the understanding and acceptance on behalf of your team.
This means that you must be able to prove its business value in order to bring it into your business. Since data is quantifiable, and the errors from poor data governance generally are too, it’s a good place to start to showcase the current inefficiencies and how data governance and tools can help.
Flexibility:
Data governance approaches don’t change on a daily basis, nor should they have to. However, business environments, needs, and situations do.
For this reason, it’s important to develop data governance that is scalable and adaptable. The challenge here is being able to balance its standardisation with the ability to be flexible, too.
Change management:
Data governance may necessitate change management and an open-minded corporate culture. This could be on the basis of having to assign responsibilities, for example. As such, it’s important to be transparent, communicative, and award the little wins.
What are the Pillars of Data Governance?
Data governance involves other aspects of the data management process. This involves:
Data quality:
A key to data governance is data quality. Having good data means having data that is complete, consistent, and accurate. To achieve this, data scrubbing and data cleansing must take place, which helps to remove duplicate data, fix errors, and ensures that data is able to be neatly organised.
Master data management:
Master data management (MDM) provides a way to define master data. This means that across different systems, data can be defined and consistent. While some departments may be more resistant to master data management because of the way data is stored, combining MDM with data governance can maximise results.
One easy method to ensure master data management and the optimal use of data is to implement an automation solution like SolveXia that can pull unstructured and structured data from various systems into its centralised system.
Data stewardship:
Data stewards hold a lot of responsibility when it comes to data governance. They oversee data quality and security. Data stewards are typically individuals with immense technical acumen and the ability to work alongside analysts and data management professionals.
At the same time, they can bridge the gap between technical teams and business units. In the same vein, automation solutions can provide aid in these areas. For example, the solution can automate processes using data without the need to code.
To transform the data into insights, real-time dashboards and reports are made accessible so that business leaders can understand what they need to know.
What are Best Practices for Data Governance?
We’ve compiled some best practices to create a successful data governance program. Take a look:
- Begin by setting measurable goals. When goals are achieved, take the time to celebrate and recognize the wins, no matter how big or small.
- Make ownership and accountability a priority and clearly communicate them to those being held responsible.
- Take the time to explain data governance benefits to stakeholders in a way that they can understand what’s happening (i.e. business context).
- Map out your tools, processes, and architecture so that your data governance framework is clearly defined. Your entire team, along with any IT staff, should understand where the data governance tools come into play.
- Identify what data you need and the purpose of collecting said data.
- Create control mechanisms and measurements. You can define measurements and pull reports to maintain oversight.
- Identify business use cases for where data governance will provide results.
- Continue to communicate with your team and stakeholders to showcase how data governance is benefitting the business.
- Remember that data governance doesn’t end. It’s a practice. Consider it like this - it’s not a crash diet, it’s a lifestyle.
Data Management Software and Data Governance
Even without an IT team, you can ensure that your data is properly managed and governed. Data management software systems minimise human errors and make it possible for data to be accessible and accurate.
Data Management Software Features
The best data management software features include:
- Data governance: the ability to display where and how data has been modified or updated.
- Data quality: these systems help to remove duplicates and fill in missing gaps in data.
- Analytics: some (but not all) of data management software systems will provide the ability for analytics and forecasting.
- Security: a large part of data management is securing data. With methods like encryption, the security aspect will help to prevent breaches and minimise compliance risk.
How to Choose Data Management Software
There are many data management software systems to research and choose from. Some functionalities you should require are:
- The ability to model and represent data
- Data cleansing to remove redundancies
- The capability to link data to the modelling method
- Real-time data visualisations in dashboards and reports so that you can utilise data from various systems and have a cohesive view of everything
Best Data Management Software
We’ve reviewed some choices for data management software and deduced the following:
SolveXia
For human analytical automation, SolveXia is a no brainer. The tool helps with data management and provides a way to augment human capabilities to minimise errors and maximise time. The tool is able to scale and combine data from existing sources.
This synchronised data can be used to automate processes and reports. It provides the ability to conduct: trend analysis, aggregate data, perform predictive modelling, supply visualisations, and more.
Oracle
For data management, Oracle is a great option. However, it does require training. With the ability to support large databases, the tool can process data quickly and securely. Oracle can migrate data, replicate data, and conduct performance analysis.
Alteryx
Alteryx is a great choice for low-value back-office tasks that don’t require human intervention because it utilises robotic process automation. Users can visually review predictive analytics and monitor business processes.
How to Manage Compliance Risk
Data governance helps to minimise and manage compliance risk. Without data security or governance, your business runs the risk of breaches and hacks, among other potential downfalls.
What is Compliance Risk?
Compliance risk refers to the potential legal and financial consequences of breaking regulations or laws. Across industries, laws exist to protect customers and businesses. When laws and regulations are not upheld, businesses risk their reputation and finances.
What are the Types of Compliance Risk?
Data grows exponentially daily. Protecting data is just one aspect of compliance risk. The different types of compliance risk include:
- Data protection
- Corruption
- Quality
- Market risk
How Automation Can Reduce Compliance Risk
Many businesses choose to hire a compliance officer to cover their bases when it comes to regulations and legalities. However, with or without a compliance risk officer, you can manage this crucial aspect of business by leveraging automation tools.
Human analytical automation tools reduce compliance risk by:
- Automating reports - so it’s easy to ensure that regulations are being upheld
- Audit trails - so third parties and internal stakeholders can review processes and control data
- Data security - so that breaches and hacks are minimised
- Reduce human errors - by automating processes and data entry which can become unintentionally detrimental and costly
- Streamline workflows - so that deadlines are never missed and bottlenecks are prevented
What are the Benefits of Compliance Reporting and Why Is It Important?
In order to ensure that your organisation is in compliance, you can run compliance reports. Compliance reporting is a way to compile the ways in which a company collects, stores, controls, uses, and shares data. This makes it easy for internal and external stakeholders, managers, executives, and auditors to review the status of data within a business and see that laws are being followed.
A chief compliance officer (CCO) may be tasked with creating compliance reports. Automated solutions remove the hassle of doing so because business processes can be easily defined, mapped, run, and monitored. Should there be anything out of the ordinary taking place, a business can rectify and reconfigure automated processes on the fly to avoid the risk of noncompliance.
Wrap Up
Data governance and the various data governance roles make for better business. Data governance is a crucial and necessary aspect of running any type of business optimally and being able to reduce risk associated with data. The chances are that your business collects data on a daily basis. If you’re not clearly stating what data to collect and how/why it will be used, then you are wasting time and money while exposing yourself to risk.
Through data governance practices and automation solutions, you can make the most out of data to better serve your customers, employees, and stakeholders.
