In today’s dynamic and ever-changing organisational environment, data governance is a pressing need. Businesses today collect enormous amounts of data from several sources while data governance aids in risk management, value maximisation, and cost reduction of the data accumulated.
Data governance, in a nutshell, is the activity of being aware of where your data is, how it is being used, and whether or not it is sufficiently safeguarded. Data integrity, consistency, and proper handling are all guaranteed by effective data governance.
Before the appropriate software can be implemented, the company, its organisational structure, processes, and the roles that need to be specified should be taken into account when it comes to data governance.
Signs of a failed Data Governance Program
Various people within the same organisation have different definitions of the same terminology.
The majority of businesses use a tonne of jargon and language that might signify various things to different people. Everything is highly subjective, and this is typically due to the culture of an organisation. The meaning of different terminology might change depending on how they are used within organisations. And that’s okay, but you should still use caution. Data governance is time-consuming and requires a lot of work, especially in the beginning. It makes sense that people would want to speed up this process.
Inactive stakeholders and a limited budget
The absence of managerial support is another factor in the failure of many data governance initiatives. An effort will nearly never be successful if senior management does not recognise the advantages of data governance and only considers the expenses involved.
First, there is a chance that the necessary procedures won’t be carried out properly. Additionally, due to costs, important changes might not be made or the programme might need to be terminated early.
Because of the legislation that supports it, such as the GDPR, it is now simpler than ever to find the funding required for a first data governance programme. However, it is essential that management also makes enough long-term resources available to continuously fund all of the roles and responsibilities necessary for effective data governance.
If your stakeholders aren’t willing to back up their claims with deeds, this suggests that the initiative isn’t being taken seriously enough and that its worth isn’t recognised.
Data Governance is only being implemented because of regulations
It is quite tempting for organisations to consider doing the bare minimum to appease the regulator if they are under pressure to implement data governance. This is a serious error because, over time, these organisations wind up working harder than they would have if they had adopted data governance correctly in the first place. Additionally, they pass on all the business advantages that come from enhancing their data management procedures.
The traditional tick-box method of data governance is task-focused and totally disregards the people involved. They provide a list of the tasks that must be completed and issue warnings if the tasks are not finished. As a result, people perform their tasks out of obligation and fail to recognise the true value of their work.
As a result, it will be challenging to implement your data governance system across your organisation, and you will always be pursuing individuals to ensure that they are abiding by the rules.
Regulators have a history of changing the goal posts, so if you haven’t integrated data governance into your organisation, you’ll probably have to start over every time they alter the rules and update the checklist, which means using the new checklist.
No Data Quality issues being reported
If data users aren’t reporting data quality issues, this means that either they are unaware of your process to investigate and fix issues, they don’t believe you will be able to change anything (possibly due to years of no one being interested in improving data), or they may not realise that the manual workarounds they must perform on a daily, weekly, or monthly basis are due to poor data quality, and that everything could be simplified and improved if the underlying data were of higher quality.
Whatever the cause, communication is the key. Additionally, any data governance strategy will undoubtedly fail if you don’t engage with your data users.
It is not discussed outside of IT
Getting stakeholders to take charge of data governance projects and take ownership of their data is essential for its success. It is pretty typical for IT to be in charge of the data governance programme when I conduct a health check on data governance for businesses that are having problems.
Always with the finest of intentions, this is done. Even though IT does not actually own the data, they are often the first in an organisation to recognise the need for appropriate data governance since they are aware of the consequences of improper data management.
Due to a misconception that exists between the infrastructure and the data, businesses frequently delegate data governance to IT. It may make sense to give IT control of the data governance endeavour if you work for a company that still thinks IT controls the data.
An IT-led data governance strategy, however, may run into difficulties. An IT-led data governance programme makes it more challenging for the company to take ownership of its data, which is a prerequisite for true data governance to take place.
Building a fail-safe Data Governance Program
Assess the success of your governance programme
Data governance is concerned with how decisions are made, not how those decisions turn out. It’s also true that typical corporate performance metrics don’t necessarily apply. The number of people covered by the programme — those assigned specific tasks, trained in processes, or made aware of policies; the number of data sources that have a related governance policy defined and applied to make operational, tactical, or strategic decisions; and observed improvements in the program’s effectiveness — are among the metrics that can help track the success of a governance programme and demonstrate that the organisation is better informed, resilient, and accountable.
Assemble a virtual team of data professionals for compliance
Many of us work in industries with strict regulations, such as the public sector, the medical field, and the financial industry. Though compliance cannot be ensured, it is essential to build trustworthiness and uniformity. A virtual staff with a focus on data policy can keep track of compliance challenges.
Data practitioners, such as database architects, software engineers, and business analysts, who deal directly with the data sources used by the governance programme but do not report to a more official compliance department, should make up the team. The team should regularly review the laws that are relevant to the governance programme, decide where to strengthen or expand the program’s regulations, and keep an eye out for occurrences, problems, and advancement.
Good governance concepts include preparing the way for compliance without obstructing corporate activities. A governance programme that takes compliance seriously lightens the workload and reduces stress for other employees.
Close to the source, protect your data
Today’s security industry is very specialized – the sophistication of threats is increasing. To protect corporate systems from outside attacks, one needs a full-time job. In a large, dynamic firm, it could be challenging to keep up with access rules and permissions.
Effective collaboration between the teams in charge of data governance and security is essential. Data access regulations should be adhered to as closely as feasible to the original data, according to the governance team.
Applying security rules shouldn’t be dependent on client tools like business intelligence or data visualisation systems. By the time a BI user views the data, it may have already passed across open, unprotected channels. Security for BI shouldn’t be regarded as a mission-critical function, despite being a useful feature.
Don’t put your trust in data privacy protections
With good reason, consumers throughout the world are becoming more concerned about data privacy and don’t think businesses have their best interests at heart. A data governance programme helps increase client trust in the company’s business practices.
Put policies in place that enforce preferences at all organisational levels. Some regulations may be applied by code or other technological means.
Consider the secondary advantages of sound Data Governance
A well-run system facilitates effective reuse of previously developed analytics and reports and enhances access to data. Policies specify in advance what information is appropriate for a role and may be confidently provided. Ad hoc requests for data access that are disruptive to IT and prone to error, including the compliance risk of over-provisioning permissions just to get the job done, are common in poorly controlled systems.
A choice based on well-governed data is likely to be more collaborative, better understood, and have wider support, even though this isn’t the core purpose of data governance. When teams collaborate to create policies rather than assembling them along departmental lines, confidence in the process creates confidence in the conclusion.
Ensure that you are open, aware, communicative, and trained
A number of these procedures are built upon an organization-wide awareness of the data governance procedure. If data users are unaware of the programme, data governance cannot be successful.
- Be transparent about the programme, its objectives, and its performance metrics. Share the measurements, describe the processes, and publish the governance approach.
- All staff onboarding procedures ought to include a section on programme awareness. Work with those teams and HR to get data governance on the same track as compliance training that already exists for topics like harassment issues.
- Include pertinent portions of the governance plan and how it relates to the tools and platforms under consideration in all technical training connected to data, such as the implementation of BI tools.
- The significance of data quality, the laws around it, and how to find and reuse authorised data sources must all be covered in training. Particularly data analysts and report writers shouldn’t feel as though policy is being demanded at the expense of adaptability. Instead, they ought to view controlled data as a resource that creates new opportunities for confidently observing the rules.
- To demonstrate that the data has been correctly governed, a “governance assured” seal of approval can be placed on dashboards, reports, and other artefacts.
Data governance is a challenging process, particularly when you initially begin. On the other hand, a well-governed data infrastructure that follows these best practices will be advantageous to business units, IT, clients, and business partners.
About Artha Solutions
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