To better understand the role of data governance, we need to look at the context of data in 2021. Compared with 4.4 Zettabytes of information in 2015, the digital universe now consists of over 44 Zettabytes, meaning that since 2015 we have created more than 10x the amount of digital data that had existed before.
The amount of data that organizations now create, and therefore have to manage, has increased exponentially in recent years. This means that IT departments have their work cut out trying to keep on top of all the company’s data without mishaps.
For many, this has meant hiring more IT staff to take on the task. But manual data governance can be time consuming and carries the risk of human error, which can lead to costly consequences.
What is governance automation?
Automated data governance uses artificial intelligence (AI) to manage key standardized processes within an organization. This could be matching data from the cloud with legacy systems, ensuring compliance with industry data protection laws, or managing company file structures.
This approach is becoming more and more of a necessity for companies who are struggling to deal with the influx of information being created and stored on their servers. As the amount of data stored increases, so too does the risk of disaster, and storage costs begin to spiral.
Data governance automation reduces the risks associated with increasing information management. It also relieves some of the repetitive tasks associated with governance from the IT department’s workload, so they can spend their time on projects that add greater value to your organization.
The risks of poor data governance
Poor data governance can create numerous issues for organizations. It can affect anything from compliance with data laws to the day-to-day running of the business. The data risk that businesses face can be boiled down into three areas:
- Risks that arise from poor data security, which can lead to breaches and cyber-attacks
- The risk of accumulating low data health associated with poor data governance
- The risk of breaking compliance laws from poor management of data: weak processes for collecting, storing, and processing
These risks grow when companies exhibit the following issues:
Failure to manage and retire data
Without proper management, information is left to build, and soon there are more unprocessed data than your IT department can feasibly manage. It’s time-consuming and difficult to sort.
You also risk breaking data privacy laws if customer data is kept for longer than the required time. Organizations that fail to retire data in line with industry guidelines could face fines or further sanctions. This is up to 4% of annual turnover in some industries, but the damage to customer trust and loyalty is much larger.
Remaining on legacy systems
There are several reasons why companies remain with outdated and insecure legacy systems. It can be costly to buy new software, and if your on-premises system is currently working, there’s no point upgrading, right?
While these legacy systems might have industry compliance already built-in, many will be unsupported and require security patches to keep them running. This takes time, effort, and usually, a big chunk of IT’s budget to maintain.
This also makes accessing data much more difficult. Legacy systems feature outdated and sometimes buggy UI. It can affect the productivity and performance of employees who rely on the system to do their job. Due to their age, these systems tend to be more susceptible to cyber-attacks too.
Creating an automated governance strategy
To combat poor data governance, you need to build a strategy that ensures all your data is acquired, processed, stored, managed, and retired in accordance with industry standards.
To create a data governance strategy, you first need to define what you want to achieve.
- Do you want to make it easier to access data?
- Do you want to give leaders greater visibility and the ability to make better decisions?
- Are you looking to roll out stronger compliance protocols?
You should also map out your current data governance approach. To streamline your approach to tackling data risk, you first need visibility on where your network needs improvement. This can be done with the right governance automation solution which makes the automation process smoother and more efficient.
When you can see where your data governance strategy can be improved, it’s time to put in place automations that help to streamline processes. Consult with all teams on this, a full company approach is required to ensure that automations continue to work in the long run.
Cut data risk with smart governance automation software
As company data volume continues to soar, governance automation is rapidly changing from being a beneficial extra to a necessity. Organizations that fail to invest in their data governance strategies risk security breaches, increased downtime, and the inability to keep up with competitors.
Software like Nintex Promapp® helps companies to map out their data management process, see exactly where the weak points are, and build governance automation solutions to strengthen their approach.
Nintex K2 Cloud allows you to build low-code data workflows that can be scaled up with your growing business. No development experience is necessary, and you can bring together data from the cloud, and from your on-premises network to build logical solutions to governance problems.
Find out how Nintex can help you to build a data governance automation strategy to futureproof your business. Contact the team today.