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It’s common for enterprises to run into challenges such as lack of data visibility, problems with data security, and low Data Quality. But despite the dangers of poor data ethics and management, many enterprises are failing to take the steps they need to ensure quality Data Governance.
Let’s break down some of today’s biggest Data Governance challenges and explore potential solutions for your organization.
Why Does Data Governance Matter?
Simply put, companies are now drowning in data and will be for the foreseeable future. Data is essentially digital gold – the more that you have, the better your enterprise can grow and the more reliably you can capture traffic and convert that traffic into customers.
But gathering data is just the start. After you collect data, you need to know how to manage and organize it to maximize its usefulness. This is doubly true for large enterprises that collect gigabytes upon gigabytes of data. The total data volume around the world is expected to exceed 175 trillion GB generated annually by 2025.
If you want your enterprise to succeed, you’re probably already collecting lots of data. But you need to know how to govern that data and manage it if you want to leverage it properly. Fail to do this, and you’ll have all the data you need to succeed but with no real purpose.
Data Governance Challenges on the Rise
Data collection and volume are surging, so it’s more important than ever to develop a Data Strategy as soon as possible. Good Data Governance will create a vital framework that will help you balance your needs for data collection and Data Management.
Let’s take a look at some of the most common Data Governance challenges you might soon face in your enterprise.
1. Limited Resources
Naturally, your organization may not appear to have the resources, including the budget or the manpower, to maintain an ongoing Data Governance program. You may have several priorities your team needs to juggle in addition to IT work, and you can’t simply funnel Data Governance responsibilities to your existing IT team.
Many organizations are struggling with the need for a Data Strategy and Data Governance efforts but didn’t plan to funnel resources to these needs beforehand. Don’t let this be you. Make sure to include plans for Data Governance when allocating your resources each year or quarter, and harness automation in your business processes to lighten the load on employees and get maximal value out of the data you collect.
2. Siloed Data
It’s also common for data to become increasingly siloed or segmented. This happens for a number of reasons, including:
- The rapid-fire pace of data collection
- The constant growth and turnover of new technologies
- New data sources
- Internal friction between teams or departments
- Evolving enterprise infrastructure
As your enterprise gathers more and more data, you must be careful not to let it become too siloed. If you do this, it’ll be difficult or impossible for you to analyze the data in connection with itself and draw meaningful conclusions from the information.
3. Lack of Leadership
On the personal side of things, many enterprises are struggling with data leadership – or lack thereof. Data Governance should be a top priority for three reasons:
- Your governance team needs someone to give them direction
- The governance leader can help develop internal policies everyone in your organization needs to follow
- Not everyone is data literate
The Data Governance officer you appoint should know how to break down concerns or ideas about Data Governance through Data Modeling, presentations, and more. In this way, the importance of Data Governance will remain at the forefront of your company’s objectives and won’t be misinterpreted as a waste of resources or time.
4. Poor Data Quality and Context
Too many enterprises waste their time and resources gathering data that doesn’t matter for their mission or their objectives. Indeed, a key part of Data Governance is ensuring that your company only acquires the data that it needs to grow and meet shareholder expectations.
To that end, you should invest in analysis tools and officers who can interpret the data you gather and help tailor your future data collection efforts. This extends to metadata as well, the information you have about data you gather.
For example, are your payment information collection practices ensuring PCI compliance to prevent business credit card fraud? Is your data properly anonymized? If you don’t have the right contextual data, you won’t be able to determine whether PCI compliance is the norm for your company or something you need to work on.
5. Lack of Data Control
Another of the most common Data Governance challenges is a lack of control over enterprise data. If you don’t control your data, it could result in noncompliance, for example, if employees access data when they shouldn’t, leading to legal injunctions. This opens you up to security breaches and legal concerns due under GDPR, CCPA, and other recent legislation.
Many enterprise leaders find that they are absolutely drowning in data and just need a place to put it. They don’t worry about who’s in charge of data storage or retrieval, just that it can be retrieved in the first place.
Funneling your data storage concerns to the cloud can work, as the cloud is fairly secure compared to traditional data storage alternatives. That said, a core part of Data Governance is controlling the data and knowing where everything is stored, organized, and who’s in charge of regulating it for the foreseeable future.
Don’t let cloud storage distract from security processes and lull you into a false sense of security. To that end, investing in a data catalog or a cataloging governance officer is a good idea if you want your enterprise to be compliant with ongoing consumer data regulations and make sure that your own enterprise’s data isn’t compromised or at risk.
The Bottom Line
Data Governance is more important than ever, especially as new challenges and risks become more apparent to enterprise executives. Make sure that your organization is ready for the upcoming challenges by prioritizing Data Governance in your storage and management now rather than later.