Transparent and trustworthy data is critical for more than compliance.
It helps your business users make accurate and informed decisions. Trustworthy data also directly contributes to your organization’s ability to remain competitive and grow sustainably. Yet, 77% of IT leaders don’t completely trust their organization’s data for decision-making.
Without a doubt, it can be challenging to maintain trust as you innovate your modern data architecture. Scaling up typically brings with it more complex data systems and more stakeholders. To retain data visibility and integrity – two key components of data trust – it requires an ever-evolving data governance strategy.
In this article we look at five key ways to create and maintain data trust through effective governance and automation.
Why is data trust so important?
Data trust is about reliability, predictability, truthfulness, and availability. To work out whether you do have this trust in your organization, you have to ask yourself the following:
- Is our data correct?
- Can we rely on it for business decision-making?
- Can we access it quickly and when we need it?
If you’re unable to answer ‘yes’ to any of these questions, the chances are you lack data trust. This could result in your business:
- Wasting resources searching for and verifying data: When business users don’t understand why it takes so long to find and verify data, they start to mistrust the IT team. This not only wastes resources but calls competency, a key marker of trust, into question. Which leads to the next issue.
- Inadvertently creating data silos: Only 22% of business leaders say their teams share data well, according to Zendesk’s CX trends 2023 report. When business users don’t trust IT to give them what they need, they keep their data to themselves.
- Undermining trust in people: If business users then present misguided recommendations based on inaccurate data to your C-level executives, it can tarnish their reputation and further diminish trust in data.
Trust is a fragile thing. It can take a long time to build but only seconds to shatter. Thankfully, there are a few tried and true ways to establish data trust in your organization.
Here’s what you need to know.
5 ways to help you create trust in your data
1. Implement automation
How much time does your IT team spend on repetitive tasks? While processes such as data validation are important, they can eat into your resources and slow down time-to-value.
Automating your tedious data processes frees up time so your IT teams can focus on becoming more proactive with data. New pipelines, and collaborations with business users on complex analyses become possible, helping to boost trust in high-impact business recommendations.
Automation also allows you to regain trust quickly where it has been lost. With automated processes, issues can be identified and fixed more easily and with greater transparency.What is data democratization? How to make data accessible to business users more easily
2. Keep your data together in one central location
Housing your business data in one central data repository helps you create a single source of truth. And benefits abound for IT leaders. For example, data warehouses let you bring trustworthy data from disparate sources together so you can create consistent data validations. This allows you to streamline your data ingestion processes and guarantees that business users are making decisions using only validated and trustworthy data. Alternatively, a data catalog allows you to keep the data where it is while offering an accessible, centralized view.
3. Standardize your data processes
Your IT teams likely handle thousands of data ingestion inputs every day, and each employee will manage and analyze data in a different way based on their skill set. Creating data policies and standardizing training helps improve team collaboration and data transparency. This leads to more consistency, accuracy and efficiency, as well as greater trust in data.
To create standardized data processes, monitor your current day-to-day workflows and identify the most efficient ways of working. You can then create policies that explain how your teams collect, store, and use data in your organization, as well as standardize processes. For example, in CloverDX, you can create and share reusable templates and blocks of code to ensure everyone adopts the same process.
4. Approach your data with caution
Data loss is more common than you might think, and there are several common causes. For example:
- Hardware failure
- Natural disaster
- Cybersecurity breach
- Human error
- Software malfunction
Mishandled and lost data damages more than just your reputation. For example, it can lead to noncompliance with regulations like the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States. Many businesses are still unprepared for these regulations, and both come with hefty fines.
However, there’s a fate worse than knowing you’ve lost data. The act of not knowing can present more danger; you can’t fix what you aren’t aware of. As such, it’s important to not only invest in tools that not only aid compliance but provide transparency.
A tool like CloverDX’s Data Catalog enables your IT team to create connections to live, curated data sources. Here, your business users can get up-to-date, accurate feeds of live data without needed to access the source system itself. This increases visibility and empowers your business users to quickly turn data into decisions, all while ensuring your IT team retains oversight over access management, data quality, and data use.
5. Increase data visibility
On the topic of transparency, it’s important to establish a data ecosystem where all of your users can see where their data has come from and what’s happened to it.
You want to avoid scenarios where data jobs happen within a black box. If you have to blindly trust that your processes and outputs are correct, you’re not really able to trust them at all. With a tool like CloverDX, you can gain visibility into every step of your data pipelines. This is important from a data trust perspective, but can also be incredibly helpful when auditing your processes.
In data we trust
Albert Einstein once said, “Not everything that can be counted counts, and not everything that counts can be counted.” Trusting data is about more than the data itself. It comes down to trusting your people and processes too.
A powerful data platform like CloverDX gives your teams a way of interacting and contextualizing the most reliable data. And with features like DataCatalog and Wrangler, you can open up your data to business users without losing control. Our unified platform lets you automate your processes and validate your pipelines, ensuring your teams only work with the most trustworthy data.