Data Governance in the Cloud: Why You Need More Than Just Data Management

Gartner analysts estimate that by 2025, 80% of organizations seeking to scale their digital business will fail because they do not adopt a modern approach to data management. Why? Because they’re missing the fundamental piece of the puzzle: effective data governance.

As the amount of data like customer interactions, operational metrics and market analytics keeps increasing, businesses need to implement strategies, policies and solutions to ensure data quality, security and availability. Read on to find out how data governance impacts companies and how you can benefit from this practice.

Understanding modern data governance

At its core, data governance is a comprehensive approach to managing, using and protecting corporate data assets. It’s like an orchestra where every instrument plays a crucial role – from data quality and security to accessibility and compliance.

Modern data governance is built on several key pillars.

First, there’s data quality management, which helps you ensure your data is accurate, consistent and reliable across all systems.

Then comes metadata management – think of it as your data’s DNA which describes where the data came from, how it’s been transformed and how it’s being used.

Security and privacy controls act as guardians that ensure data is protected and accessed only by authorized users.

Data lifecycle management tracks your information from creation to deletion, while data architecture provides the blueprint for how all elements of data governance fit together.

But data governance isn’t just about rules and restrictions. It enables your organization to use data confidently and effectively. It’s about knowing that when your marketing team examines customer insights, your finance department runs forecasts or your product team analyzes user behavior, they’re all working with trusted, secure and up-to-date information.

Why is data governance important across industries?

Data governance isn’t reserved only for large corporations with massive IT departments. From two-person startups to global enterprises, everyone who works with data needs governance – and nowadays, that means every company.

Take healthcare providers, for instance. With effective data governance, they can dramatically reduce operational costs while significantly improving patient outcomes. Meanwhile, retail companies can use governed data to predict customer behavior with unprecedented accuracy, leading to remarkable improvements in customer acquisition.

Regardless of their industries, companies that prioritize data management can achieve better business outcomes through enhanced decision-making based on accurate, high-quality data. Proper data management, combined with effective data governance, also increases operational efficiency by eliminating redundancies.

Moreover, data governance enables successful implementation of automation and AI as it ensures high data quality, which is essential for AI-driven solutions. It also supports businesses in complying with various regulations. Overall, it provides companies with increased visibility into the data assets they own so that they can easily identify risks and threats. Data governance also helps improve data security and privacy by establishing policies to foster safe data management.

Data governance is not just a marginal improvement – it’s a game-changer for companies that want to make the most out of their data.

The modern data governance landscape

The cloud has revolutionized the way businesses approach data management, and the major players are constantly innovating in this space. For example, Microsoft Purview is redefining automated data discovery and classification. This system automatically catalogs all your data assets, tracks their sources and ensures compliance – all while seamlessly integrating with your existing Azure infrastructure. As a result, this solution can significantly reduce the time spent on manual data classification tasks.

AWS isn’t far behind, with Lake Formation changing the way organizations build and manage data lakes. This solution enables companies to easily manage data lake access permissions, manage security at scale, get improved insights and audit their data. It can also help reduce data lake setup time, while maintaining solid governance controls across the entire data ecosystem.

Implementation is the real challenge

Implementing data governance isn’t just about choosing the right technology. Often, introducing data governance requires cultural changes and process transformation.

The first most important step is to understand your organization’s unique needs and how data governance can support them. Implementation also includes defining clear roles, responsibilities and access permissions – establishing and documenting this information can take time. Data governance also requires companies to create policies and procedures regarding, for example, security, privacy, data quality and ethics.

When developing these elements of the data governance framework, it doesn’t help that many businesses have to navigate complex data ecosystems comprised of different data platforms. These ecosystems are sometimes siloed and fragmented across departments, which adds another layer of complexity. Coordinating all this data and ensuring its consistency as well as quality can be an additional challenge, which needs to be resolved to effectively implement data governance.

There’s also the matter of change management. Your data governance framework might require your teams to adapt to new processes and procedures. In some cases, you might encounter some resistance to these changes. It’s important, then, to educate and train your employees to expand their knowledge, while ensuring alignment and collaboration.

Effective introduction of data governance requires domain knowledge and skills to ensure the framework addresses an organization’s requirements, while meeting industry-specific regulations. To get support on this journey, it’s a good idea to team up with a software partner who has data management experience and can help you prepare and implement data governance policies tailored to your specific needs.

Making data governance work for your organization

The path to successful data governance is both challenging and rewarding. Implementing data governance requires significant investments in people, processes and technology. While measuring the return on investment (ROI) of data initiatives may seem difficult at first glance – after all, how do you quantify something as intangible as “better data”? – the numbers speak for themselves. 80% of companies see high-quality governance as key to long-term success, but only 50% of leaders actually monitor their data governance systems.

This monitoring is crucial for securing long-term executive support and positioning data governance as a business enabler, not just an IT cost center. Understanding how your data governance framework functions will help you optimize your systems, identify areas for improvement and explain how this initiative contributes to your company’s goals. It’s an important aspect of promoting and advocating for data governance across your organization.

Consider a compelling case from a Fortune 500 company that was initially struggling with data chaos. Their reports were scattered, and decision-making was based largely on guesswork, significantly impacting their bottom line. By implementing a comprehensive data governance strategy, they transformed their operations from data confusion to data-driven decision making. This success story isn’t an outlier – it’s a testament to what’s possible with the right approach and commitment.

Similar transformations can be seen across industries – for instance, insurance company APRIL International successfully consolidated their customer data, which led to improved sales and revenue growth. Meanwhile, industrial minerals producer Imerys merged their disparate systems, which resulted in enhanced operational efficiency, better insights and improved regulatory compliance. These successes are particularly relevant as the adoption of new technologies, like generative AI, accelerates.

Get more out of your data with data governance

The financial impact of poor data governance is staggering – organizations lose, on average, $12.9 million annually due to poor data quality, according to Gartner. By implementing data governance, businesses naturally have to improve their data quality, which creates new opportunities.

These returns can come from multiple sources:

• Direct cost savings through reduced data breaches, compliance penalties, elimination of duplicate data silos and lower IT infrastructure costs.
• Significant productivity gains from streamlining data processes, enabling self-service data access and reducing time spent on manual data preparation and reconciliation.
• Perhaps most importantly, increased revenue opportunities through enhanced decision-making capabilities, improved customer analytics for personalized marketing as well as enabling advanced analytics and AI/ML initiatives.

In today’s data-driven economy, effective data governance isn’t just about managing risk, it’s about unlocking your data’s full potential to create sustainable competitive advantage.

If you want to learn more about the latest data governance trends, watch this online conference, led by Microsoft and Software Mind experts. You’ll get to explore modern data management solutions, discover best practices for improving data quality and hear about integrating AI with existing data management systems.