Save Millions of dollars by Governing the Data That Matters for Your Business!

We all know that data is crucial for companies as it enhances decision-making, boosts operational efficiency, improves customer experience, and drives innovation. In today’s digital age, the companies that effectively harness data are often the most successful. Data provides valuable insights into customer behavior, market trends, and internal operations, allowing companies to make informed, evidence-based decisions. This reduces reliance on guesswork and intuition, leading to better strategic planning and resource allocation.

Data enables companies to quickly identify market opportunities and respond to changes in the competitive landscape. Data-driven innovation ensures that products remain relevant and aligned with customer needs. Additionally, data helps businesses identify potential risks—whether financial, operational, or cybersecurity-related—allowing them to take proactive measures.

Accurate data is also essential for regulatory compliance. It helps companies adhere to legal standards and supports transparent reporting for shareholders. Moreover, data allows businesses to track key performance indicators (KPIs) across departments like sales, marketing, and finance. This visibility promotes continuous improvement and aligns efforts with company goals.

Investing in data governance is key to unlocking numerous untapped opportunities. However, not all data is critical. By identifying the right use cases, business scenarios, and investment areas where data insights play a crucial role, companies can significantly reduce their data governance and management costs while maximizing value.

 When Does Data Become a Burden?

While data is a powerful asset, it can become a burden if not managed properly. Excessive data without the ability to filter, prioritize, or analyze it effectively can overwhelm businesses, a phenomenon often referred to as "information overload" or "data fatigue." When companies collect vast amounts of data without clear objectives or strategies for analysis, it becomes challenging to extract meaningful insights, leading to confusion and indecision.

Inaccurate, outdated, incomplete, or inconsistent data can lead to poor decision-making. For instance, bad data can result in errors in customer targeting, financial forecasting, or operational planning. The costs associated with bad data—including incorrect business decisions, customer dissatisfaction, and regulatory risks—can be substantial.

When different departments or teams store data in isolated systems, it creates "data silos." This fragmentation prevents a unified view of the business and leads to inefficiencies, as key insights may be locked away from decision-makers. Data silos make it difficult to gain a holistic understanding of customer behavior or company performance.

Additionally, the cost of storing and maintaining large volumes of data can become a financial burden. Managing vast datasets requires significant resources—both in technology and human expertise. Without proper data governance and strategies, companies face operational inefficiencies and squander resources on maintaining data that doesn’t provide value.

If businesses can't extract value from their data, the effort spent on collecting and maintaining it becomes wasteful, resulting in lost opportunities for innovation, customer insights, and growth. Moreover, the more data a company collects and stores, the more attractive it becomes to cybercriminals. Protecting large data sets requires advanced, costly security measures.

Ironically, having too much data can also slow decision-making. An overload of information can cause "paralysis by analysis," where teams spend excessive time analyzing data instead of making timely, effective decisions.

Case Study – Data Governance with Data Minimalism

A recent study revealed that approximately 40% of data assets are not required for governance. Of the 5,200 data assets reviewed, many were found to be unused in business scenarios, processes, or any critical use cases. After evaluating several business scenarios, we identified that around 40% of these assets were non-critical or unused:

• Account Intelligence
• Marketing Execution
• Sales Execution
• Support Analytics
• Compliance Analytics
• Performance Management
• Customer Growth and Experience
• Service and Operations
• Procurement
• Order and Revenue

Additionally, 16% of the data assets were identified as exact duplicates, while 7% were nearly identical, differing by only one or two attributes (93-98% of the columns were the same). Instead of extending and reusing existing data assets, new ones were created, causing unnecessary duplication.

Sales domain data is maintained by seven different teams, product data by six, and customer data by eleven different teams. This lack of governance and poor data management practices has led to many identical copies of the same data asset being stored across multiple databases. Investing in the governance and maintenance of this 40% (2,080) of unused data assets is wasteful, as they serve no clear business purpose.

This presents a significant opportunity to apply data minimalism, a concept advocating for the intentional collection, storage, and use of only the most essential and relevant data. Instead of hoarding unnecessary amounts of data, data minimalism reduces risks, costs, and complexities, while still enabling organizations to make informed decisions. It emphasizes efficiency, simplicity, and data quality over sheer volume.

Key Learnings from This Case Study:

• Govern data that matters for the companies - focus on managing and overseeing only the most critical, and relevant data that directly supports a company’s goals and objectives. It involves setting up Governance domain, practices, policies, and tools that ensure valuable data is properly collected, protected, managed, and used in a way that drives business value while minimizing risks.
• Collect only the necessary data to achieve specific business objectives or meet regulatory requirements. This reduces the burden of storing, processing, and analyzing large datasets, ensuring each data point serves a clear purpose and minimizing "data fatigue" and unnecessary complexity.
• Prioritize high-quality, accurate, and reliable data over collecting vast amounts of information. Accurate and clean data leads to better decision-making. By minimizing data collection, businesses can focus on improving data quality and avoid errors or inconsistencies from bad or redundant data.
• Reduce exposure to data breaches and legal risks. Less data means a lower risk of mishandling personal information, which helps build trust with customers and stakeholders by respecting their privacy.
• Focus on the most relevant data for sharper insights and improved decision-making. Data minimalism prevents businesses from being overwhelmed by irrelevant information, ensuring targeted data collection that leads to more actionable insights addressing key business challenges.
• Encourage responsible data use and govern by limiting the collection of unnecessary personal information and aligning with ethical standards. Companies practicing data minimalism can easily maintain ethical standards, avoid intrusive data collection, and enhance their corporate responsibility image.
• Optimize resource allocation. By avoiding unnecessary data collection, companies can allocate their resources more effectively, focusing on strategic analysis rather than maintaining massive datasets.

By adopting these principles, organizations can streamline their data management processes, enhance compliance, and improve decision-making, all while contributing to sustainability and ethical data practices.

How Can Microsoft Purview Help You Manage Your Critical Data Assets?

Microsoft Purview’s integrated experience enables companies across all industries to effectively manage their data governance and data quality frameworks while maintaining a manageable investment. The comprehensive data governance framework offered by Microsoft Purview allows organizations and data practitioners to rethink and strategically plan the scope of their data estate, focusing on governing the critical data necessary to run and manage their business operations.

With Purview, data consumers can easily discover and subscribe to data products required for their analytics and business reporting needs. Data product owners can define and create data products, associate the necessary data assets, policies, and glossary terms, and publish them within governed data domains for subscription and specific use cases. Data stewards can then curate these data products to ensure they are discoverable, trustworthy, and readily available for subscription.

By using Microsoft Purview, organizations can streamline their data governance processes, ensuring that critical data assets are well-managed and accessible for decision-making and operational efficiency.

Data quality stewards can define, measure, analyze, improve, and control the health of their multi-cloud data estate using Microsoft Purview’s integrated experience. Microsoft Purview integrated DQ experience enables data quality stewards to implement a comprehensive data quality framework for managing data health. With Purview, stewards can profile data, define and apply data quality rules, monitor data quality (DQ) scores and metrics, and assign remediation actions. Notifications can be sent to data publishers and consumers to address and resolve any data quality issues.

Microsoft Purview offers everything data practitioners and companies need to effectively govern and manage the health of their data estate. Additionally, Purview is integrated with a variety of partners to provide master data management solutions and business lineage, allowing companies to govern their entire data estate through one unified platform. This eliminates the need for siloed approaches to data governance and control, streamlining the management of the entire data ecosystem running on multi-cloud and heterogeneous infrastructure.

Summary

Data is critical for a company for several key reasons, helping businesses operate efficiently, make informed decisions, and gain competitive advantages. Again, data can be a burden for a company if they do not manage and govern data properly.  Companies should think what data matter for their business, if data are not matter for any business scenario, then why company need to govern those data. Companies should focus on critical data to business, which will help them to govern those critical data to run their business with highest trust.  This will help companies to reduce their data management costs. They will be able to define, measure, analyze, improve, and control their overall data management with low investment.

Data minimalism is a strategic approach that helps companies maximize the value of data while minimizing the risks and burdens associated with excessive data collection and management. It’s about being deliberate in what data is collected, processed, and analyzed—resulting in simpler, more efficient, and ethical data practices. This approach can enhance business performance while reducing costs, improving compliance, and fostering greater agility. Without proper governance, integration, and analysis, data can lead to increased costs, operational inefficiencies, and even legal trouble. Effective data management strategies are key to preventing it from becoming a liability. Misuse of data, whether intentional or accidental, can lead to legal and ethical concerns. Companies need to balance data usage with ethical standards, which can become complicated as data collection methods evolve. Governing the data that matters for companies will help them reduce data management costs and unlock even more unrealized opportunities.

References

• New data governance experience in Microsoft Purview
• Microsoft purview pricing concept
• Governance domain of your data estate
• Data Product in Microsoft Purview
• Discover your data product
• Integrated data quality experience in Microsoft Purview