What Are the Key Elements of Enterprise Data Management?

The key elements of any enterprise data management strategy include data quality, data governance, master data management, data security, and data integration. These ensure the quality, accuracy, consistency, security, and availability of data across all functions in real-time.

Data has become the driving force or currency that drives the world of business. From delivering business intelligence and gathering insights on operational needs to charting out user journeys, it has come a long way.

Enterprises, to remain competitive, need to manage data adroitly by employing a holistic data modernization strategy. They need to utilize data to fuel decisions, drive efficiencies, empower the workforce, and shape the company’s direction. This would entail transforming the data into a structured and standardized form, storing it securely, and making it available for easy and quick access. 

Interestingly, enterprises often lack the foresight to maintain a robust enterprise data architecture and scramble to manage data that keeps growing and changing. In fact, according to the market intelligence firm IDC, businesses manage a data volume that keeps growing at a rate of 40% per year. With so much focus on data, let us first understand what enterprise data management is all about.

What is Enterprise Data Management?

Enterprise data management broadly represents the ability of an enterprise to source, integrate, store, and access data seamlessly and securely for business requirements. In other words, enterprise data management deals with the processes and practices to ensure the quality, security, availability, and management of data and how best it can be used for business purposes.

The job of any enterprise data management service is to mitigate any existing or potential issues related to data management. These ensure departments such as IT, HR, Finance, Production, Marketing, and others get easy access to accurate data in real-time. The key to the success of any business that spans domains is its ability to manage data effectively.

Why is Enterprise Data Management (EDM) Crucial for a Business?

Enterprise data management is crucial for any enterprise, as it builds a standardized system to source, monitor, manage, store, access, secure, and share data across functions.

The system ensures the enterprise quickly gets, analyzes, and uses data to draw insights and make decisions in real-time. EDM ensures data and insights always complement each other. The need for an EDM system is to ensure the following outcomes:

• Streamlined operations
• Better decision-making in real time
• Improved customer experience
• Gain competitive advantage
• Create space for innovation
• Better response to customer needs and market changes
• Regulatory compliance
• Reduced costs

Key Elements of Enterprise Data Management

Working with data can be a challenge, so enterprises need to consider some key elements to manage data and be successful.

Data Governance: As the foundation of data management, data governance encompasses laying out the policies, roles, and procedures related to data. It ensures the privacy, integrity, and security of data, compliance with regulatory standards, ethical responsibility and accountability, and a seamless flow of information.

Data Integration: To make the most of any data management solutions, it is important that data be received from various sources and formats and integrated into a centralized repository for easy access. Data integration makes the data uniform and allows stakeholders to extract actionable insights and business intelligence. It helps to reduce errors, save time, and enforce better system collaboration. There are various types of data integration, such as propagation, virtualization, consolidation, and federation.

Master Data Management: It is a process where data is organized, categorized, centralized, and transformed given that most data comes from disparate silos. Master data management (MDM) ensures the quality of the data is enhanced, and suitable insights are drawn for decision-making. It is called master data because employees can make use of it to bring about uniformity in other data and facilitate analytics. As a combination of tools, processes, and software, MDM helps eliminate data redundancies.

Data Quality: Data received from disparate sources can be unorganized, unstructured, incomplete, or even inaccurate. Using such data can negate the reliability of analytics and impact the business. Hence, the quality and integrity of data must be maintained at all times by performing data cleansing, enrichment, and other QA activities.

Data Security: With cybercrime rearing its ugly head now and then and the regulatory landscape changing continually, the security of data must be ensured at all times, whether during storage or transit. Thus, EDM should implement measures to prevent breaches, leaks, theft, or destruction. The measures may include encryption, the use of a virtual private network or data lake services, or two-factor authentication. Even technologies such as blockchain can be an option where enterprises gain from its cryptography and decentralization aspects.

Conclusion

Enterprise data management is a multidimensional concept encompassing a few key components, as stated above. Given that data has become a hack for enterprises to succeed, it is important to leverage data and gain suitable business intelligence.

Hiring experienced enterprise data management services can be a step in the right direction to ensure the EDM ecosystem for a business is alive and kicking.