Enterprise Data Management: What You Need to Know
The increased pressure to implement enterprise data management is not the result of a fad or herd mentality. There are real operational needs driving this movement. Chief among these is the urgent demand to make data accessible and useful. Businesses need to be able to put their data to work fueling decisions, empowering efficiencies, and shaping company direction. That means data must be standardized, converted to useful forms, and stored where it is secure but still accessible to users.
If you are lucky, your company was able to get a jump on its data management, implementing proactive measures over the last few years to handle the swelling data tide. Unfortunately many enterprises weren’t quite so vigilant and now find themselves scrambling to get a handle on their data, which is growing and changing by the day.
The Many Sides of Enterprise Data
According to IDC, businesses are managing a volume of data that is growing at an average of 40% a year. Not only are companies handling more data, but the types of data are expanding as well. Data streams contain everything from inventory figures and financial information to videos, images, and other unstructured data coming in from social media, mobile, and the Internet of Things (IoT). All of these varied data types need to be centralized, organized, and made accessible and useable to the business. That is the true mission of enterprise data management.
So, What is Enterprise Data Management?
Let’s back up just a bit and address this question. Enterprise Data Management (EDM) describes an organization’s capacity to integrate, govern, secure, and disseminate data from multiple data streams. This includes the ability to accurately and safely transfer data among partners, subsidiaries, applications, and/or processes. Effective EDM is no easy feat and can only be accomplished by fully understanding your data and implementing an intelligent EDM strategy.
Enterprise data management involves several components, including:
- Data Governance – Data governance refers to the policies and processes used to ensure the integrity, quality, and security of data. It is a close relative of data stewardship and encompasses the guidelines around policy enforcement, overall responsibility, and governance authority. In short, data governance establishes an organization’s data laws and how, when, and by whom they are enforced.
- Data Integration – Enterprise data integration means moving and consolidating a business’s varied data into one, accessible place. This is a key component to making all the disparate data forms accessible and useable for the company. There are several different types of data integration, including virtualization, propagation, federation, and consolidation.
- Master Data Management – Data integration methods are used in Master Data Management (MDM) and there can be some confusion involving these terminologies. MDM refers to tools or applications used as part of an enterprise data management strategy to help create master versions of data and provide a consistent view of scattered data. To generalize, data integration is about the movement and consolidation of data and making it accessible, while MDM is about reconciling a business’s data from varied sources and making it useable.
- Data Security – Security is an integral part of any data-related strategy. Data security often refers to the measures in place to ensure data is protected at all points of its lifecycle, including data at rest and data in transit. This protection not only refers to anti-theft and anti-leaking measures, but also to efforts that maintain data integrity and prevent corruption or destruction.
With all of those components accounted for, it’s possible to draft an EDM strategy. Below are a few best practices to keep in mind.
Enterprise Data Management Strategy Best Practices
- Perform Assessment – Businesses need a clear understanding of their data flows and the types of data they have in order to craft an effective data management strategy. This work can be time-consuming, but it is a worthwhile, important process that can help ensure the methods of management employed are well matched with the data.
- Define Deliverables – Data management can be a nebulous term. It’s important for companies to outline what they hope to accomplish by implementing enterprise data management. What are the end goals? What is not in scope? How will success be measured? Demands on data can at times be overwhelming and some data projects can be remarkably large. In those cases, a phased approach with incremental deliverables can work well.
- Determine Standards, Policies, and Procedures – Standards, policies, and procedures are invaluable guideposts, keeping data where it needs to be and helping to prevent corruption, security breaches, and loss of data. The success of standards and policies hinges greatly on the procedures in place to enable them. Procedures give staff members methods and tools they can use to meet required standards. Policies are also important when it comes to regulatory compliance, especially in highly regulated industries like healthcare and financial services. Not only do they protect data, they help prevent fines and penalties, and help preserve customer confidence.
- Educate and Inform Stakeholders -- Enterprise data management is sure to fail if the standards, policies, and procedures surrounding it are not properly disseminated and emphasized. Additionally, EDM strategies are better positioned for success if all of those who deal with data are on board with the project. Consider an education campaign to ensure a company-wide understanding of the EDM goals, the methods to achieve them, and the reasons behind the initiative. This equips staff members with a full understanding of why certain rules are in place, instead of just asking them to blindly follow them.
- Emphasize Quality – Bad data is actually worse than no data at all. Adopting a culture of data quality will help protect your data’s security and integrity and ultimately preserve its worth. This is where data stewardship comes in. It’s important for businesses to remember how valuable their data truly is and how important it is to responsibly maintain its quality.
- Invest in the Right People and Technology – Understanding the art of managing data isn’t everyone’s forte. It’s best to have an in-house or consultative expert with experience establishing enterprise data management systems. Their knowledge can help identify the right technologies to use. They can also help your business avoid pitfalls, including accidental data loss or regulatory violations, thus aiding in a successfully, smooth EDM implementation.
The Term "data integration" can be interpreted in different ways, depending on context. In this blog, we explain 5 common types of data integration: 5 Types of Data Integration You Need to Know
Learn how one organization managed to streamline its data transfer processes and secure all of its data movements in this success story: International Fast Food Chain Eliminates Legacy Data Transfer Inefficiencies with EFT Enterprise
Without an effective enterprise data management plan, accomplishing business objectives can't happen in the most efficient or secure way possible. Learn more: Enterprise Data Management with Managed File Transfer