Enterprise Data Management: All You Need to Know
If you're lucky, your business was able to get ahead of the curve with its data management by taking proactive steps over the past few years to deal with the growing tide of data. Unfortunately, many businesses did not have the same foresight and are now scrambling to control their ever-expanding and constantly changing data.
Here's everything you need to know about enterprise data management, whether you're just starting out or perfecting your strategy.
The Many Sides of Enterprise Data
According to IDC, a leading market intelligence company, businesses are managing an increasing volume of data at a rate of 40% per year.
In addition to handling more data, the types and formats of data are also growing. Videos, images, and other unstructured data from social media, mobile devices, and the Internet of Things (IoT) are all included in data streams. Financial data, inventory figures, and other financial data are also included.
All of these varied data types need to be:
- Centralize,
- Organize,
- Make data accessible to and usable by the business.
The true purpose of enterprise data management lies in these three aspects.
What exactly is Enterprise Data Management, then?
An organization's capacity to integrate, regulate, secure, and disseminate data from multiple data streams is referred to as enterprise data management, or EDM for short. This includes being able to securely and precisely transfer data between partners, subsidiaries, applications, and/or processes.
The only way to perform effective enterprise data management is to fully comprehend your data and implement an intelligent enterprise data management strategy.
Four Essential Parts of Enterprise Data Management
Enterprise data management consists of the following parts:
- Data Governance: The procedures and policies implemented to guarantee the security, quality, and integrity of data are referred to as data governance. It encompasses the guidelines regarding policy enforcement, overall responsibility, and governance authority and is a close relative of data stewardship. In a nutshell, data governance is the process of defining an organization's data laws and the procedures for, when, and who enforces them.
- Data Integration: Moving and consolidating a company's various data into a single, accessible location is known as enterprise data integration. This is an essential part of making the company's various data forms accessible and usable. Data integration can take many forms, including virtualization, propagation, federation, consolidation, and others. Cloud integrations are one example of a different strategy.
- Master Data Management (MDM): Master Data Management (MDM) uses data integration methods, which can lead to terminology misinterpretation. As part of an enterprise data management strategy, MDM tools and applications are used to help create master versions of data and provide a consistent view of scattered data. In general, the distinction lies in the fact that while MDM focuses on reconciling a company's data from various sources and making it usable, data integration focuses on the movement, consolidation, and accessibility of data.
- Data Security: Any data-related strategy must include security. Data security often refers to the measures taken to protect data throughout its lifecycle, including when it is at rest and when it is moving. Not only does this protection include measures to prevent theft and leaks, but it also includes efforts to preserve data integrity and prevent its corruption or destruction.
It is possible to draft a business data management strategy after accounting for all of these aspects. A few good practices to keep in mind are listed below.
For businesses to develop an efficient data management strategy, they need to have a clear understanding of their data flows and the types of data they possess.
Enterprise Data Management Strategy Best Practices
Perform Assessment
This work can take a long time, but it is important and worthwhile, and it can help make sure that the management strategies used match the data well.
Define the Process and Deliverables
Data management can be tricky to define. It is essential for businesses to outline their goals for implementing enterprise data management. An enterprise management strategy's focus can be defined by asking questions like:
- What are the end goals?
- What is not in scope?
- How exactly will success be evaluated?
Data projects can be remarkably large and demand can sometimes be overwhelming. A phased approach with incremental deliverables may be effective in those circumstances.
Establish Standards, Policies, and Procedures Standards, policies, and procedures are crucial compass points that help keep data where it needs to be and assist in preventing corruption, security breaches, and data loss. The procedures in place to enable standards and policies are crucial to their success. Methods and tools for staff members to use in order to meet required standards are provided in procedures.
When it comes to complying with regulations, policies are also an important consideration, particularly in highly regulated sectors like financial services and healthcare. They not only safeguard data, but they also assist in avoiding penalties and fines and maintain customer confidence.
Educate and Inform Stakeholders
If the standards, policies, and procedures that surround it are not properly disseminated and emphasized, enterprise data management will undoubtedly fail. Additionally, if everyone who handles data is on board with the project, enterprise data management strategies are better positioned for success.
To ensure that everyone in the company is aware of the enterprise data management objectives, how to achieve them, and the motivations behind the initiative, think about launching an educational campaign. Instead of simply asking employees to adhere to the rules without question, this gives them a comprehensive understanding of the reasons behind them.
Emphasize Quality
In fact, bad data is worse than no data at all.
Your data's value will be preserved and its security and integrity will be preserved if you implement a data quality culture. Stewardship of data is needed in this situation. Businesses must keep in mind the true value of their data and the significance of responsibly maintaining its quality.
Invest in the Right People and Technology
Not everyone is an expert at data management. Enterprise data management services and solutions are best established by an in-house or consultative expert. Their expertise can assist you in selecting the appropriate technologies for your particular use cases. They can also assist your company in successfully implementing EDM by avoiding obstacles like accidental data loss or regulatory violations.