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Enterprise Data Management: What You Need to Know

Enterprises analyze the data collected in the development process and then put into work to promote decision-making, improve efficiency, and plan the company's development direction. This means that enterprises must collect data, turn it into valuable information, and store it in a safe but still accessible location.

Unfortunately, many enterprises didn't plan and manage the data in the early stage, but now they see that the data is growing and changing every day, but they are helpless.

According to IDC data, enterprises are managing a large amount of data that is growing at an annual rate of 40%. Companies are not only processing more data, but the types of data are expanding. The data stream contains many unstructured data such as inventory figures, financial information, product promotional videos, promotional pictures, and so on. All these different data types need to be centralized, organized, and accessible, and usable by businesses.

So, what is enterprise data management? Enterprise Data Management (EDM) describes the ability of an organization to integrate, manage, protect, and distribute data from multiple data streams. This includes the ability to transmit data accurately and securely between partners and subsidiaries. Effective EDM is not easy, it can only be achieved by fully understanding your data and implementing an intelligent EDM strategy.

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Enterprise data management involves many parts, including:

Data Governance – Data governance refers to policies and processes to ensure data integrity, quality, and security. It is a close relative of data management and covers guidelines on policy implementation, overall responsibility, and governance authority. In short, data governance establishes an organization's data laws and how, when, and by whom to enforce them.

Data Integration – Enterprise data integration means moving and integrating all kinds of enterprise data into an accessible location. This is a key component that enables companies to access and use all the different data forms.

Data Security – Security is an integral part of any data-related strategy. Data security usually refers to the measures taken to ensure that data are protected at all stages of its life cycle, including data at rest and data in transit. This protection involves not only anti-theft and anti-leakage measures but also the work of maintaining data integrity and preventing damage or destruction.

All these factors need to be considered, and now we can draw up an enterprise data management strategy:

Perform Assessment – Enterprises need to have a clear understanding of their data flows and the types of data they have in order to develop effective data management strategies. This work may be time-consuming, but it is a valuable and important process, which can help to ensure that the management methods adopted are completely matched with the data.

Defining Deliverables – Data management may be a vague term. It is important for companies to outline what they hope to accomplish by implementing enterprise data management. What is the ultimate goal? How to measure success? The demand for data is sometimes overwhelmed, and some data items may be very large. In this case, the phased method of step-by-step delivery can work well.

Identify Standards, Policies, and Procedures – Standards, policies, and procedures are invaluable guides to keep data where it is needed and help prevent data corruption, security breaches, and data loss.

Investing in the Right People and Technology – Knowing the skills of managing data is not everyone's strong point. It is better to have in-house or consulting experts who have experience in building enterprise data management system. Their knowledge reserve can help enterprises manage data better. Similarly, it is necessary to deploy a set of excellent data transmission management software (Raysync) for enterprises, which can help enterprises to transmit stored data efficiently, safely, and stably.

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