DX (digital transformation), which permeates IT into various activities of people, including corporate activities, is becoming a trend. In particular, by utilizing data in AI, etc., there are active movements to improve operational efficiency and increase the possibility of earning profits. However, collecting data alone cannot deliver its value. Especially in DX promotion, the concept of data management that maximizes the value of data by appropriate operation and management of data is important. In this article, we will give you an overview of data management and the basics of data management.
Table of contents
- The role and need of data management
- Data subject to data management
- Benefits of data management
- 11 basics of data management
- How can a company succeed in data management?
- If you want to succeed in data management, leave it to the no-code AI tool “UMWELT”!
- summary
The role and need of data management
The amount of data held by companies is increasing year by year. At the same time, the importance of data management, which manages and operates data appropriately, is increasing. Here, let’s explain the role and necessity of data management.
What is data management?
The general implication of data management is to leverage and manage your own data for business growth and outcomes. The purpose is not only to manage physical data, but also to establish a general mechanism for the relationship between business and data, such as data collection, management, design, examination / execution of utilization methods, and security management.
The role of data management
Data held by a company is an important asset that is indispensable for developing a business. What kind of data is needed to solve problems in corporate activities and achieve objectives / goals, what is the appropriate data analysis method, what is the optimal data management method, and so on. Is the role of data management.
Why you need it for your business
It is difficult to utilize it for corporate activities just by collecting and storing data. If you do not collect the necessary data for your purpose, you will not be able to utilize it in your business. In addition, accurate data utilization cannot be implemented unless the data is organized. And data management is also important from a security perspective. Leakage of customer information is directly linked to corporate credit problems. Data management is indispensable to business in order to make data and corporate activities closely related.
Data subject to data management
Data subject to data management can be broadly divided into business data and metadata. I will explain each of them.
Business data
Business data is data used for general business activities. For example, data used when market segmentation is performed to narrow down the target and formulate a marketing strategy is one of them. Business data also includes unstructured data such as audio and images.
Metadata
Metadata is data that contains information that accompanies this data. For example, file creation date, author, editor, save location, size, and so on. For files such as PDF, Word, and Excel, the information can be confirmed from the properties. As the number of data files increases, management tends to become complicated, but by utilizing metadata, data management and security can be expected to improve.
Benefits of data management
So far, I have given you an overview and types of data management. However, the benefits of performing data management can be difficult to grasp. Therefore, I would like to introduce the merits of data management.
Trigger new business opportunities
Data management speeds data-based decision making. It also leads to visualization of your company’s business processes and allows you to clarify issues. Prompt decision-making and understanding of company issues will be important factors for corporate growth and productivity improvement. As a result, data management opens up new business opportunities.
It will be possible to reduce business risk
You can promote the use of data analysis in planning corporate strategies. Data management makes it possible to select and utilize appropriate data for strategy formulation. Data is also an important information asset and sensitive information for businesses. From a security perspective as well, managing data management is essential. By utilizing data management, it is possible to reduce business risks such as highly accurate strategy planning and security management.
11 basics of data management
DMBOK is a book that summarizes knowledge about data management and is published by “Data Management Association International”, a data management organization in the United States. DMBOK, which summarizes the body of knowledge of data management, introduces the concepts necessary for data management in 11 areas. Here, we will explain the 11 defined knowledge areas.
1. Data governance
Data governance refers to managing data management activities company-wide. Ideally, we should support from a company-wide perspective in order to smoothly proceed with data management activities such as whether overall optimization has been achieved and whether compliance and other rules have been observed.
2. Data architecture
Clarifying the purpose of data utilization in a company and designing and maintaining data management suitable for the purpose is called data architecture. By setting the ideal data management for the entire company and implementing data governance based on it, the effect of data management activities can be maximized.
3. Data modeling
Data modeling is to clarify the data management process in a format called a data model based on the identified data requirements. The data model consists of attributes, entities (the targets of information gathering), and relationships (relationships between entities). Schematizing with data modeling helps clarify the flow of data governance.
4. Data storage / data operation
Data design and construction of data system implementation infrastructure are called data storage and data operation. We will build a company-wide data management system based on data architecture and data modeling.
5. Data integration / interoperability
Data integration and interoperability are also essential in data management. By building a data collection mechanism and linking systems, we will facilitate the data flow with existing systems and tools used by individual departments.
6. Document / content management
Content management, such as unstructured data such as documents and images, is also part of our data management activities. In particular, data governance needs to be instilled in the management of documents containing confidential information.
7. Master data management
Data that is common in the business of the company is called master data. Centralized management of master data leads to improvement of data quality and reduction of data integration cost.
8. Data warehousing / business intelligence
Business intelligence is the use of data within a company for analysis and reporting, and for corporate decision making. Data warehousing is a method of appropriately rearranging data to solve problems and achieve goals. Recently, with the spread of BI tools and the like, the movement to automate analysis work has become widespread.
9. Metadata management
Even if data management is optimized, if the employees who use the data do not have access to the data they need, then data management is not possible. Incorporate the concept of data governance into metadata and manage it by unifying rules company-wide.
10. Data quality
It is also important to control data quality standards company-wide. In particular, when performing data analysis mechanically with AI etc., it is necessary to preprocess the data, so it is desirable that the file format, unit, etc. are at least unified.
11. Data security
Data security is also an important aspect of data management, such as security policy establishment, authentication authority management, and access control. In addition to the security risks that can be assumed in advance, it is necessary to regularly review security even at the execution stage of data management.
How can a company succeed in data management?
Data management flows are being systematized, and it is known that the causes of failure can be summarized by similar factors. Here, we will explain the key points for a company to succeed in data management.
Clarify the purpose
Data management is only a means to develop corporate activities. By clarifying the purpose to be achieved by data management in advance, the axes of data governance and data architecture are determined.
Develop a medium- to long-term strategy for the entire organization
With the aim of solving short-term problems in data utilization, data management will not be led within the company, and individual optimization will proceed. Since corporate activities are facilitated by uniting the entire company, it is important to carefully formulate strategies over the medium to long term without being confused by short-term results.
Keep in mind a small start
As for the strategy, it is important to work on data management throughout the organization in the medium to long term. However, when you actually start the data management process, try to make a small start so as not to cause confusion within the company. Accumulating successful cases of data management within the company will lead to the final company-wide efforts.
If you want to succeed in data management, leave it to the no-code AI tool “UMWELT”!
TRYETING’s no-code AI cloud UMWELT is recommended for companies that want to utilize data that incorporates data management. UMWELT can build AI just by dragging and dropping without writing code. There is no need to hire AI personnel or data scientists. UMWELT can also be connected to mission-critical systems, making it an effective tool from the perspective of data management and security.
summary
We introduced the concept and types of data management. By utilizing UMWELT, it is possible to utilize data that incorporates the concept of data management. Information can be collected in advance by downloading materials and free consultation is possible, so if you are looking for data utilization, please consider it once.
