Standardization is the key to successful data integration

What is data integration standardization?

To put it simply, standardization of data integration is "unifying the rules and formats for efficiently developing and operating data integration between different systems."

We support the standardization of data integration by combining our customers' DX concepts with data integration know-how we have cultivated over the years.

So why is standardization of data integration so important?
Let's take a look at the challenges that arise when promoting data integration.

Challenges in promoting data integration

Let's take the example of upgrading mission-critical business systems. When building an interface for upgrading mission-critical business systems, if a connection method that is heavily dependent on the specifications of mission-critical business systems is adopted, there is a risk that data integration will not be scalable and will have a significant impact when it is modified.

Furthermore, as SaaS is adopted one after another by each department and data integration tool are selected on an individual basis, various data integration tool are scattered throughout the company, which makes them difficult to maintain and increases costs.

One way to prevent the above scenario is to adopt a single data integration tool, but if development and operation/maintenance policies are decided for each project, it may end up being individually optimized for each project.

In either case, this leads to a decrease in maintainability and development efficiency in data integration, and increases the costs and labor required for development and operation and maintenance.Even if automation through data integration has made operations more efficient, the benefits of data integration will be diminished if the work required to create and maintain this system increases.

Concept of data integration standardization

We have given you an idea of the importance of standardizing data integration by using examples of challenges in promoting data integration, but we would like to introduce our thinking on what to standardize and how.

Our understanding of standardization means organizing and unifying things related to data integration so that the same results can be obtained regardless of who is developing and operating data integration. Specifically, there are three steps involved:

① Formulating development and operation rules related to data integration

② Patterning of interface configuration

3) Standardization of functions required for multiple interfaces

Let's look at these one by one.

① Formulating development and operation rules related to data integration

In order to carry out controlled design and development, as well as operation and maintenance data integration various rules must be established. In terms of design and development, these include how to divide functions, what type of data integration processing to perform, and from what perspective to test. In terms of operation and maintenance, these include how to back up and restore, and how to manage permissions and incidents. data integration standardization support provides the know-how to determine these rules.

② Patterning of interface configuration

Interfaces with the same integration method are grouped together, and interface configurations are patterned to improve development efficiency. The main criteria for grouping are the integration method (connection protocol), startup method (batch or on-demand), and whether or not conversion is required. For each pattern, we organize how to configure data integration processing.

3) Standardization of functions required for multiple interfaces

It is more efficient to share common components across multiple interfaces than to develop them individually. For example, this includes outputting logs when data integration processing is performed, and sending emails to notify the maintenance team of abnormalities. Functions required for multiple interfaces are standardized as a single component and summarized as a "common component."

Expected effects of data integration standardization

What benefits does standardizing data integration bring to customers? For example, we believe that by implementing this initiative, we can expect the following effects:

• Improving efficiency and reducing costs through patterning and standardization
• Improve governance through development and operations based on common rules
• Establishing guidelines to eliminate dependency on individuals and promote in-house production
• Expand data integration and utilization efficiently with a streamlined platform

Naturally, this will reduce the man-hours required to develop and operate data integration platform, but it can also contribute to DX (digital transformation), such as promoting in-house development, which has been gaining attention in recent years, and expanding data integration for data utilization.

Finally

This time, we introduced "data integration standardization," an important concept for successful data integration.

We also provide support services for standardizing data integration data integration integration know-how we have cultivated over the years. An overview of our services can be found on our website.

The person who wrote the article

Affiliation: Data Integration Consulting Department, Data & AI Evangelist

Shinnosuke Yamamoto

After joining the company, he worked as a data engineer, designing and developing data infrastructure, primarily for major manufacturing clients. He then became involved in business planning for the standardization of data integration and the introduction of generative AI environments. From April 2023, he will be working as a pre-sales representative, proposing and planning services related to data infrastructure, while also giving lectures at seminars and acting as an evangelist in the "data x generative AI" field. His hobbies are traveling to remote islands and visiting open-air baths.
(Affiliations are as of the time of publication)

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