How to data integration?
How to data integration to the cloud? Check the basic points
"We're currently running our systems in an on-premise environment, but we'd like to take this opportunity to replace them and use the cloud," or "We want to migrate all of our systems from on-premise to the cloud to improve operational efficiency." An increasing number of companies are finding themselves with these needs these days. In order to use data that has been handled on-premise in a cloud environment without any hassle, the key to success is how smoothly data integration can be linked. How should data integration be carried out when migrating existing systems to the cloud? Let's take a look at some basic concepts.
1. Decide on data placement
First, consider data placement based on the individual company's circumstances. Choose an appropriate data placement method based on the current state of the system, current operation methods and issues, and future outlook.
1-1 Four data placement methods
There are four main ways to arrange data:
- Keep all your data on-premise
- Keep all your data in the cloud
- Keeping separate data on-premise and in the cloud
- Same data on-premise and in the cloud
For example, let's say a company operates its customer information and product information on separate servers (on-premises environment). Currently, all data is stored on-premises (1). If they were to move to the cloud, they would have to choose one of the options (2) to (4).
1-2 Points to consider when deciding on data placement
There are four points to consider when choosing a data placement method.
- cost
- Data processing speed
- Ensuring data accuracy
- Security
Consider these points to determine the best approach for your company.
For example, if you choose option (2) "Keep all data in the cloud," you can expect relatively low costs and speedy data processing. However, if any problems occur on the cloud, there is still a risk that the data will become unusable (low data availability). Also, from a security management perspective, many companies have security policies that prohibit storing customer information on the cloud, and in such cases, the policy itself will need to be changed.
Method (3) "Having separate data on-premise and in the cloud" is cost-effective and can be implemented without violating existing security policies, but it is inferior in terms of speed and data availability.
If you choose option (4) "Having the same data on-premise and in the cloud", you can expect data processing to be faster, but this will incur costs for synchronization (replication) and network development and operation.
2. Main methods of cloud data integration
Once the data placement policy has been decided, the next step is to consider how to data integration. There are three methods for data integration:
- Batch integration allows for non-real-time data exchange
- Synchronize data using replication software etc.
- API Integration
The current mainstream method is (1). In other words, a data integration mechanism is installed on the on-premise side, and data is transferred between the cloud and on-premise. This method is not a real-time integration, but development costs can be reduced by using data integration tool or creating your own data integration mechanism. Operation can be made smoother if the tool and system environment is set up so that data can be sent and received with simple operations. For example, operation can be as simple as placing the file you want to data integration in a designated folder and double-clicking the icon for data integration tool created on the desktop.
Method (2) Synchronizing data using replication software allows for real-time processing, but requires development costs. Method (3) API integration has many advantages, such as low cost, ease of implementation, and the ability to use any network, but requires that the application being used is API-compatible.
The functions of currently available cloud services are expected to become even more specialized in the future, and companies will likely have to choose the cloud that best suits them. Going forward, there will be an increasing number of cases where advanced data integration between clouds will be required. data integration when migrating to the cloud must be considered all the more carefully, especially for mission-critical business processes. It is also important to research information and case studies from proven vendors with a deep understanding of the characteristics of each cloud service, and to have a concrete image of your company's system migration and data integration.
summary
This time, we've talked about the concept of cloud data integration. It's important to compare the advantages and disadvantages of each method and find the best solution for your company. We recommend starting by reviewing the current state of your system and how it's being operated, and identifying any issues.
File Sharing: A Beginner's Guide Column List
- File Sharing: An Introduction
- The dangers of "shadow IT" that you should be aware of before using data integration services
- File sharing services: 5 things you need to know when selecting one
- Pitfalls of free file transfer services! Information leakage prevention
- Understand the roles and types of protocols used for file transfer
- Is a file sharing service the best option for sending and receiving large files?
- The ever-increasing volume of data is making file transfer a struggle.
- Three benefits of large-capacity file transfer software that prioritizes ease of use
- Four things to be aware of when data integration
- How to data integration?
- file transfer via HTTP? ISDN will end in 2020
- MFT enables file transfer that FTP cannot.
- No more need for USB flash drives? 3 ways to transfer data over LAN
- Improve business efficiency with data integration platform! Three benefits
- Convenient! How to use Bluetooth for file transfer
- How to use file transfer services that you may have thought you knew about
- Key points to consider when choosing data integration middleware
- Recommended file transfer services to improve business efficiency
- A reliable ally for data integration! Efficient conversion and effective utilization through ETL
- How to data integration with Salesforce
- data integration middleware makes your work more efficient
- This is recommended! data integration service that is conscious of security
- Efficient data integration and siloed system integration through EAI
- When integrating systems with overseas bases, improve work efficiency with English-language tools!
- Three benefits of centrally managing system integration
- A DI platform that data integration scattered throughout the company
