What Is Data Integration – Definition and Deep Meaning
Enterprise data integration is the process of combining all the data stored and accumulated by your company throughout its existence in one place. What is more, it also means fully organizing your data and its systematization in a single format – for quick access, convenient analytics and flexible forecasting capabilities. Neil Raiden, one of the data experts, defines the process of data integration as modeling of its meaning. That is, having a large amount of information from disparate sources, and integrating it into a single system, we get a chance to get completely new, unexpected and useful insights. In other words, a certain piece of data may not have practical application alone, however, after being integrated into a system of interconnected information, it may acquire a different meaning and sense.
What Are the Reasons to Implement and Benefits of Data Integration?
Let’s suppose your data is already integrated. What can you do with the final result? Back in 2009, 1out of 2 business leaders say that are unable to get the information necessary to perform their tasks. For now, 83% of modern business leaders always or usually have access to any data they need and are able to make more 100% informed and data-driven decisions due to the enterprise data integration. Enterprise data integration allows getting all the data regarding your customers in one place -and while being combined with other effective tools, it makes it possible to instantly perform any action to satisfy your customers and partners. Enterprise data integration allows shortening the order-shipment chain up to 50%. Real-time access to data will be always crucial when it comes to improving internal processes. Transactional costs are also reduced by 35% when EDI is realized. The necessity to be distracted and think about whether to find the data they need absorbs the time and effort of your employees. Enterprise data integration allows them to have is all at their fingertips. Combining historical information with real-time data and artificial intelligence algorithms makes it possible to get the most accurate forecasts and build advanced business strategies on their basis. Since all data, both current and historical, are connected in one system, this makes it possible to automatically generate reports on the status of sales and profits at any time. You can always test out different tools that can help you efficiently blend data from multiple systems and see which one suits all your needs. By the way, there is a chart that shows how modern companies use the benefits of data integration and what goals they pursue.
The Step-By-Step Data Integration Process
So, how will this happen in practice? This is the very first but the most difficult stage in the whole process, because at the moment your data is in different sources, have different formats and different quality. At this point, you need to decide exactly how your data will be synchronized. After that, the data is loaded into the integration system. It is necessary to choose this system based on your goals and expectations, as well as to analyze whether there is a possibility of bilateral synchronization and take into account the frequency of updating your data. After all the data has got inside one system, it is necessary to do the initial data classification by assigning a meta tag to each element. At this stage, each of the departments and users gets the opportunity to use only the data that is really required for its work, while all changes will be synchronized with each other.
What Are Data Integration Techniques?
There are several approaches to data integration, each of which meets specific business goals. As part of data consolidation, all data is transferred from various systems to a single repository. This is an effective approach to collect all disparate data in one place, but in this case, there is a delay between data updates in the source systems and data updates in a single repository. This delay can range from a few seconds to several days, and so far the possibility of lightning-fast synchronization has not yet been developed. When federating data, data is consolidated in one virtual location at the request of the user. That is, the data remains scattered until the system receives a request for its integration. An example of this approach is enterprise informational integration (EII). In this case, the data is copied and transferred from one place to another at the request of the user. Examples of this approach are Enterprise application integration (EAI) and Enterprise data replication (EDR). As the name implies, in this case, it becomes possible to use several approaches to data integration at once.
What Are Data Integration Tools?
Data integration tool is special software that will help you to go through the process we have described above, and them, work with your integrated data according to the basic approaches. Here are some data integration services examples you may choose from.
Oracle GoldenGate, IBM InfoSphere DataStage, InfoSphere, SAS Enterprise Data Integration Server, SSIS, Informatica PowerCenter.
Data Integration or Migration?
The main difference between migration and data integration is that migration is simply transferring data from several external sources, while integration is a complete ordering of all your data and bringing them to a single format for generating insights.
Conclusion – Taking the Final Decision and Choosing the Right Data Integration Vendor for Your Business
So, here is the infographic that clearly shows the main benefits and goals of data integration that may be relevant for your business. However, making the decision to integrate your data, you immediately face the next logical question of how to choose a reliable vendor that will help you. Choosing the company, you should make sure that they are fully aware of the value of data for business, and take full responsibility for its preservation and security. The team should work in compliance with the most stringent rules for handling sensitive and strategic information. For instance, the employees of data integration company SPD Group have the relevant experience, expertise, and the most updated knowledge, which allows them to solve the most diverse business tasks in working with data and using artificial intelligence.
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