Data Integration: Digital transformation has changed how companies operate to the point where it is impossible to talk about innovation without mentioning some technological mechanism.
Another fact is that this modernization generates a massive amount of data, which, if used correctly, can be crucial for the growth of a business. The digital transformation has generated considerable changes in business models and the IT sectors of companies. Knowing a little more about innovations can be interesting for your brand’s positioning in the market. Today, business transactions involve multiple actors, systems, technologies, and stakeholders. So relying on expert support is a sensible strategy.
A business manager must follow IT trends to apply them in the company’s reality. Market innovations gave strength to the sales funnel concept. Therefore, data integration is a trend used to optimize corporate processes. If you still don’t understand what we’re talking about, continue reading this article to find out what data integration is and its uses for your company!
How Does Data Integration Work?
Data integration combines data from disparate sources to group it into a single source of information that has some value to users. This method can be used for analytical purposes and applications in the most diverse operational processes.
The overall objective of data integration is to create coherent information and make it accessible. In every organization, an immense amount of data is generated by institutional applications. If interpreted correctly, this data can provide valuable insight into the company’s current market situation and risks and opportunities for future business.
What Types Of Data Integration?
Data integration is an area of great complexity; therefore, there is no standard approach that serves as the basis for any industry or location within a company. IT specialists are constantly improving the techniques we cite below, and each company is responsible for adapting them to their needs.
Extract, Transform And Load (ETL)
ETL — an acronym for “extract, transform, and load” — is one of the most used data integration methods today. As the name suggests, data is extracted from its source and undergoes a transformation process for analytical use. These results are then loaded into a database, where they are stored.
Virtualization consists of integrating data from different points into a single virtual layer without necessarily having to store it in a single location. The process is near real-time and has the advantage of providing a centralized view of information.
Replication is an integration method that copies data from one source to one or more systems similar to the original. This strategy aims to keep the data updated and synchronized between the different systems to protect them in case the source system fails.
Where Can Data Integration Be Applied?
Data integration can be used in customer relationship management to collect and store relevant consumer data. This is especially useful for businesses because it helps teams get a deeper look at who buys from them.
For marketing initiatives, data integration is essential to create personalized emails and campaigns more focused on the profile of each customer. In addition, it allows monitoring the results of each approach to determine which has been most effective, according to the proposed objectives.
Another everyday use of data integration is in analyzing various metrics such as profits, expenses, productivity, employee payrolls, and many other numbers that organizations use to assess the business’s health.
Information management has always been a determining factor for the success of any business. However, having the data at hand is not enough. For them to be relevant to your company, you must have the right tools to process and interpret them correctly. This is how data integration plays a vital role in this scenario.