A considerable amount of data is collected by companies every day in multiple channels and formats. In general, organizations use a lot of software to deal with them, which causes them to spread in silos (the name given to isolated sets of information).
Data integration tools improve communication between business areas, make it easier to meet and anticipate customer needs. They also serve to optimize the functioning of systems and processes. This article will show the most used in the market and how each one can benefit your business.
What Is Data Integration?
Data integration is “to use both technological and business processes to combine data from different sources and generate meaningful and valuable information for the business.” We can understand this as using a single solution to access all business data and gain insights from it, without worrying about the format in which it was saved or the software that gave rise to each silo.
Integrated data is accessed from a single location or shared across all corporate systems. Depending on the volume of data a company works with, one can choose to virtualize the information, store it in a data repository, or data integration processes.
When hiring a consultancy, she will do a study to determine the right option for your organization and what steps are necessary to implement it. The ideal is to integrate data with the help of a partner to ensure the best results.
What Are Data Repositories?
Data repositories are where the information used by BI and BA solutions is stored. Companies use them to serve various Analytics tools and store other business information in the format they are in without structuring them.
The term can refer to several structures for collecting and storing data, such as Data Warehouses and Data Lakes. Repositories are advantageous for organizations because they store all data in one place, making analyzing it a faster task.
Learn more about the two main types of data repositories and how they work.
To organize all the data sets your company has, opting for a data warehouse in the cloud is ideal when you have a considerable amount of them. Data Warehouses are scalable and can be connected to the leading Business Analytics tools available on the market to facilitate the development of solutions with descriptive (past) or predictive (future) analysis.
The warehouses consolidate all the company’s banks, facilitating data governance and reproducing the security policies used by the company to ensure that only authorized users have seen the information they need to make decisions. Each Data Warehouse is customized to meet the demands of a particular company.
Data Lakes from data science course in Bangalore with placement are central data repositories that allow you to store both structured and unstructured data at scale. They are different from Data Warehouses because they can even include information with which your company does not yet know what to do in the future since they do not follow a predefined scheme at the time of data capture.
Several types of analysis, such as Big Data, can be done as the company needs them. Data Lakes are highly efficient in storing and processing information and work just as well in the cloud as on-premise. However, the challenge in their implementation is to create mechanisms to catalog the data and gain access to it when necessary.
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