Data Integration: What it is and why it is important?

Running a company without data and analytics is akin to playing one of those bat-and-ball games where you have to strike the target but with a blindfold on your eyes. Businesses have been generating massive data that needs to be analysed and interpreted to be of use. And for this, companies have relied on data warehouses with unique schemas for specific functions or applications in the business for years.

Furthermore, when a team wished to add a new data set for extra context and source material, they had to undergo a lengthy manual process. To update the data warehouse, they'd have to describe needs independently, source new data, and manually design new procedures - all while ensuring that the changed schema didn't disrupt current functionality. Manually working on such vast data repositories was not only challenging but also gave rise to errors.

However, the technological advancement brought by the current digital wave has completely revolutionised the business world and how companies function now. For today's enterprise, assembling and using the information acquired from loads of data is easier said than done. Companies face a challenge in conducting successful business intelligence analysis on data from various sources and locations, each with its own set of formatting requirements. Data integration is all about resolving that issue.

What is Data Integration?

Data integration, in technical terms, is the process of merging data from several sources into a single cohesive perspective. Ingestion approaches, such as ETL (extract, transform, load), mapping, cleansing, and transformation, are all part of the integration process. Finally, integrated data management enables analytics tools to generate actionable insights and business intelligence.

The field of data integration is enormous, and there is no one-size-fits-all strategy for integrated data platform. Nonetheless, the process usually comprises a few standard components, such as a master server, a network of data sources, and clients who access data from the master server.

Why is Data Integration Important for Businesses?

While it's obvious why every organisation needs data integration, here's a more in-depth look at how integrated data management affects technical and business operations:

• Reduce data complexity

Hundreds of programs with thousands of interfaces are used in a typical firm. This maze of networks can easily tangle you up. However, you can readily manage the intricacies of networks with an integrated data platform, which streamlines connections and ensures uniform data transmission.

• Increase the availability of data

Employees can easily retrieve, inspect, and evaluate data when it is integrated into a single platform. Moreover, it is much easier to update data and communicate outcomes when data is freely accessible, which leads to better knowledge-sharing, innovation, and collaboration.

• Smarter decision making

Integrated data allows users to use data flexibly in internal systems while maintaining transparency. Therefore, you'll be able to make quick and informed decisions on projects and business processes.

• Integrity of data

Integrated data management aids in the cleansing and validation of data. Your company data should be reliable, free of errors, duplications, and inconsistencies. Data can be made more relevant with the help of a good integration strategy.

In a nutshell, data integration benefits everything from real-time information delivery to data enrichment and from customer data analytics to business intelligence. And if you wish to take your business notches high, you should consider partnering with a reliable data integration company. And one such company is Needl ai, which provides best-in-class integrated data management solutions by organising your data into a valuable form and increasing overall productivity.