Everything You Need to Know About Data Integration

Fremont, CA: The process of combining data from various sources into a single, unified view is known as data integration. Ingestion is the first step in the integration process, which includes steps like cleansing, ETL mapping, and transformation. Finally, data integration enables analytics tools to generate effectively, actionable business intelligence.

There is no one-size-fits-all solution for data integration. Data integration solutions, on the other hand, typically include a network of data sources, a master server, and clients accessing data from the master server.

In a typical data integration process, the client requests data from the master server. The master server then collects the necessary data from internal and external sources. The data is extracted from the sources and combined into a single, cohesive data set. This is returned to the client for use.

Let us look at an example of an analytical use case. A single report without unified data typically requires logging into multiple accounts, on multiple sites, accessing data within native apps, reformatting, copying over the data, and cleansing, all before analysis can take place.

The importance of data integration is highlighted by the fact that all of these operations must be carried out as efficiently as possible. It also demonstrates the significant advantages of a well-thought-out approach to data integration:

Improves Collaboration of Systems

Employees in every department — and sometimes in dispersed physical locations — are increasingly requiring access to the company's data for collaborative and individual projects. IT requires a secure solution for delivering data through self-service access across all business lines.

Furthermore, employees in almost every department are creating and improving data that is required by the rest of the business. To improve collaboration and unification across the organization, data integration must be collaborative and unified.

Time-Saving and Increases Efficiency

When a company takes steps to properly integrate its data, it significantly reduces the time it takes to prepare and analyze that data. The automation of unified views eliminates the need for employees to manually collect data, and they no longer need to create connections from scratch whenever they need to run a report or build an application.

Furthermore, instead of hand-coding the integration, using the right tools saves the dev team even more time (and resources overall).

All of the time saved on these tasks can be put to better use, with more hours set aside for analysis and execution to help an organization become more productive and competitive.