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What is Data Integration and How Does It Work?

By |2021-02-23T23:28:17+00:00March 17th, 2020|

Most businesses nowadays use a variety of data management systems (ERP, CRM, SCM, etc.) and each system comes with its own data formats. Consequently, interoperability is one of the key challenges that businesses face whenever they want to use data from different source systems. Data integration can help solve this problem.

The process of acquiring data from different sources into a single, consolidated view is termed as data integration. It starts with data ingestion, following which the data is transformed and loaded into a consolidated database. Once all the data is integrated, it paves the way for analytics tools that help produce actionable and effective insights.

This blog delves into how data integration works and explores its business benefits.

How Does Data Integration Work?

To help you understand how  integration system works, let us illustrate with an example. Suppose there is a company called ABC Corporation that sells a cloud-based software for customer relationship management. ABC uses various systems to run its operations, including:

  • Google Ads for customer acquisition
  • Salesforce for sales data management
  • Google Analytics and Hotjar for tracking user activity on their website
  • MySQL database for storing user information
  • Quickbooks for expense management

Each system stores its own repository of information related to ABC’s operations. But because each data storage system is different, the same customer may be spotted in different ways across the various data sets. Therefore, for getting a 360-view of their business operations, ABC needs all the data in a single place and unified format.

Here is how this disparate data can be integrated into a single enterprise repository:

  1. Data extraction is performed to collect data from the heterogeneous enterprise systems into a single database at a staging server. This is known as the extraction process.
  2. Data from each source will be transformed, cleansed, and aggregated as required to ensure that it is stored in a consistent, universal format. This is known as the transformation process.
  3. The converted data is then written into the destination system, which can be a data warehouse, database, or a data lake. This unified storage system provides a single source of information for ABC’s business operations. The last step is known as the loading process.

The process outlined above is known as ETL (extract, transform, and load) and most data integration systems involve one or more ETL pipelines. An ETL pipeline can be prepared by writing manual code but this can be a complex and cumbersome task, especially when dealing with large data volume and non-relational databases.

Therefore, it is recommended that you make use of enterprise-grade data integration platforms, such as Astera Centerprise. These data integration solutions come with a variety of built-in data connectors (for ingestion), pre-defined transformations, and built-in job scheduler for automating the ETL pipeline. These tools make data integration easier, simpler, and quicker, while reducing the dependency on your IT team.

How Data Integration Benefits Businesses

Data integration is an essential part of various analytics and data management systems. Now that we have understood how data integration works, let’s take a look at some of the key areas where it plays a vital role:

Business Intelligence (BI)

Business intelligence is the process of analyzing data to make better business decisions. A pre-requisite to using BI tools is that you need to have structured, cleaned, and consistent data that is ready-made for analysis. Data integration makes it possible to get access to this data and visualize operations from a bird’s eye view.

Data Warehousing

Data integration initiatives are often taken to create a data warehouse or data lake, that combines data from various sources into a single relational database. The data warehouse gives a 360-degree view of the enterprise data, which can then be used to generate reports, gather analytics, and retrieve data from a single system.

Master Data Management (MDM)

Master Data Management (MDM) is about providing a single version of truth to business users. It ensures when you are talking about a customer, let’s say XYZ, then it is the same customer that is referenced to in the sales, marketing, and CRM systems. For enforcing the security policies and guidelines that are a part of MDM, data administrators first need integrated data that is unique, structured, and consistent.

Types of Data Integration

There are several types of data integration processes, and the one you should choose depends on the size and requirements of your business:

  • Shared storage integration is the most common approach used for integrating data. This involves an ETL pipeline that copies the data from the source system and stores the consolidated, structured data in an integrated system. This is the opposite of uniform access data integration because it follows the principles of a data warehousing solution (which is the desired outcome of most data integration tasks).
  • Uniform access data integration focuses on creating a front-end view of the integrated data rather than physically moving data. In this approach, data still lies within the source, but the application makes it look consistent and structured when the user accesses it. This is beneficial for organizations that want to use object-oriented database systems for data integration.
  • Manual data integration is a process where individuals manually collect data from various sources (by querying or writing codes) and then combine them into a single database. This is a time and resource intensive process, and requires constant monitoring to prevent errors.
  • Middleware data integration involves a middleware application that normalizes the data from various sources and brings it into a master database. Often, middleware is used when a data integration system cannot directly access data from the source system.

Conclusion

Having full access to the data sets from various source systems is critical for businesses and this is made possible through data integration. Data integration provides a competitive edge by enabling businesses to acquire accurate analytics that drive better business decisions.

Astera Centerprise helps enterprises manage their integration flows in a code-free, visual interface. To experience the power of integration with Astera Centerprise, download a free trial version and see for yourself!