What is Data Integration?

In 2020, it is definitive to argue that one of a company’s most significant assets is its Data.

Data integration involves collecting data from different sources, combining this data into a unified set that can easily be used for a predetermined business function, and enabling you to query and manipulate all of your data from a single interface and derive analytics and statistics. While the sources and types of data continue to grow, it becomes increasingly important to be able to perform quality analysis on that data.

Benefits of Data integration

Data integration is becoming more and more common, as numerous apps and companies race to meet consumer demand to have all of their data collected in one place and in a useful format.

From small businesses that want to spend less employee time creating reports, to large corporations taking a deep dive into an array of user statistics, data integration is indispensable for businesses that want to compete in today’s economy.

Here are the primary benefits of data integration offered to businesses.

Integrate data from multiple sources

Businesses are using tons of applications, systems, and data warehouses within your organization. Nevertheless, these data sources are disparate and siloed. A data silo, is a repository of data that is isolated. Generally, in businesses, this means that the information is under the control of a business unit or department and is not available across the organization. When systems containing valuable data are integrated across an organization, then the data gathered by one app or department can benefit the company as a whole, not just a team or individual.

Inter-system cooperation ensures that your company is free from information silos that benefit the few, and allow data gathered across the organization to be viewed and used by anyone who needs access to it.

For example, integrating data from multiple online stores can give you a more complete understanding of customer behavior and payment processing preferences.

Data integrity and data quality

Data integrity is an important element of data integrations. Data integrity is the assurance of the consistency and quality of the data through its entire lifecycle.
Nevertheless, most of the data is still of poor quality. Eliminating errors in data sets used for business intelligence and decision making is one of the primary advantages of data integration.

When data is gathered manually, then every tool, database and user account must be properly accounted for and set up prior to collecting this data, meaning that any data source overlooked or added last minute results in an incomplete data set as the end result. This also means that reporting protocols must be re-worked whenever a new data source is added.

When data systems are integrated properly, however, errors from overlooked sources do not occur and reports can be run and accessed in real time.

Save time and boost efficiency

When a company takes measures to integrate its data properly, it cuts down significantly on the time it takes to prepare and analyze that data. The automation of unified views cuts out the need for manually gathering data, and employees no longer need to build connections from scratch whenever they need to run a report or build an application.

Additionally, using the right tools, rather than hand-coding the integration, returns even more time (and resources overall) to the dev team.
When systems are properly integrated, collecting data and converting it into its final, usable format becomes a quick, easy task instead of a treasure hunt across your company’s data assets.

All the time saved on these tasks can be put to other, better uses, with more hours earmarked for analysis and execution to make an organization more productive and competitive.

Increase competitiveness

This is the most straightforward from all the other benefits of data integration.

Having a data integration strategy in place can help you to plan what actions you need to take to improve the accessibility of data both externally and internally, you will be able to influence many vital parts of your business. Yes, the overall goal is to generate more profit. An essential part of that is delighting your customers, so offering better services than your competition cannot be overlooked.

Tools for Data Integration

There are numerous tools available in the market that would help us query out the Data effectively since our Data is not going to integrate itself. To name a few, we have some Open Source Data Integration Tools, Cloud-based Data Integration Tools and the On-premises data integration tools.

Again, the question is that how to and which one to choose among those various tools available in the market.  The features you should look for in a data integration tool are:

A lot of connectors. There are many systems and applications in the world; the more pre-built connectors your Data Integration tool has, the more time your team will save.

Portability. It is important, as companies increasingly move to hybrid cloud models, to be able to build your data integrations once and run them anywhere

Ease of use. Data integration tools should be easy to learn and easy to use with a GUI interface to make visualizing your data pipelines simpler.

A transparent price model. Your data integration tool provider should not ding you for increasing the number of connectors or data volumes.

Cloud compatibility. Your data integration tool should work natively in a single cloud, multi-cloud, or hybrid cloud environment.

Business intelligence, analytics, and competitive edges are all at stake when it comes to data integration. That is why it is critical for your company to have full access to every data set from every source.

Simple data integration with Etlworks

Etlworks is an all-in-one, any-to-any data integration platform for all your ETL projects, regardless of the complexity, data location, format and volume. There is no code to write — with just a few clicks, Etlworks will extract your data from wherever it lives and get it ready to be analyzed, understood, and acted upon.

Etlworks offers a free 14-day trial. Give it a try today!

Author: Olena S.

Data Architect, University of Pittsburgh

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