By Boomi
Data is the currency of modern business. For most companies, the more data you collect, the more accurately you can predict what will happen next.
But the average enterprise organization uses hundreds of applications across multiple business units. This siloed structure for collecting business data provides a fractured, incomplete view of what is happening within the organization.
When combined with manual data collection methods, teams are left to work with incomplete or inaccurate data. The results can range from inefficient business processes to costly missteps due to business decisions based on bad information.
Breaking down these data silos and creating a unified view of the entire organization’s data requires a data integration tool. Read on to learn more about data integration tools and how more advanced application integration solutions can get more from your business data.
What is Data Integration?
Data integration is retrieving and combining data from multiple sources into a unified view. This creates a single source of truth that ensures everyone within the organization is working with the most recent and accurate data.
Each bit of data must be extracted from its source, transformed into a format compatible with the rest of the organization’s data, and then loaded into a central repository such as a data warehouse. The business then can use the data for analysis that informs reporting, improves efficiency, and guides future planning.
Data Integration Tools
Data integration requires specialized tools. After all, organizations collect and generate data using hundreds of different applications, and most have their own way of formatting and transmitting data. Intermediary tools are needed to ensure data transformation into the same format.
While many types of data integration tools exist, three varieties are commonly used.
Extract, Transform, Load (ETL)
An extract, transform, load (ETL) solution does what the name suggests. It extracts data from all connected sources, transforms it into a standard format, and loads it into a central repository like a data warehouse. ETL solutions are among the most commonly used data integration tools. They can be extremely thorough when gathering the data – including cleansing, identifying duplicate data, and presenting a clean, unified view.
However, ETL solutions present a few challenges. The data transformation process is more complex and therefore creates cleaner data, and that complexity requires significantly more technical expertise to achieve in the form of coding.
Data Replication
Data replication tools retrieve data from all available sources and copy it into a central repository. This data integration method offers users a more straightforward integration process while providing faster search because it replicates the data with far fewer technical requirements than integration with an ETL tool.
What data replication tools gain in speed and ease of installation, they lose in data hygiene. Data replication solutions do not transform the data – they simply replicate it. This can be useful for aggregating data into a data lake, but it presents problems if users require all data to be in a common format, such as for use in a data warehouse.
Data Virtualization
A data virtualization system does not extract data from its source. Instead, it creates a virtual version of the data from all available sources.
This approach can be faster to set up and require significantly less storage space than data replication or ETL solutions. However, it can also be much slower to run queries and is inaccessible when not connected to the internet.
Put Your Data to Work With Application Integration
Regardless of the tools a company uses, data integration is invaluable for gathering and storing data in a single, centralized location.
However, the benefits are primarily passive. Yes, it can be accessed as needed to perform analysis. Still, data integration requires human intervention to realize its benefits.
To get the most from data, organizations should consider application integration.
Application Integration Makes Data Smarter
Data integration is about moving data from multiple sources into a single location. Application integration takes this a step further, allowing data to move between the applications. This creates opportunities for applications to work together on their own through data-driven automation.
The benefits of application integration span the enterprise. Unified data that flows freely between applications can create an up-to-date 360-degree view of each customer, smarter and more efficient planning with ERP integration, and even enable AI-powered process automation.
Boomi Makes Integration Simple
Moving beyond data integration to a more holistic approach with application integration can benefit every aspect of your business. Boomi’s iPaaS solution offers a vast library of pre-built connectors that enable you to quickly and easily integrate your entire suite of business applications with a visual no-code/low-code process. And for connectors that do not yet exist, Boomi’s Quick Start wizard makes it easy to connect whatever you need into your integration ecosystem.
For more information on how Boomi can help you, contact our experts today.