For organizations that want to survive and thrive in the era of big data, data integration is a critical component for success. And as the number of data sources multiplies each year, the volume of data organizations are dealing with gets bigger, too. In order to capture value from all these sources, the data needs to be integrated.
To understand how to begin a large-scale data integration initiative, it is necessary to understand what big data is and what it means to integrate big data.
What Is Big Data?
Big data refers to a data set that is too large and complex to be useful without being processed by software. It is usually characterized by the three V’s: volume, variety, and velocity.
Volume refers not only to the amount of data that has been collected, but also to the number of data sources.
Velocity refers to the rate at which data is captured by the many data sources. For big data, this means data that is being captured at a rate too fast for it to be useful without automated analysis.
Variety refers to the variable and inconsistent formats in which the data is being captured. When data is captured in multiple formats, it has to be normalized in order to be useful in conjunction with the rest of the data that has been collected.
What Is Big Data Integration?
Big data integration is the process of connecting every data source to a central platform that provides users with a single, streamlined visualization of relevant data, trends, and other insights. Data sources that feed into a big data integration platform can include CRMs, ERPs, marketing automation software, factory floor sensors, and IoT devices.
Another key aspect of big data integration is the automation of processes. By removing the need for human intervention, the central platform through which all data sources are integrated can be used to automate actions in one application or device based on data received from another.
Big data integration also enables a dismantling of silos within an organization. The centralized nature of the data and the ability for any system to access the organization’s full data set means every department has immediate access to whatever information they need, whenever they need it. Rather than submitting requests for data that will likely be outdated by the time it is received, a user can access the data directly.
How to Integrate Big Data with iPaaS
Integration is the cornerstone of generating the efficiencies and insights organizations need to excel as information proliferates around them. Integration using an iPaaS solution provides a flexible and high-performance infrastructure that can tackle immediate needs and also grow as the business builds its big data capabilities.
The iPaaS integration process works like this:
- The entire collection of data sources is fed into a master server.
- The data is transformed into a uniform data set so it is readable by all other endpoints.
- The data set is stored in a centralized location.
- Additional data sources are added without the need to create custom connectors.
Once this process is complete, users can access whatever data they need through a customizable dashboard. The big data stored within the iPaaS system can be analyzed and acted on automatically by applications integrated into the platform or manually by users via the dashboard or by other means.
Boomi Powers Big Data Integration
With Boomi’s iPaaS solution, you can quickly and easily meet any data integration need, from the smallest data challenge to the largest big data initiative.
To learn how Boomi can help your organization capitalize on big data, please contact our integration experts today.