Today, data is both the output and the fuel of companies. For many however, the process of becoming a data-driven organization is hindered inflexible systems that were created years and even decades earlier.
The ways data is being produced and accessed are continuously increasing. The Internet of Things resulting in continuous flows of data and enabling a better understanding of products, services, partners, and customers. Mobile technology is omnipresent, creating large amounts of geolocation and usage data. Analysis has become the lifeblood of organizations, and with it comes the need for terabytes and gigabytes of data.
With the wide variety of data flowing into organizations, the need for efficient data integration—combining data from a variety of sources to increase its value and usability—has never been more pressing.
There are a wide array of techniques and processes that can be used today to help organizations integrate this disparate data and gain a unified picture, such as replication, change data capture, extract-transform-load, extract-load-transform, data virtualization/federation, and others.
Data integration has been described as the essential link between information and insight. Businesses that ensure their various databases can communicate to one another are able to take advantage of information they are collecting.
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