Data integration has become the flagship of many IT projects run by multiple organizations across the world. However, the road to creating an integrated business environment, where data accessibility, collaboration, and connectivity holds prime importance, is set with thorns. Data integration entails many barriers or challenges, and it keeps getting more difficult each day.
It’s no surprise, considering the proliferation of devices that consume and generate information, the explosion of cloud-based solutions, and information exchange between systems and between systems and humans. The challenges are multifold since the volume of data has been increasing substantially. As per IDC, the volume of data will expand to reach a magnanimous number of 40 Zettabytes (1 billion Terabytes equals 1 Zettabyte) by 2020, out of which almost 90% will be unstructured.
Such an enormous rise of data coupled with change in the supply and demand policies has made data integration extremely challenging, and the barrier has become insurmountable with legacy data integration technology.
Generating custom code is onerous. Enterprises must address four steps during data migration as well as the integration process:
For quite a long time, IT teams have taken care of data integration by writing volumes of custom code. With the explosion in SaaS applications, the rise of big data, the emergence of new products and the Internet of Things, and surge in mobile devices, such difficult task has grown even more complex.
The burden on IT has increased, and so the integration backlog has become difficult to deal with. The time taken to deploy a tactical warehouse solution has increased substantially from days to months, impeding IT productivity. Apart from that, the sky-high costs to manage as well as maintain integrations are overwhelming for most IT enterprises.
Luckily, the days when IT teams needed a hundred hands to create an extract, transform, load (ETL) process and then maintain it by writing more code are long gone. Modern integration solutions eliminate the need for custom coding and allow enterprises to deploy data integration 10X faster.
Modern data integration platforms offer flexibility to users with features such as pre-built connectors, shared templates, and more. These platforms allow IT teams to facilitate governance activities, ultimately increasing their productivity.
Moreover, since the embedded application connectors are always up-to-date, IT firms need not update integration every time it is updated. As a result, a lot of time, money, and resources are saved.
No doubt modern integration solutions streamline data integration processes, but not all these are created equal.
While a few offer quality point-to-point cloud app integrations, others are better at transforming large and complex data into a data lake for advanced analytics.
While some provide self-service, others call for resources to hand-code APIs.
While some are a befitting option for meeting the requirements of the current market scenario, others help companies foster a bright future by embracing digital transformation.
You can weigh your options and identify what your specific needs and end objectives are, and then match them to the most relevant solution.
If you’d like to experience a modern integration platform for your business, grab Adeptia’s free trial and see how we can add value to your business.