Part 1 of a multi-part series on the essential interwoven nature of Business and Modern Data Integration
Forward-moving businesses and their data needs comprise a whole new world that is constantly changing. This new data-smart world is built on expanded approaches to data integration that have become known collectively as Modern Data Integration. If businesses want the right kind of data to underpin advanced analytics processes or to create multi-dimensional views of customers, data integration must be pursued as a strategic function that aligns with business objectives.
Most organizations have entered the digital realm, where various aspects of business increasingly incorporate cloud, social and mobile as important platforms. As the usage of these platforms grows, we see more changes in both business and customer behavior. To perform well in the digital realm requires an elastic organization.
Elasticity, both as business and technology infrastructure paradigms, enables organizations to tap into dynamic business models, decision-making processes, and technology mechanisms to strengthen responsiveness to any situation. To empower enterprise elasticity, organizations have to commit to continually improving data gathering methods, analytics approaches, business processes, and bi-directional connections between the people of the organization.
Vital data needed by organizations frequently is found not only outside the enterprise data warehouse, but outside the enterprise. Businesses are pressed to recognize the value that can come from integrating data from a variety of sources. Data management and data integration solutions have been strongly challenged to handle continuous changes in data and how it's used, increasingly in real-time.
Modern data integration builds on technologies and processes that long have been part of the bigger world of data integration, beyond basic ETL functions. Practices like data quality, data profiling and data governance (also highly relevant to business users) comprise important capabilities that are central to reliable up-to-date data, no matter the source or structure.
Modern data integration offerings encompass interoperating multi-platform solutions (iPaaS and on-premises), as well as pure-play cloud and SaaS solutions, where the lines continue to blur between application and data integration. Today modern data integration stands as a critical endeavor that must be agile and business-responsive, directly underlying many initiatives that can make or break organizational success: analytics and decision-making; real-time processes to engender improved customer experiences; omnichannel and digital marketing; intelligent business automation; alignment with digital transformation -- and so on.
Newer technologies like graph databases and data virtualization have contributed to the metamorphosis of traditional data integration into modern data integration, as have concepts like 'good-enough' data quality and data mash-ups. Part of the metamorphosis is to provide access to business users, to give them more hands-on power for data usage and analytics. The metamorphosis also reflects needs such as real-time situational awareness analytics, frequently run as continuous processes. With these changes, modern data integration also takes on the burden of ensuring that business users are protected from the inherent pitfalls of concepts like 'good enough' data quality and data mash-ups.
For data integration solutions, the reality of modern data integration has been a work-in-progress for several years. Some solutions began with integrations designed specifically for cloud to cloud data flows, and then expanded to include cloud to on-premises.
