Data integration is one of the most important concepts that enterprises should be dealing within 2013. Data integration provides the ability to extract information from source systems, and move the information to target systems that need to act upon the information in some way. As the number of systems have increased and become more complex, the need to dive deeper into data integration becomes more apparent and urgent.
Data integration allows us to approach the real-time enterprise, where all processes and systems have the ability to see into all other processes and systems, and react to optimize the business in (near) real-time. This concept has been mulled over for years, but has yet to become a reality for most enterprises.
So, as we progress toward this ideal, what are the issues that we should consider? How can we become good at data integration to the benefit of the business? For 2013, what are the data integration resolutions we should be setting? I have a few resolutions you should consider.
I resolve to create a holistic data integration strategy for my enterprise.
Most enterprises don’t have a core data integration strategy that spans all IT assets. They may have one for a group of systems, however, data integration has more value if the strategy and use of technology is systemic.
This means we understand most systems, including semantics, and we’ve mapped the exchange of information between them. Finally, have a roadmap to implement data integration solutions over the years, and define the value that this technology will bring to the business. It’s a tall order, but doable for most.
I resolve to create a data integration center of excellence.
If your enterprise is large enough, you should have a group of people who are dedicated to exploring the use of data integration technology within your enterprise. They are charged with creating the strategy (see previous resolution), as well as dealing with the technology providers, and testing the solutions.
In the long run, having a group like this will save you money. Consider the number of issues they will spot and resolve before they cost real money, as well as the strategic value of moving quicker to an enterprise where information exchange latency becomes less of an issue.
I resolve to understand and implement data virtualization.
Those who have complex and less productive physical databases around the enterprise will find that data virtualization technology provides a cost effective alternative to replacing those databases, or changing the structure of those databases. Indeed, data virtualization allows you to deal with physical databases using a structure of your choosing, typically, a better representation of the business.
As time goes on, data virtualization will become more important to the data integration strategy, and a sound tool in the IT technology arsenal. In 2013, you should get ahead of this technology and understand the proper use.
I suspect that 2013 will be the year of change. We will see more movement to the clouds, more movement to big data, and the need to driving information exchange between then. Data integration technology will have to be a large part of that mix.