Data Architecture & Big Data
The concept of "Big Data" isn't really about the size of the datasets, it is about how it is analyzed. To take advantage of advanced analytics you need the right architecture, one that lets you make the decisions you need to make from your data and yet is able to survive and adapt to changes in markets and technology.
That means aligning different technologies to feed each other while providing you with the insights you need. Different kinds of analytics can require different architectural choices to support them.
Who needs Big Data?
"Big Data" has taken on a lot of hype and not every business problem has a "Big Data" solution, but the advanced analytics will have an important place in the future of many organizations. Is yours one of them?
If so, you will need a solid architecture that brings your data into line with your business strategies. One that protects you from future changes in technology and markets. One that lets you think less about your servers and where your data is and who can see it, and think more about how to make good decisions to run your business. A good data architecture means you know what is going on with your data at all times.
Companies go through multiple stages of maturity as they implement more sophisticated analytics, and the architecture needs to meet those changing needs as the company matures in its use of technologies and decision making methods.