More and more companies across various industries are beginning to move away from more traditional data warehousing options such as storage area networks. Companies are looking for more distributed, clustered, or scalable storage.
Big Data is math, not magic. It is science, not sorcery. And, because Big Data is about quantifying, you need to have a protocol in place: ways to measure your results, to catalogue and store your data, and ways to move that data from raw information to actionable intel. We all know what a sales pipeline looks like, but what should your Big Data pipeline look like, and how should it operate?
As more and more companies reap the benefits of Big Data, it will continue to become increasingly vital for businesses to look for the competitive advantages Big Data can offer them. And, while that’s a smart business strategy, one step in that process must be to consider how to prepare your business to deal with the challenges Big Data can present.
When we read about Big Data, it’s as if writers act like it is the “method of the future,” as if companies are not already implementing and benefiting from the Big Data revolution. The reality is, Big Data has already been here for some time, and the reasons why other industries are beginning to take notice is because it has been so successful for others.
While it’s true that nothing is absolutely foolproof, and certainly impregnable – after all, people really did escape from Alcatraz – there are many steps you can take to maximize security and minimize potential risks. One way is to follow the series of steps you have seen recently at tech sites like CNET and consumer sites such as Mashable.