If we had to choose one thing that has changed the rules of the modern business world the most, it is big data. While it involves processing staggering amounts of information, the rewards are undeniable. That’s why companies that want to stay competitive in the 21st century marketplace need an effective data strategy.

Analytics, the process of finding, interpreting and communicating meaningful patterns in data, is the next logical step after data processing. While data processing changes data from one form to another, analytics takes these newly processed forms and makes sense of them.

But regardless of which of these processes data scientists use, the sheer volume of data and the analysis of its processed forms require greater storage and access capabilities, which leads us to the next section!

The future of data processing
The future of data processing can best be described in one short phrase: cloud computing.

While the six stages of data processing remain the same, cloud technology has provided an impressive advancement in data processing technology that has given data analysts and scientists the fastest, most sophisticated, cost-effective and efficient methods of processing data today.

The cloud allows companies to consolidate their platforms into one centralized system that is easy to work with and adapt. Cloud technology allows for seamless integration of new updates and upgrades to legacy systems, offering organizations tremendous scalability.

Cloud platforms are also affordable and serve as an excellent balance between large organizations and small companies.

So, the same IT innovations that created big data and its associated challenges have also provided solutions. The cloud can handle the huge workloads typical of big data operations.