Big data has become vital for businesses in today’s competitive world. Several companies are using Big Data analytics to generate insights that can be valuable for them. The mass prevalence of Big Data analytics and its increased utilization, has created a situation where not using it has become equivalent to business suicide. Most CEOs and CTOs realize that if they don’t utilize it, then their competitors will get ahead of them. Therefore, funding Big Data analytics has become a priority for most.

High Processing Requirements for Big Data

Big Data, as the name implies, is really big when it comes to size. Traditional computers take a long time to run analytics on such a large data set, which leads to high power consumption and also delays insight generation. Therefore, fast solutions for processing millions of transactions per second are required to get the job done on time.

Expedite Insight Generation with Superfast Processing

Superfast processing solutions are available on the cloud platform to cut short the time it takes to generate insights from Big Data. However, there are certain important features that your superfast processing solution needs to have for it to be effective in a business environment:

1. Security – Security is not the first thing that strikes one’s mind when we talk about fast data processing, however, in a real business use case, it is probably the most important. Big Data comprises business-critical information that you simply cannot afford to lose. Hence, it is vital to partner with a vendor who takes security seriously.

2. Up scaling capability – Generally, Big Data processing takes place on a huge scale. And, at any time that scale may need to be increased to ensure generation of valuable insights. Without scaling capabilities, you will not be able to harness the real value of Big Data. Hence, always select a vendor that has a big enough operation and many high-powered systems at its disposal.

3. In-memory and parallel processing – As mentioned earlier, traditional computers are not good enough for effective processing of Big Data. Therefore, you need to partner with a company that uses the latest technologies like In-memory and parallel processing. In-memory processing makes use of RAM instead of HDDs for storage, which makes fetching of data extremely fast. Also, parallel processing solutions that integrate TPUs are a must-have for any worthwhile Big Data processing venture.

4. Redundancy for data safety – When you offload your data to a vendor, you need to be absolutely sure about its safety. The best way to ensure safety is by choosing a vendor that stores your Big Data at multiple datacenters. So, when there is natural disaster at one datacenter, your data and generated insights stay safe at another location.

Big Data requires large data processing capabilities for generating insights that are valuable for a business. To ensure that you are able to exploit Big Data for maximum business advantage, it is best to partner with a vendor who can offer security, redundancy, in-memory processing and fully-scalable computing solutions.

Author's Bio: 

I john martine freelancer content writer. I have written many article like real time data stream processing, processing large amounts of data, millisecond transaction processing, scalable solutions processing etc