As dependence on data grows, business world is waking up to a new reality. Entrepreneurs have realized the potential of data and have started capturing all the data streaming in and out of their systems. But as vast troves of data accumulate, the importance of big data processing technologies is rising.
The Significance of Big Data Analytics
Big data analytics has become vital for companies because of its immense potential to provide insights. These insights lead to quicker and faster decision making, which helps a company exploit market trends at the right time. The importance of timing can be elucidated with the following example:
Your telecom company offers wireless modem/router to its subscribers receives multiple calls, in which, customers are complaining about its short wireless range. Most customers are enquiring if they can add a high-powered router from a different brand to the modem for increasing the range. Now, your customer services reps are making notes and inputting these queries in the CRM. However, as your call center process is spread over multiple departments, no TL/manager is able to spot this widespread trend. In this case, big data analytics can process the vast amount of data instantly (via real-time processing) and make you aware of this very specific customer requirement. In turn, you can either start selling your own router or supply a more powerful modem/router (as upgrade at an additional cost) that addresses this customer need.
Such an initiative can be really helpful as it prevents you from losing out on revenue to your competitors and other vendors. And, it can only be made possible by processing large amounts of data using fast and real-time processing technologies.
The Real Value of Big Data Processing Technologies
Big data processing technologies need to meet certain requirements for them to be valuable for a company. Below are some essential requirements:
- Fail factors management – A processing system, no matter how fast it is, won’t be able to provide the desired results if it does not manages fail factors well. Due to unpredictable failures, your insight generation process can become abrupt. Such inconsistent processing performance completely negates the benefits of fast and real-time processing as you simply cannot rely on it for critical and timely insights.
- Auto scaling, self-healing and high availability – Self-healing in big data processing technologies can be implemented with auto scaling. A fast processing system based on the cloud that replicates data across different datacenters can shift the load from one server to another via load balancing. The balancing of load is extremely important as it prevents the server from crashing and ensures high availability of resources for data processing.
- Server and database managers – Although hardware resources are crucial for big data processing technologies, the importance of human resources cannot be underestimated. To ensure worthwhile results, it is important to have a team of DBAs, data analysts and program managers looking after the performance of servers. Latest database platforms that are used for processing large amounts of data in real-time like MemSQL require considerable expertise and hands-on experience.
At Superfastprocessing, you get access to services that always meet the stipulated deadlines. With over 100 seasoned engineers and managers presiding over the operations, we always perform our clients’ work according to SLAs and maintain the level of quality at all times.