13:23 02 December 2019
Businesses rely on analytics to understand their target consumers better. Computers analyze a huge amount of data (big data) in a fraction of the time and cost typically devoted to market research and come up with more informative and useful results to help businesses reach their goals.
Computers, the Internet and the World Wide Web, and the interactions of people with these systems generate a large database of consumer patterns, preferences, and trends. Analysis of big data provides businesses with the tools and information necessary to understand their current and potential customers, fit their products to different markets, and provide a variety of products, services, and experiences for consumer satisfaction. It allows them to stay ahead of the competition.
Big data processing leads to new business opportunities. Today, you can find companies that offer analysis and aggregation of industry information.
The information is in real-time, which is crucial in the aggressive pursuit of new business directions, the adaption of marketing and advertising strategies and campaigns, and the development of enhanced products and services to capture consumer interest.
You need big data analytics to serve your customers better. But how do you process big data, handle the analytics, and use them for your business?
This is where Hadoop comes in. The tool is a combination of open-source procedures and programs which you can use freely as the anchor of your big data processing. It consists of four modules:
Hadoop is instrumental in helping corporations make business decisions according to the extensive analysis of several data sets and variables. It has the capability to process large amounts of unrelated data to provide a comprehensive analysis of risks, opportunities, business operations, and existing consumers. The process can be done in-house, which is another advantage.
You can tune up the Hadoop performance to achieve better results. It is vital to have a Hadoop administrator who is familiar with the different hardware specifications such as the capacity of the RAM, the number of disks available on the data nodes, the number of virtual and physical cores, the number of cores of the CPU and other computer hardware. What is good about Hadoop is that you do not need expensive computers to make it work, which is a plus factor for enterprises that need data analytics but need to save money as well.