7 CHECK POINTS TO FIND WHETHER YOU ARE READY FOR BIG DATA PROCESSING INTERNALLY

Whether you agree or not, you probably need to look at ways to explore big data if you need to sustain in the industry.

Today, there are tens of billions of new Internet-connected devices and these devices send huge amounts of data to cloud or server. And, this data – big data, is a gold mine of information for business.

Recent research shows that the amount of data collected by enterprises continues to grow at a rate of 40 % to 60 % per year. And hence, it is prerogative for enterprises to start getting into big data and processing it – eventually, use it for decision support.

Big Data is a very large set of data and it could be unstructured, semi structured or structured data. It is huge, complex and very tough to handle using classical processing tools. We need special framework to analyse those huge amount of data. Also, we need multiple expert resources too for analysing these data. So, before starting the big data processing, it is good to check that whether we are ready for big data processing or not. Now, let’s look at some of the prerequisites – including people who needs in big data processing. Some check points before starting big data processing are:

Big Data lab – Big Data Lab is a dedicated development environment for experimentation within your current IT infrastructure with presence of big data technologies and approaches to process big data and analytics.

Though it is not mandatory, it is good to set up a big data lab to start big data processing. Is your big data lab setup ready to process the different steps of big data processing? If not then you are probably not really ready for processing big data. All the operations during processing will be occurred with the help of this lab. So, each and every component of this lab needs to be ready for big data processing.

Data Integration Capabilities– When we say data integration, it is essentially a process of connecting data to big data lab from different data sources. This phase or step is for connecting the data from its source to the technology – your big data lab. For this step, we need machine setup that can be used for this connection and the expert professionals who can perform data integration.

Data Development– In this phase, data is collected and arranged. Here, we may need a distributed database like HBASE for collecting big data and the developers to handle this operation with suitable tools and store the data in appropriate database according to the needs. Data developer needs to make the data readable for analysing tools like Hadoop, R, SAS, etc. All the necessary components for big data development and data processing to be ready in your big data lab with right skilled people should be available before data processing starts.

Data Analyst – To analyse big data, we need data analyst who can work on the data to find meaningful information. The role of data analyst is very important in the big data processing. Data analyst should be skilled i.e. know to apply different and appropriate analytic techniques for different types of problem. They should be experts of statistical and computational techniques. In short, we will need a team of analyst for this purpose. We must have a group of analyst having these skills before start processing.

Visualization experts– To visualize the analysis results, often we need visualization experts. The visualization experts must have ability to turn statistical and computational analysis into presentable graphs, charts and animation. They need to be expert in virtual art and design – more over business requirement. We may need these experts during presenting the analysis report to the client because client may not understand the big data table or any other technical things. So, we need to show them results in graphical or animated representation – it could be a simple dashboard. To be short, before processing big data you should have some good visualization experts.

Business Analyst– These are people who have knowledge of different area of business i.e. your business, industry, benchmark, pricing, marketing, risk analysis, finance, etc. They need to have ability to ask right business questions and a drive or orientation towards business objective of big data processing. If you have business analyst with these quality, then you can get a reason to analyse big data.

Data Scientist– In order to run the entire big data project and drive the big data processing exercise into meaningful and fruitful one, it is good to have a data scientist. Data scientist is an expert in the entire big data value chain with hands-on experience in big data tools and technology. Though it is a costly proposition to on-board a data scientist having end-to-end big data capabilities, you can consider hiring a consultant who can perform this job and get the project done.

To summarize, it is good to build big data processing capability as big data can help drive proactive business decisions. Once you have all the seven factors and resources ready, yes – go ahead and start exploring big data; and get prepared for a big leap in your business and growth.