Big Data and Analytics – The New Era of Information
Published on : Saturday 07-05-2022
Organisations must choose the right tool based on their need to process and analyse data, says Soundharyaa Nandakumar.
We are living in the generation of time where life is characterised and designed in accordance with a collection of vast amounts of far-reaching information and the terms Big Data and Analytics are frequently heard and spoken aloud now, than ever before. Big Data and Analytics became so very important that each and every aspect around the globe, starting from Geography to Rehabilitation has data collection issues due to increased diversified network types, solutions, etc. Big Data has changed the world in many ways, for instance, predicting customer behaviour. When we think of the term Big Data, we also cannot forget another popular term Social Network, which is more likely to be interrelated and interdependent, because most of today’s data is collected through social network platforms like Facebook, Google, etc.
Presently organisations use big data and analytics software and systems to make data driven decisions that can help them to reconstruct their business models, and business-related outcomes. In general, data analysts, data scientists, statisticians, and other analytics professionals work by collecting, processing, cleaning, and analysing greater volumes of structured data as well as unsorted data. Many different types of tools and technologies are used to support big data and analytics processes, for instance, Hadoop is an open-source framework for storing and processing big data sets, which are predominantly used in Sales and Marketing, and gaining operational efficiency.
There are four steps of big data and analytical process:
1. Data from different sources: Data professionals often collect a mixture of structured and unstructured data, where each organisation will use different types of data from different sources according to their own needs. For example, Internet stream advertisements, web search logs, text from customer email, mobile phone records, etc.
2. Data preparation: Once the data is collected, it is stored in a data repository, because of which professionals must organise, segregate the data properly for analytical related interrogations.
3. Data cleansing: To increase the quality, professionals use scripting tools and quality software, which can find errors and inconsistencies.
4. Data Analysis: The processed tidied data is then analysed with analytic software.
When we speak about Big Data and Analytics, we also need to understand, Big Data and Data Analytics are two different terminologies which are often used in combination in the process of work. In simpler terms, the main agenda of big data is not in collecting it, but also in managing it and making sense of it. Big data helps in scrutinising data to unveil information such as invisible patterns, correlations, market progression, customer behaviour, etc., which can help organisations make better decisions; on the other hand, Data Analytics helps in the path of technologies and techniques, where technologies and techniques used in data analytics helps organisations to analyse data sets and collect new information (Table 1).
Big Data and Data Analytics as one structure often need data from both external and internal sources, such as weather data, data from third party information service providers, etc. In addition to those, presently streaming analytics applications are also becoming common in big data and analytical environments as it is useful in analysing the real time information or data.
Big Data analytics is also called Advanced Analytics, which is considered to be way better than the traditional BI (Business Intelligence) process of analysing data which is an old school method of data collection needing a complex environment, hands of duty from mere IT staff who does all the work.
Some of the use case examples which show Big Data are more effective than traditional BI:
1. Customer Property and Control – Data which are often collected from customers are tremendously useful in making companies realise the customer’s expectations to increase product value and meet the customer satisfaction, e.g., Netflix, Amazon shows refine the suggestion movie or series list based on the customer view list.
2. Advertisements – Past purchases, frequent page viewing histories can create self-generating digital ads for users on every level.
3. Risk management – Big data analytics can identify new risks from data patterns for effective risk management strategies.
4. Improved decision-making – Insights business users extract from relevant data can help organizations make quicker and better decisions.
5. Cost optimisation – Retailers may opt for pricing models that use and model data from a variety of data sources to maximise revenues.
From the use cases we can clearly see the advantages of Big Data and Analytical process, but we also need to make sure to know about the challenges involved in the process, as they are equally important:
1. Data accessibility – Since, enormous amount of data is collected, processed, cleaned which is also a complicated process, as the result of which it should be stored and maintained properly so that even an inexperienced user can access it
2. Quality assurance – Data maintenance always requires significant time, effort, and resources to maintain it.
3. Security – the complexity of big data sets present unique security challenges every time.
4. Right tools – due to enormous data sets available outside in the market, organisations must choose the right tool based on their need to process and analyse it.
Current trends in India
Use of Big Data and Analytics ensures high employment and helps people to connect with advanced technologies. In ‘A Study in Scarlet’ by Sherlock Holmes, it is stated that ‘It is a big mistake to guess before one has data’. Accessibility to his data has made him a celebrated expert investigator for his deductive thinking with complex analysis. In simple words, accessibility and availability of data have evolved leadership in all fields like science, medicine, innovation in the sense of volume, assortment, etc.
The Comptroller and Auditor General (CAG), India’s largest reviewer has formulated ‘Big Data Management Policy’ for divisions which are trying to encourage the use of data analysis to intensify their capacities in their respective domains. For instance, Reliance Jio is so far considered to be a tough competitor in the field of data abundance. Ever since their entry into the telecommunication industry, Jio has made even the illiterate person join Digital India.
The Government of India has been giving its continuous candid importance to Big Data, as it was the core of the Digital India campaign. During the peak of Covid-19, it also launched a free app, the AarogyaSetu, or Bridge to Health, to harvest mobile phone records, artificial intelligence, and big data to help identify individuals potentially exposed to Coronavirus through contact with other infected patients.
According to a recent survey it is said that current internet usage in India is second with the US in first place, and it also estimated that very soon India will become the largest smartphone-using population, changing the big data market forever, creating more changes and more opportunities for everybody in every aspect. It would also be totally unrealistic to say India is fully digitalised, but digitalisation and the use of big data has definitely expanded its wings wider than compared to last year, and will continue to expand.
Soundharyaa Nandakumar has done her Masters in Mechatronics and Cyber-Physical System in Germany and presently working as a Test Engineer, testing Vehicle Electronic Control Units in Connected Drive department. Her previous work experience as an automobile technician has given her a good understanding of how beautiful the car/vehicle is with intricate designs and unbelievable technologies inside. This craze and passion for cars made the decision for her to pursue a career in Automotive Technology.
In her own words, “I always compare cars to women, because we never know what is inside them, how mysterious they are with n number of technologies evolving around every day making them futuristic statements – just like women – undergoing many things in a day to be strong enough to conquer the world.”