Information in the form of data has become invaluable for making informed business decisions and for formulating future strategies. Known as Big Data Analytics, it has a huge potential in bringing about qualitative improvements.
Ever since the advent of computers, the word ‘data’ has been irrevocably linked to these. With the advent of the internet, computers are now handling a very wide array of data comprising text, emails, sounds, images and videos, all stored in binary form. The phenomenal growth of the web and entry of smartphones has led to a huge surge in data creation, which now includes log and web activity records. The entry of (Internet of Things) has brought in a very large number of sensors, which in their routine operation also add to data. A huge volume of applications and use of data cover the entire spectrum of operations of an organisation.
How big is Big Data?
When data size exceeds 100 terabytes (1 terabyte is 10 to the power of 12), it is referred to as Big Data. The data gets generated from social media platforms: such as tweets, likes, emails. Machine data from CCTVs, sensors of IoT, medical devices. Transactional data of e-commerce, credit cards. We create a record or data when we make a web search, post a mail, tweet, message on WhatsApp, connect a device to IoT, etc. According to Eric Schmidt, Executive Chairman of Google, “there were 5 exabytes of information created between the dawn of civilisation through 2003; but now the same information is created every 2 days.”
Handling Big Data
With the availability of so much data, organisations began looking for options to store, retrieve and utilise the data in future. Fortuitously, the concept of cloud computing came in handy. Cloud computing refers to the practice of using a network of connected remote clusters or groups of servers, somewhere in the ‘cloud,’ to make storage available. This arrangement resolved the problem of finding storage capacity.
How to access and process all this data? In 2004, Google developed ‘MapReduce,’ a framework for search optimisation across multiple servers. Incorporating this, a Yahoo employee, Doug Cutting, designed a software project for processing high-volume data and called it ‘Hadoop’. This software framework is now widely in use for processing Big Data.
BIG DATA ANALYTICS
Processing Big Data extracts historical trends, patterns and correlations, market trends and customer preferences under a variety of situations or conditions. Such information becomes invaluable for making informed business decisions or for formulating future strategies. Since these are now based on actual data, they find ready acceptance. This is simply referred to as ‘Big Data Analytics.’
A typical example of this analytics is from Amazon. It analyses each one of its customers’ purchases, items on shopping cart/wish list, products reviewed/searched for most, what else other customers who bought the above items had bought… Then it shows items accordingly and all these analyses are a set of recommendations for additional purchase. These impulse-suggestive recommendations have reportedly helped to boost Amazon’s revenues annually by 30 per cent. Similar personalised suggestions are offered on YouTube, Netflix and Google.
The weather forecasting sector takes past weather and climatic conditions data and superimposes live feedbacks from weather satellites to predict weather. Medical Health Record is yet another ambitious project for compiling and storing all information regarding an individual’s medical test results, X-ray reports, surgery records, therapies, medicines, etc. for reference by health care providers.
Banking, Agriculture, Pharma, FMCG companies and Education are other sectors that use Big Data Analytics to get insights into the behaviour and needs of the communities they serve and fashion their actions to suit.
Big Data Analytics is an interesting and upcoming area that has huge potential to bring in a qualitative improvement across industries. It should, therefore, be no surprise to hear of its deployment in many more areas in the coming years.
