Interpreting Big Data

The modern-day business can benefit from interpreting and sorting out relevant data generated from social and digital media, to improve marketing, operations and customer services.
Big Data and Analytics

By Vishal Soni, Big Data and Analytics Consultant at Advaiya

Big Data is all about the non-traditional ways of dealing with the modern digital data. We are surrounded by an ocean of digital data. It includes data stored in piles of well-structured databases residing with organisations, streams of data generated from active social networks, various understandable and non-recognisable signals generated by all sorts of digital equipment around us.

For any organisation, Big Data can be about identifying the right datasets from large amount of data commonly defined by the three Vs: Volume, Velocity and Variety; transforming them into readily consumable models; and then extracting meaningful insights for better business prospects. These insights can be used to improve different aspects of the business - from marketing and sales, to research and operations, and customer services.

Till early 2010s, many organisations adopted big data as an experimental tool. Today, when many of those organisations have started realising true value and benefits of Big Data, its demand has grown manifold.

Big Data technology has the potential to meet many promises including better decision making, higher customer satisfaction, customer retention, cost reduction, and many more. These unique benefits are drawing people’s attention towards Big Data, and a large number of organisations admit that Big Data is going to play an important role in their future business model and plans.

Emergence of new trends related to implementation and application of Big Data seem to propel its adoption in newer areas of businesses. Let’s take example of Automation Platforms, or wearable devices and sensors.

Automation Platforms: Till date, Big Data set up largely involves huge infrastructure and technical skills. To extend the scope of Big Data to non-technology centric organisations, several automation platforms (cloud-based platforms, SaaS or similar) could emerge to make this technology directly consumable by non-technology centric organisations without much investment in skills and infrastructure.

Wearable Devices and Sensors: With the advent of Internet of Things (IoT) wearable devices and sensors has already become primary objective for the next generation of device manufacturers. Big Data capabilities could be used to boost their performance further, helping them even more useful for consumers.

How and where to get started: While many organisations have been early adopters of Big Data, there are many new companies that want to check if Big Data technology is feasible for their business or not. In this regard, the first step for most organisations is to try to identify how they can leverage Big Data for their business. Organisations often go for Proof of Concept (POC) to see if something meaningful could turn out for their business.  Many organisations also consider cloud-based SaaS and PaaS offerings on pay-as-you-go basis for getting familiar with this concept without making any huge initial investments or upfront costs.

According to analysts, organisations that embrace Big Data make more informed decisions, develop better strategies, handles risks better and reap good financial gains. Some common usage scenarios of Big Data are:

·Analysis of customer data for identification of patterns, and running marketing campaigns based on these patterns.

· Sentiment analysis on Facebook and Twitter data to determine what are people talking about your product or brand, and make decisions related to improvement and intervention.

·Optimise inventory across various warehouses and delivery channels while tapping into right marketing promotions based on customer sentiments and market trends.

Let us take an example of effective use of Big Data in retail Industry: Big Data enables clients in the retail Industry to track and better understand a variety of information from many different sources (i.e. CRM, AdWord/AdSense analytics, inventory management system, e-mails, transactional data, sensors data etc.). Industry can identify the current trends, re-order supplies for hot-selling items, adjust the prices in real time and also manage and control item distribution across different stores to channelise their sales in effective manner. This provides retail industry with entirely different perspectives of looking towards the datasets available at their disposal. By collating their organisational datasets with social media data streams, they can also use it for better sales predictions, driving relevant campaigns to suit masses of their profitable customers and ensuring customer satisfaction.

For Implementing Big Data, organisations will require multiple skills including distributed system administrators, parallel and distributed application developers, and most importantly, data analysts, or data scientists. And increasing global demand for such skills could really mean shortage and limited availability of such talent. In India, which is a hub for outsourced technology services, the scarcity of these skill sets is particularly worrisome.

While Big Data concept is gaining popularity, data privacy and security remain a major challenge for organisations looking towards implementing Big Data. Big Data technologies usually leverage personal and business data collected from several sources, which are stored across different systems and access from various remote locations using different toolsets. These all activities carry a huge risk of exposure of confidential data and also poses threat of non-compliance with regulatory norms. Another major challenge is finding the right skills. Developing the big data talent pool and then utilising their potential to help drive the organisation towards successful big data implementation is challenging.

As discussed, Big Data offers several advantages like cost reduction, better decision making, higher customer satisfaction, customer retention and many more, that are drawing people’s attention towards big data. In fact, the immense potential of Big Data has capability to transform almost every aspect of business, including new product development, production, marketing, sales, customer relationships, process optimisation etc.

Like every other technology, Big Data also has several positive and negative aspects. The organisations that are able to tame this wild elephant and use it to drive their businesses effectively would have better future aspects in longer run.

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