The buzz around Big Data as with any emerging and potentially disruptive technology is only growing and enterprises are as usual wondering how to make sense of all the hype surrounding it.
What is Big Data and why is it so critical? In today’s connected world, there is a surfeit of data being churned out from multiple sources, both structured and unstructured such as information from enterprise applications, social media, Internet and mobile. And the pace at which this is happening is only accelerating — it is said that the available data globally today is doubling every 12 months and is expected to only increase further.
The scale of this data has led to the apt coining of the term ‘Big data.’ The sheer volume and variety of data often running can be overwhelming for enterprises, which are under pressure more than ever to take informed decisions and respond in quick time. So, how can enterprises wrap their arms around this behemoth? This is where Big Data analytics steps in.
Big Data Analytics Across Industries
It is evident that enterprises need to maximize the information and knowledge that they can access to stay relevant in today’s hyper-competitive environment. And here’s how Big Data analytics can help across diverse scenarios. A common example is that of a retailer being able to sift through tonnes of consumer data to derive insights on shopping preferences and direct targeted campaigns. This can even be extended to capture the personal preferences and likes of the shopper and provide customized offers, leading to increased hit rates and revenues. This is a win-win situation for both parties as the consumer gets information and offers that he is interested in and the retailer enjoys revenue growth and potential customer loyalty as well. Big Data analytics does not have to adopt a big-bang approach all the time and is equally useful and effective in behind-the-scene scenarios for retailers. It can be used for a dramatic reduction in processing time when comparing product information, which resides across multiple data sources. Analyzing data allows a retailer to make intelligent decisions and helps gain a competitive edge.
Big Data analytics has immense potential in the field of healthcare too. Imagine if a hospital is able to go through its patient records and identify patterns in diseases. This can enable doctors to detect the onset of a disease much early on and the benefits of such an approach cannot be overstated. Throw in lifestyle data to gather additional insights and the possibilities are simply mind-boggling. Obvious gains are decreased mortality rates, better quality of life due to accurate prognosis, diagnosis and treatment, and lowered insurance costs. However, the challenge will be in overcoming regulatory and patient confidentiality issues.
Another example is from the telecom industry. Mobile connections are expected to exceed 6 billion globally and in India there are close to 750 million subscribers. In this highly connected world, the amount of data available is colossal and telcos can cleverly mine this data to their advantage. The biggest impact can be experienced by studying subscriber persona and usage patterns and using that intelligence to devise targeted marketing campaigns. The analytics can also help telcos determine what additional services are likely to find favor with subscribers and offer them appropriately. This also provides opportunities to offer value-added services such as location-based services leading to better customer service.
The examples discussed give a glimpse of how Big Data analytics can help enterprises concretely and have a tangible impact on business results. However, before embarking on this path, enterprises need to evaluate their business landscape and options available that can best suit its context. This is necessary to avoid any costly missteps. As in anything else, implementation holds the key.
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