Big data is a volume of structured, semi-structured, and unstructured data whose size is beyond the potential of typical database processing applications to capture, store, manage and analyze.
Big data challenges have become more familiar in recent years because of the growth in Web 2.0 technologies and mobile computing devices such as smartphones and tablets. Because of its massive size and complexity, the majority of organizations are not able to handle this sort of information by using their current IT infrastructure.
With the rising trend towards large scale collection of Web content – including social media logs (for example Facebook or Twitter), Web clickstream (such as Google Analytics), geospatial information (such as cell phone GPS), among others – there is also a growing need for dealing with great amounts of data in a variety of formats, which requires new technology skills and expertise.
This challenge can be addressed by using the obtainable big data technologies that are emerging to make sense of enormous volumes of raw data — ranging from private customer transaction histories captured from companies’ internal computer systems and external sources such as social media feeds or government databases, to video monitoring via CCTV and other sensor networks. A handful of early pioneers have already effectively deployed large-scale solutions to reap the payback of big-data strategies.
Big Data has been widely renowned as a key differentiator in several industries—from healthcare, retail, banking, oil & gas, and telecommunications sectors.
Organizations are progressively investing in analytics and business intelligence applications that sustain more granular, real-time access to data. This presents a number of challenges around information governance, storage capacity, and compliance with regulations. Unfortunately, traditional technologies cannot adapt fast enough to meet these demands, make new sources of value, or satisfy the appetite for big data across an organization. As a result, organizations that want to use big data effectively must consider innovative alternatives.
This is why big data is becoming a peak priority for many organizations. It complements their existing investments in information technology, enables them to accomplish competitive advantage, and improves business intelligence. Their journey requires new skills, knowledge, infrastructure, and technologies. Finally, successful deployment of big data means aligning it with corporate strategy as well as identifying the right use case(s) that will generate calculable value for your organization today and into the future.
Top 7 Big Data Applications That Show Real Life Changes
1. Big Data in Retail
For retailers to thrive in this competitive world, they need to understand their customers in a better way. If they are aware of their customers’ needs and how to fulfill those needs in the best possible way, then they know everything.
2. Big Data in Healthcare
Big Data and healthcare are an ideal match. It complements the healthcare industry better than anything ever will. The amount of data the healthcare industry has to deal with is unimaginable. Smart wearables have gradually gained popularity and are the latest trend among people of all age groups. This generates massive amounts of real-time data in the form of alerts which helps in saving the lives of the people.
3. Big Data in Education
It is not only rekindling academic skills but also the non-academic ones such as interpersonal skills. Big Data is providing assistance in evaluating the performances of both the teachers as well as the students. Universities can even track the dropout rates of the students and are taking the required measures to reduce this rate as much as possible.
4. Big Data in E-commerce:
Some of the biggest E-commerce companies in the world like Amazon, Flipkart, Alibaba, and many more are now bound to Big Data and analytics is itself evidence of the level of popularity Big Data has gained in recent times. Big Data’s recommendation engine is one of the most amazing applications the Big Data world has ever witnessed. It furnishes the companies with a 360-degree view of its customers. Companies then suggest to customers accordingly. Customers now experience more personalized services than they have ever had. Big Data has completely redefined people’s online shopping experiences.
5. Big Data in Media and Entertainment:
Keeping a customer pleased is a lifelong journey for the media and entertainment industry. They must offer their customers new content to keep them engaged with their firm. The recommendation engine plays an important role here as well. Viewers these days need content according to their choices only. Content that is relatively new to what they saw the previous time. Earlier the companies broadcasted the Ads randomly without any kind of analysis.
6. Big Data in Finance:
Even before Big Data gained popularity, the finance industry was already conquering the technical field. In addition to it, financial firms were among the earliest adopters of Big Data and Analytics. Digital banking and payments are two of the most trending buzzwords around and Big data has been at the heart of it. Big Data is bossing the key areas of financial firms such as fraud detection, risk analysis, algorithmic trading, and customer contentment. (Most Successful Fintech Startups in India)
7. Big Data in the Travel Industry
Through Big Data and analytics, travel companies are now able to offer more customized travelling experiences. They are now able to understand their customer’s requirements in a much-enhanced way. From providing them with the best offers to being able to make suggestions in real-time, Big Data is certainly a perfect guide for any traveller. Big Data is gradually taking the window seat in the travel industry.
Big data isn’t just extensive, it’s useful. How companies can turn giant amounts of unstructured information into valuable business intelligence. Big data is often defined as large volumes of data in any form (text, video, voice, or other kinds) that are so large they cannot be processed using traditional ways and tools. But big is a relative term – what makes big for one company might not make big for another.
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