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Companies collect various kinds of data through transaction records or information provided by the customer. Some of that data is useful in the present day, while some of it is not. Even if the data is not as useful today, it doesn’t mean that a user can’t be derived in the future – as any data can lead to unexpected uses. One such example is Kaggle. According to its website, “It is the world’s largest community of data scientists competing with each other to solve complex data science problems.”
 
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Gradually, they started collecting information on the professionals who participated in their contests and built up a database having records of close to 100,000 analytics professionals across the world. Using information regarding what kind of contests that these participants contributed to, Kaggle could also know their strengths and interest areas. They realized that with so much data on analytics professionals, they could indeed match the talent with companies having a need for analytic professionals and provide recruitment assistance to them. Though the data was collected without this specific objective, it proved to be a valuable resource for addressing an unforeseen need.
 
 
 
 
Here are three examples of Big Data being applied in retail, recruitment, and banks.
 

Retail

UK-based retail giant Tesco has been know to be using Big Data when it didn’t even exist. In 1995, it launched ‘Clubcard’ – a customer relationship tool that helped them know who their customers were and how they behaved – so that they could target them in a more personalized way. Today, Tesco uses data not only to understand its customers better and to provide relevant benefits to induce their loyalty but also to optimize their supply chain and costs.
For instance, they use data to predict the effect of weather on sales (and managing the supply thereof), optimizing store operations, and even to cut cooling costs.
 

Recruitment

The open web talent search is an upcoming trend in Human Resources. Companies are using publicly available information about professionals to approach them for open positions, even if they are not looking for a change. For example, a software engineer who’s documenting his projects, interests, and other skills for others while not looking for a job can be a great prospect for companies looking to hire someone having those skills. Companies such as TalentBin are having such a setup at the base of their business strategy. They are positioning themselves as “The talent search engine for the entire web”
 

Banks

Financial institutions have data embedded in their very DNA and consequently, data management becomes a significant concern for their top management. A lot of large US banks are using Big Data to understand how customers use their various channels, such as online, mobile, physical banking, ATMs, call centers, etc. The Banks who were earlier usually doing it the traditional way – using a sample, are now appreciating the benefits that comprehensive data accrues. Bank of America is using propensity models and transaction data to predict which customers are most likely to refinance their loans or credit cards from its competitors, and then makes them an offer when the customer contacts the bank before they defect.
 
 
Have some interesting Big Data uses to share? Do let us know in the comments below.
 
 
 

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