Big Data is the new currency of the modern age. As technology continues to massively influence our lives, our reliance on data is also increasing. According to Statista, the global data market size is predicted to rise to 42 billion USD.
Big Data is everywhere. It has already started influencing everything in our lives, right from our music and TV show preferences to smart assistants who can accomplish a host of tasks for us, thereby making our lives much more convenient and comfortable.
Here’s the Big data market size revenue forecast worldwide from 2011 to 2027 (in billion U.S. dollars):
Career opportunities in Big Data are on the rise. As more companies are joining the data bandwagon, higher is the demand for skilled data professionals.
Which means, if you’re thinking of making a career in Big Data Engineering you are most definitely going to be in-demand.
Let’s see how Big Data impacts our daily lives!
1. Online shopping
Ever wondered how those personalized “recommendations” pop up in your notifications every time you browse through an online shopping platform? Well, folks, that’s the magic of Big Data. Online shopping sites like Amazon, Myntra et al dive into the vast pools of consumer data to understand and learn your shopping patterns, tastes and preferences and that’s how they’re able to create customized shopping recommendations for you.
The Importance of Continuous Learning and Upskilling2. Entertainment
Thanks to Big Data technologies, platforms like Netflix and Spotify have taken entertainment to the next level. Data influences the shows you watch and also the music you listen to. Netflix produces and curates highly addictive shows by extracting the consumer behaviour and preference patterns from their database. It leverages consumer data and viewing habits to customize the watchlist according to the hottest genres, actors, and so on. Similarly, music giant Spotify taps into consumer data to specially customize the weekly playlist according to the tastes of individual users.
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3. Healthcare
Big Data is rapidly radicalizing healthcare for the better with data backed by innovative technologies. Gone are the days of loads of paperwork for organizing and maintaining patient health records. EMRs (Electronic Medical Records) which are powered by Big Data, allow health care providers (HCPs) to aggregate patient data within a centrally integrated platform enabling medical professionals to access them anytime, anywhere for more personalized treatment and supervision. Also, fitness sensors and wearables have allowed millions of individuals to take charge of their health. People can now monitor their health without having to rush to the clinic every time. Tracking the health of the elderly has also become easier with remote monitoring technology, another result of Big Data technology. Any fluctuation and anomaly in their health will be conveyed to HCPs in the form of alerts or messages, thus allowing doctors to prescribe treatments in real-time.
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4. Banking
Big Data analytics are now helping banks to prevent financial fraud. Banks can efficiently track and trace any suspicious activity, credit card fraud, and the breach of crucial financial data by leveraging Big Data tools and technologies. This has greatly helped in fortifying the security of banks and protecting valuable customer information.
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5. Crime
Ever heard of ‘predictive policing?’ Thanks to Big Data analytics, the police can now monitor and prevent crimes even before they happen! Using Big Data visualization software, policemen can now predict the probability of where a crime can most likely occur and be there on time to prevent it. Usually, the software database stores the complete history of criminal data according to locations and is integrated with algorithms based on criminal behaviour patterns. This allows police to always stay alert and monitor activities in their respective areas.
These are just some of the examples extracted from real life depicting how Big Data has started impacting our lives even without us realizing it. From enhanced security to healthcare, Big Data is definitely creating a wave of change around us.
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Wrapping up
If you are interested to know more about Big Data, check out our Advanced Certificate Programme in Big Data from IIIT Bangalore.
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How can we implement Big Data in general use?
Data ingestion, or the extraction of data from diverse sources, is the initial stage in implementing a Big Data solution. The data source might be a CRM, ERP system, RDBMS, or any other log files, papers, social media feeds, and so on. Batch tasks or real-time streaming are also options for ingesting data. Following data intake, the extracted data must be stored. HDFS or a NoSQL database will be used to store the data. HDFS is better for sequential access, but HBase is better for random read/write access. Data processing is the final stage in adopting a Big Data solution. A few of the processing frameworks are used to process the data.
How is Big Data used in businesses?
For enterprises, Big Data has become extremely crucial. It aids firms in standing out from the competition and increasing income. Big Data helps organisations with personalised recommendations and ideas using predictive analytics. Big Data analytics also allows companies to offer new goods based on client demands and preferences. As a result of these considerations, organisations are turning to Big Data analytics to increase their income. Implementing such analytics may result in a huge boost in income for businesses. LinkedIn, Facebook, Twitter, Investment banks, and other well-known corporations are adopting it to boost their profitability.
Why can’t all types of businesses make use of Big Data?
Numerous small-scale companies lack the competence needed to develop, implement, manage, and leverage Big Data. Handling a Big Data environment is a challenging and time-consuming operation that necessitates having both equipment and content, as well as ensuring that all of the necessary components are in place. It is challenging to safeguard data and maintain personally identifiable information because of the many types, amounts, and origins of that data. Analysing large amounts of heterogeneous data requires time and money, and the findings are not always what the firm is looking for. Infrastructure, software, and human expenditures may quickly add up, making it difficult to keep track of them.
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