Due to an exponential increase in data in the 21st century, a new term "Big Data" was coined few years back.
Investopedia defines big data as “the growth in the volume of structured and unstructured data, the speed at which it is created and collected, and the scope of how many data points are covered.”
Big Data continued to experience rising adoption throughout 2016, and we’ve observed an increasing number of organizations transitioning from experimental projects to large-scale deployments in production.
This increase in data has given organizations the opportunity to to analyze their data to get more and more insights. Most organizations now use multiple tools and frameworks to store and process this enormous amount of data. More than 70% of organizations, whether they are start-ups, mid-sized companies or bigger corporations, are leveraging big data analytics today.
It has been predicted that by 2020, 40 zettabytes of data will get generated - an increase of 300 times from 2005!
It’s not a big data wave anymore as much as a roaring tsunami.
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Big Data Technologies and Applications
Different domains are leveraging Big Data technologies in various ways – some to solve a problem, some to identify patterns or most to increase their revenue.
Behold a brief list of examples.
- Retail: Being one of the biggest beneficiaries of big data, retail giants generate a huge amount of data every single day. Organizations like Amazon perform extensive customer purchase behavior analysis for product recommendations and re-marketing.
- Manufacturing: In this domain, analyzing big data helps in increasing efficiency, improving product quality, reducing component defects and thus saving lot of time and money.
- Smarter Healthcare: Hospitals generate a huge amount of patient information each day. Today, there are big data applications which can analyze patient data and prevent many illnesses and complications from occurring by preemptively alerting doctors.
- Telecom: Organizations like Vodafone, AT&T and Airtel are leveraging big data applications to significantly reduce the data packet loss that occurs when networks are overloaded, thus providing a seamless connection to their customers.
- Search Quality: As you would expect, Google is one of the major user of big data applications. It stores huge amount of data and uses big data applications to provide faster search results.
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The Future of Big Data and What it Means for You
As the market matures, we will start to see businesses riding from one wave to the next: that’s when things will really start to get exciting. Arguably, the next wave will be when we start to see more machine-driven control loops and predictive analytics, pushing us closer to a data-driven, value-centric future.
From the career perspective, there are multiple openings for professionals with knowledge on big data technologies like Hadoop, Spark, Kafka, Cassandra etc.
Datajobs.com quotes a McKinsey Global Institute study that states: "By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of Big Data to make effective decisions".
It’s simple really – to ride this tsunami, you need to build expertise in multiple data technologies which are used to store and process Big Data. Technologies like Hadoop, Spark, Kafka, Machine Learning etc. CIO.com’s list of the 10 hottest skills shows that the demand for Big Data skills has moved up from No. 10 in 2015 to No. 4 in 2017.
The demand for Big Data professionals is only going to rocket in the near future and up-skilling now will prepare you for a future-proofed career.
