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Big Data


In this article, we will be acquiring an understanding of data. How the data is classified as Big Data. How the big data has evolved. The aspects and importance of Big Data. Applications to be used to process Big Data. The career aspects of Big Data. In the end, a conclusion that will summarise the whole article.

What is Big Data?

The data that is the coagulation of tremendously large data sets of different data types clubbed together can be classified as Big Data. It is called big data because no one in the history of computing had anticipated the possibility of the growth of data at this pace. The data is bits and pieces of information that can be stored virtually in the form of binary format. Some terminologies explain the storage of data starting from bits to zettabytes. There are mainly two reasons for the fast-paced growth of data-

  • the prime is acceptance
  • another is dependence

Acceptance is the ability of people to understand the value of Data and its possible outcomes. An example would be Digital Marketing and Advertisements.

The dependence deals with the inability to perform the routine task in the absence of certain data. An example would be Google Search Engine.

History and evolution of Big Data

Traditionally data was stored in the form of writing. These writings from the beginning of the human race till 2004, post-conversion of them in digital data accounts for 40 petabytes of data. Now from 2004 to 2006, we had generated 140 petabytes of data, and by 2020 we had generated 44 zettabytes of data (i.e. 44 trillion gigabytes). The real question would be how this enormous data has been generated. This can be explained by understanding the chronology of data evolution.

The IT industry from the beginning of the 20th century remained extremely robust but with limited application for acceptance in the business. Hence it first conquered the repetitive yet laborious tasks. The primary clients of IT were Banks, Air ticket systems, High-level communication with Morse code, etc. This is an era where this industry has collected data just for keeping the records, however the value of this data and its utilization remained very limited.

Then we entered the 21st century, where the IT industry witnessed advancements and it became the ultimate necessity. This had made possible with the help of high-speed internet facilities offered at low tariffs. World has witnessed the launch of Social Media services and platforms, which enabled every individual to have an online presence. A shift has been witnessed from the traditional telephone to the smartphone, the manual electrical appliances to IoT smart devices and from the traditional cars to Self-Driving Cars. All these advancements work on millions of small sensors which communicate and produce data.

To make sense of this humongous data, the overhead costs of database servers increased tremendously. Since the data is important for keeping records so the earlier servers are now being replaced by cloud-based servers. As the overhead running cost increased, the pressure on the engineers to make use of this data had also begun to rise. Therefore a bunch of engineers, scientists, mathematicians, and statisticians worked together and turned this potential liability into an asset. It is discussed in great detail in the "Application of Big Data"

Application of Big Data

With data comes knowledge and with knowledge comes "intelligence". The new term called "Data Insight" began featuring in the 21st century. Now, what is Data Insight? Data Insight is the calculated possibility of an outcome to happen based on previous usage patterns. These insights can be obtained by quantifying and modeling the data obtained by series of algorithms. It can be summarised with 4D's Data-Driven Decision Making. To get a better idea we have to go through the case studies of companies who had encashed fascinating possibilities of Big Data.

Walmart

When hurricane Sandy hit the east coast of America, the Walmart store had predicted in advance the change in the buying pattern of consumers. They had filled their stores in advance with the supplies of essential items and strawberry candies. These strawberry candies are predicted by the usage pattern with the help of modelling of Big Data. At the time of the hurricane, the Walmart stores were well prepared with essential supplies, which helped them in gaining a huge profit margin.

IBM Smart Meters

IBM developed a smart meter that records and sends the usage patterns of electricity consumed every 5 minutes. With every passed 5 minutes, the usage pattern has been acknowledged by the system, and simultaneously the results are delivered to the Grid. The IBM after successful simulation did a partnership with Oncor, a power distribution company of East Texas. Upon application of these smart meters, the grids were bombarded with usage patterns of consumers. This helped Oncor to identify the peak usage timing and pattern of electricity. This helped in Load Distribution and Dynamic Pricing. Therefore they also intimated the industries to operate heavy types of machinery at set timings to save money on the electricity bills. These partnership has helped ONCOR with efficient distribution and Management of Power along with benefits for the consumer with dynamic pricing.

FAANG

Facebook, Apple, Amazon, Netflix, and Google use Big Data with the decision-making process and capitalize over the same. Facebook's Ad knows more about the likes and dislikes of an individual than anyone else. Apple's smartphone user experience is completely based on data gathered by the user by observing the Usage Patterns. Amazon started its journey from an Online Book shop that currently sells 600 products/seconds. Netflix by analyzing the viewer pattern recommends movies based on likes and dislikes which enhances reach and user retention. Google has been a dominant player in the search engine market, based on user search it had accumulated data that suggests relevant URLs. All these techniques are a complement to the application of Big Data.

The above mentioned real-world examples are of Big Data, however it haven't yet scratched the surface of possibilities engraved with it. This Big Data helps with building and developing machine intelligence so that the machines will soon become capable of performing difficult tasks such as surgeries, driving, hospitality, etc.

Conclusion

Big data is the next big thing befalling within the IT industry and the scale of growth is enormous. The world is shifting towards a more robust, connected, and safe place. Big Data is playing a crucial role in shaping the present world. Now is the time to make a career in Big Data and Intelligence.

At EdifyPath we have a full-fledged course based on Big Data that discusses the in-depth practical application of Big Data which are further applied in the real-time job environment. As we speak, Data Scientists are only able to process 30% of data produced with the help of all advanced technologies combined. The data will continue to grow and this gap of 70% untouched data will also increase. This untouched data comes with an enormous possibility of business growth and decision-making that needs to be taken care of. There is also a necessary requirement for robust software as well as advanced hardware to process such gigantic data. The scope of innovation is also huge, therefore now is the time to invest in ourselves and get some practical insights into this technology.