Introduction to Big Data

What is Big Data?

Big Data is a term for massive data collection having large, more varied and complex structure. An example of big data might be petabytes or exabytes of data consisting of billions to trillions of records of millions of people from different sources like social data, machine data and transactional data including online transactions, texts, images, emails, videos, audios, click streams, posts search queries, sensors and so on. Data lakes are a central storage repository that stores these structured, semi-structured and unstructured data in a raw format for future use. (Rouse, 2019)

The 3V’S of big data (Volume, variety and velocity) are the key to understanding how big data can be measured. (Botelho, 2018)

How it works?

Using traditional data management it is difficult to store, analyse and visualize the data. Big Data Analytics is the process of examining massive measures of data to discover patterns, unknown correlations, market trends, customer preferences, and new business insights that provides nano-level valuable insights which is an advantage for better decisions and strategic business moves over the competitors. This can be done by using frameworks like Hadoop, MapReduce and Spark from Apache. (Monnappa, 2020)

Source: Hitec Dubai

Why Big Data is important?

In the explosion of cloud and AI technologies, the transactions, inventory and IT infrastructure can exist in an absolute virtual state, a good big data approach helps companies make sense out of random information to create an overview by accessing data from many sources or for designing digital architecture which is critical for business success. According to Grand View Research, the big data market will flaunt a size of $123.2 billion by 2025 and by the PwC report, the growth of technology by 2030 will contribute over $15.7 trillion to the global economy. In 2020, there will be a huge demand for big data processing frameworks and data scientist and also the business worldwide will invest on big data technologies to increase profitability through advanced analytics. (Shacklett, 2019)

References 

Available at: https://www.techrepublic.com/article/big-data-predictions-8-analytics-trends-in-2020/

Botelho, B., 2018. Bigdataldn. [Online]
Available at: https://bigdataldn.com/intelligence/big-data-the-3-vs-explained/
[Accessed 25 Jan 2020].

Monnappa, A., 2020. Simplilearn. Data Science vs. Big Data vs. Data Analytics, 22 Jan.

Rouse, M., 2019. TechTarget. [Online]
Available at: https://searchdatamanagement.techtarget.com/definition/big-data
[Accessed 25 Jan 2020].

Shacklett, M., 2019. TechRepublic. [Online]
Available at: https://www.techrepublic.com/article/big-data-predictions-8-analytics-trends-in-2020/
[Accessed 25 Jan 2020].