What is Big Data, and why it matters to your business?

As of January 2021, there were 4.32 billion mobile internet users worldwide. With such a high global internet penetration rate, how much data do you think we produce? The answer is A LOT. But how big is BIG data? Every time we wishfully gaze at that new phone online, every song we listen to on Spotify or 'retweet' posts adds up to data for any tech-related companies. By 2025, we are expected to create a volume of 181 zettabytes worth of data. The sheer volume of data available now makes it imperative for businesses to leverage on it, using it to their advantage and better meet customer expectations and preferences. 

So what is Big Data? Simply put, Big Data is data that are large, extensive and much more complicated than its smaller, much more accessible and easier to process small data counterparts. While small data is all about finding needles in haystacks, big data is really about converting hay into needles, or more accurately, turning hay into something that accomplishes what needles can do. Because of its complex and myriad nature, typical data processing technologies cannot handle Big Data. Big Data can then be defined as having one more of the following characteristics:

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• a significant degree of variation (e.g., what type of data – text or photos), 
•  a large volume of data, 
•  high velocity or speed of data generation and processing, and a 
• high degree of veracity in terms of data value and quality.

Big Data can come in the form of viewing history in Netflix, comments on Facebook, transactions from Amazon, medical records, emails, weather, financial markets like the New York Stock Exchange, even that funny cat meme you saw – the list goes on.

"if you can't measure it, you can't improve it”

-Peter Drucker

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Now, if you are someone who wants to jump on the bandwagon of Big Data, you might ask, "what's in it for me?". Peter Drucker, a renowned management consultant, once said that "if you can't measure it, you can't improve it". It is becoming apparent that Big Data is the front runner for all that we do online, rendering Peter Drucker's words even more applicable. In various aspects, the usage of Big Data has revolutionised business operations. 

• Firstly, businesses are now capable of detecting potential fraud and anomalies, allowing them to compile a narrow list of the plausible suspects if need be.  
• Secondly, Big Data allows quick and timely analysation of data which would have otherwise taken a long time if done traditionally.  A good example of how businesses use Big Data to produce well-informed decisions is McDonald's. McDonald's employs Big Data analytics to determine if their chosen location is an ideal and profitable place for a new franchise.  This is accomplished by considering parameters such as demographics, population, and accessibility of the said chosen location.
• Additionally, customer experience is a significant subject that the introduction of Big Data has transformed. As a business, you are presented with an array of data that allows you to make a personalised recommendation to customers. Check out this feature we did for Coffee Bean, which recommends a drink based on the weather (and each customer's most frequently bought beverages).  Netflix also functions in a similar manner whereby it utilises predictive analytics to power their recommendation engine which enables users to have an array of suggested movies or series to watch based on their viewing history.
• Furthermore, businesses who want to incorporate mobile applications in their business are privy to save up production cost as Big Data allows developers to store and extract source codes. This, in turn, reduces the time needed for coding and inevitably drives cost down.

The knowledge of Big Data allows businesses to measure, store and analyse the data they have acquired much efficiently and eventually improve their business.  Data-driven decisions allow businesses to peek at the possible risk and make better decisions. Big Data touches every part of our lives but granted that, it can seem overwhelming at first. After all, BIG – BIG changes in management, a BIG pool of information, BIG risks involved, and even BIG data can seem daunting at first. The good news is, as a company, Think Axis offers solutions that can successfully build analytical capabilities that allow your business to generate a competitive advantage while assuring both you and your client's peace of mind. As a company that goes beyond the conventional approach to using technology, Think Axis will help your company use Big Data to turn seemingly meaningless data and transform it into solutions. 

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Glossary/Keyword

• Recommendation engine - A recommendation engine is a system that suggests products, services, information to users based on analysis of data. Notwithstanding, the recommendation can derive from a variety of factors such as the history of the user and the behaviour of similar users (Chua, 2019). 

Predictive analysis - A set of statistical approaches derived from data mining, predictive modeling, as well as artificial intelligence which evaluate current and historical data in order to forecast future or otherwise unknown events (Nyce, 2007).

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References

Chua, R., 2019. A simple way to explain the Recommendation Engine in AI. [online] Medium. Available at: <https://medium.com/voice-tech-podcast/a-simple-way-to-explain-the-recommendation-engine-in-ai-d1a609f59d97> [Accessed 10 June 2021].

Enterprise Big Data Framework©. 2019. The Four V's of Big Data | Enterprise Big Data Framework©. [online] Available at: <https://www.bigdataframework.org/four-vs-of-big-data/> [Accessed 10 June 2021].

Liu, S., 2020. Topic: Big data. [online] Statista. Available at: <https://www.statista.com/topics/1464/big-data/> [Accessed 13 June 2021].

Nyce, C., 2007. Predictive Analytics White Paper. [online] The-digital-insurer.com. Available at: <https://www.the-digital-insurer.com/wp-content/uploads/2013/12/78-Predictive-Modeling-White-Paper.pdf> [Accessed 10 June 2021].

Pence, H., 2014. What is Big Data and Why is it Important?. Journal of Educational Technology Systems, 43(2), pp.159-171.

Statista. 2021. Topic: Mobile internet usage worldwide. [online] Available at: <https://www.statista.com/topics/779/mobile-internet/> [Accessed 13 June 2021].