What is Big data? Where does it come from? and Who uses Big Data?
What is Big Data?

Over the several years, there has been a grown understanding of the role that big data can perform in delivering valuable insights to an organization. Nevertheless, in term of definition, there are many different concepts and meanings of Big data that was interpreted and announced by data specialists and experts.

Although the big data definition is still various in general, I would like to suggest the most reasonable meaning in my opinion. It is the 5V’s of Big data which was state by Keith Gordon MBCS CITP, former Secretary of the BCS Data Management Specialist Group. The 5V’s of Big data is the combination of the following five characteristics:

Volume: where the amount of data to be analyzed and collected is sufficiently massive to require complex and special analytics.

where the amount of data to be analyzed and collected is sufficiently massive to require complex and special analytics. Velocity: where the data is built at high rates or created nearly in real-time.

where the data is built at high rates or created nearly in real-time. Variety: where the data have the various types of data from different sources. For example, structured data is any data that locate in a fixed field within a record or file, and unstructured data which is the form of binary data such as video, picture and audio.

where the data have the various types of data from different sources. For example, structured data is any data that locate in a fixed field within a record or file, and unstructured data which is the form of binary data such as video, picture and audio. Value: where the data has perceived or quantifiable benefit to

the enterprise or organization using it. (ex. customer insights, the trend of time series)

where the data has perceived or quantifiable benefit to the enterprise or organization using it. (ex. customer insights, the trend of time series) Veracity: where the correctness of the data can be investigated and assessed.

Although the 5V would be the main nature of Big data, it can be altered and changed by innovation and the capability of data adoption. In other words, the characteristics of big data can be more advanced in the future.

Where does it come from?

After we understand what is exactly call big data. Now, the question is where does it come from? How can it be generated? The answer is so simple, big data was from us by consuming and spending time on social media platforms. For example, commenting on a Facebook post, uploading pictures on your Instagram and watching videos on Youtube, all these activities were recorded immediately once you give any actions by such platform owners. However, social media is not only a source of Big data. I would like to share the 3 primary sources of Big data that I have found from cloundmoyo website which are:

Social media data: as I mentioned, it comes from the Likes, Tweets & Retweets, Comments, etc. via your preferred social media platforms. Transactional data: the data which is generated from all the daily transactions that take place both online and offline. Invoices, payment orders, storage records, delivery receipts. Machine data: the data which is defined as information which is generated by industrial equipment, sensors that are installed in machinery and even weblogs which track user behavior.

Who uses big data?

So now it seems like Big data has become a part of our life, and it is so valuable. Why? Because many companies can use big data to their advantage such as automating processes, gaining insight into their target market and improving overall performance using the feedback readily available. Let look at the examples of some of the industries that boosting their business by using big data.

Financial services: transactional data rapidly grows due to the spending ability of users that faster and more comfortable via E-banking or Online banking. The bank is able to use client data to guide decisions for credit card offerings for individuals, the credit limit and benefit, and reward offerings.

Transportation services: currently, using ride-hailing service is widespread intensively in most big cities. More interestingly, ride-hailing service firms allow to collect a vast amount of data in both rider and client-side. Although utilizing these data on individual user is challenged, but it can increase the long-term profit and the service personalization. For example, in case that rejects a ride after request, due to the unsatisfied price, the Uber application can respond back to the user in a few minutes later that the price is now lower (while knowing the precise location of the rider). This function can be done by analyzing geo-localization in real-time. Certainly, such a large size of client data can lead firms to offer the targeted promotion to users.

Hospitality service: Hotel records and stores their customer information in order to exploit the data. After the client checks out, hotels are able to collect the guest detail and preference, for example, the special requests, vegetarian, room dining service, etc. Thus, before the next accommodate, the hotel can facilitate the customer’s requirements in a more personalized way. Alternatively, hotels analyzed historical data to create and deliver targeted promotional offers. Another interesting platform in hospitality service is online platforms such as Agoda, Airbnb, VRBO and Homestay, to name a few. The platform allows guests to rent accommodation (not only hotel but also apartment) via application or website. Normally, these service providers usually are not own any accommodation but earn a commission fee (percentage service fee) from every single booking and host. The price is generally set by the host, it can be affected by the period of the year, the weekday, the number of stays, etc. Accordingly, the amount of data compiled by the platform is valuable due to both the property and the user data were collected. Consequently, analyzing the data allow companies to enhance service by recommending a reasonable price to host and developing the ranking of the offering options for each browsing user, based on previous preferences.

To sum up, it can be seen that the great of big data depends on technology development. The key to the information explosion is online platforms such as websites, mobile applications and social networks. Consequently, the more people connect to the platform the more data are generated. Correspondingly, the discussion of utilizing big data evolve service operation is identified by the sample of improved services in the financial, transportation and hospitality industry. In fact, not only the provided example but there also the big data used cases across different industries occur in the world. Ultimately, the technologies are continuously developed and change over time, the presence of big data is one of the phenomenons that everyone should aware of.
['Prin Iamchula']
['Big Data Analytics', 'Information Technology', 'Contextual Marketing', 'Big Data', 'Data Science']