What is Big Data?
Big Data is a modern subfield of data science that requires the use of several tools, methodologies and techniques to explore, analyse and process complex data sets in order to be provided insights and information systematically.
Big Data had broken into four dimensions by IBM data scientists. Volume, Velocity, Variety, Veracity and Value are known as the five V’s which can be referred as the characteristics or the key elements that define Big Data. These characteristics are crucial and must be considered by companies that want to run operations successfully. Volume refers to the size of big data while velocity can be defined as the pace in which the data is getting accumulated. Variety stands for the complexity of the data while Veracity can be considered to assure the accuracy of the data. Lastly, the term Value was added, representing the usefulness of accumulated data.
Velocity – Analysis of Streaming Data
The speed at which data from IoT, mobile data and social media is generated, accumulated, distributed and collected can be defined as Velocity. The rate of velocity parallels with the speed in with the data is acquired and processed. Velocity-oriented databases provide users real-time analytics, information and insights which enable companies to make valuable business decisions at the right time. In addition; acquiring, analysing and processing data in real-time allows companies to solve upcoming problems before facing complex issues, making real-time decisions and catching frauds as well. Besides, Processing information quickly into data allows users to have flexibility in their queries and reports.
On the other hand, the systems which analyse the data should be compatible with the task which means high velocity data may require distributed processing techniques due to the speed it is being generated. Some organizations came up with several solutions for streaming data such as; Apache’s Kafka and Spark, Amazon’s Kinesis, Google’s Cloud Functions and other streaming applications that process information in almost real-time to handle the high velocity of data (Reca, 2020).
Every day 2.5 quintillion bytes of data is created to be managed, secured (Marr, 2018). Processing that streaming data instantaneously requires strong data handling processes. High velocity allows users to react high volume of information within a short time. Twitter or Facebook messages, social media posts, Facebook status updates, online transactions, fraud checking, credit card swipes, compliance mechanisms, GPS signals, purchase transaction records and live transportation data can be shown as high velocity data examples. For instance, Facebook needs to ingest, process and file all of the photos uploaded by the users in a short time (Gewirtz, 2018). Also, one TB of trade information can be captured by The New York Stock Exchange during each trading session. In addition, velocity is essential for packet analysis for cybersecurity since the massive flow of data should be analysed and investigated quickly in order to detect anomalies and prevent risks. Thus, data should be gathered, processed and presented near real-time to achieve successful business results (Tudor, 2020).
Buket Bostanci
Keywords: big data, data velocity, velocity, data flow, data volume
References & Sources
Gewirtz, D., 2018. Volume, Velocity, and Variety: Understanding the three V’s of Big Data. [online] ZDNet. Available at: https://www.zdnet.com/article/volume-velocity-and-variety-understanding-the-three-vs-of-big-data/[Accessed 21 February 2021].
Reca, M., 2020. The 5 V’s of Big Data. [online] FlyData. Available at: https://www.flydata.com/blog/5-vs-of-big-data [Accessed 21 February 2021].
Marr, B., 2018. How Much Data do we Create Every Day? The Mind-Blowing Stats Everyone Should Read. [online] Forbes. Available at: https://www.forbes.com/sites/bernardmarr/2018/05/21/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read/?sh=6da11b3560ba [Accessed 21 February 2021].
Tudor, N., 2020. Understanding the 5Vs of Big Data: Volume, Velocity, Variety, Veracity & Value. [online] BornFight. Available at: https://bornfight.com/blog/understanding-the-5-vs-of-big-data-volume-velocity-variety-veracity-value/ [Accessed 21 February 2021].
The article states the concept of “velocity” which considered as the second component of 5Vs of big data, and gives fruitful insights into the analysing process of high volume of streaming data. The high speed of the digitalisation in the marketplace indicates businesses who use big data need to consider velocity as it provides real-time analytics which would be beneficial for an efficient and quick decision-making. Considering the digital payments worldwide where huge number of online transactions have been recorded every second, high velocity would be vital for a business who wants to detect frauds and act in real-time during data collection and processing.
ReplyDeleteIlgin Damla Omay
This blog provided insights regarding that data is not just text, numbers of images which can be called as variety. IBS data scientist have very clearly differentiated the varieties into categories - Volume, Velocity, Variety, Veracity and Value. The velocity of data received is increasing day by day proportional to the number of internet users, the services of large companies must be always prepared for data surge at anytime, and it is also important to remind that the servers should also be capable of leveraging their capacities by providing additional support of extension for space and support of new technologies. High velocities can also lead to data loss which can even put the organization into greater risks of losing the valuable data of their clients.
ReplyDeleteThe knowledge in this article is excellent. Data is the 21st century's oil, and businesses around the board are rapidly recognizing this. The company's overall decision-making will benefit from insights derived from volume, velocity, value, veracity, and validated data obtained from variety of sources. Although the majority of businesses today plan to use data, many are having difficulty capturing, storing, processing, or using it effectively. With its range of Business Intelligence and Analytics services, Accurate assists medium and large companies in efficiently exploiting data. From developing a solid BI plan to establishing a data warehouse, integrating real-time data to leveraging advanced analytics.
ReplyDeleteDamanvir kaushal