Data
velocity refers to the agility in which data is generated, distributed and
collected. High data velocity is generated at such pace, that it needs specific
processing techniques. The higher the velocity rate, the sooner the data can be
obtained and processed. Such high velocity data when processed through advanced
tools such as analytics and algorithms can reveal great information appropriate
for decision-making in business
Traditional versus Fast paced decision-making
Traditional business decision-making was accustomed to waiting for a day, weeks and months to have a certain amount of relevant information before the high quality and safeguarded decision was made based on the previous business performance. But with time changing organization, companies and even new business try to take up a fast-paced approach. One such example is organization Amazon who thinks “the traditional approach to decision-making is far too slow”.
Defining Traditional Data Processing Techniques
· Balancing – Data Balancing the compiled survey, in a manner where the ratio of gathering information is equal between the subjects. Example - Ratio on preference of buying Android phone versus IOS, if the survey suggest that Android buying is excelling IOS, then the study needs to be conducted between hand-picking the Android users and IOS users in ratio of 50:50
· Shuffling – Data Shuffling inculcates the initial data will have similar processing results, but if the data shuffling is done then the actual sense of survey is clear, the random results can help in predictive performance and can avoid misleading results.
Defining Big Data (Velocity) Processing Techniques
· Text Data Mining – Ability to extract sufficient information from various source of volume data stored in database. This process is helpful for companies who need research from the gathered volume data to conclude on decision-making
· Data Masking – In other words pseudonymitication of data, for privacy and data security is what the developed system offer in order to be able to access without fearing for data breach. This helps in confidentiality of individual and data to some extent.
Example of Fast paced Decision Making – Amazon’s Ideology
Amazon’s CEO Jeff Bezos in his letter to Amazon shareholders (2017) emphasized on how “speed matters in business” and focused on the importance of “high-velocity decision-making.” He suggested that “Most decisions should probably be made with somewhere around 70% of the information you wished for. Waiting for 90%, in most cases, will probably get slow.” Nobody ever wants to make bad decisions for their business or organizations however, constantly waiting for almost perfect information can lead to withered and missed opportunities. Processing the data or information is critical for companies, the business that are good at course correcting are far better than the business that are slow in decision-making.
Velocity data processing and analytics helps the businesses to quickly turn raw data into actionable insights by
· Tracking transactions,
· Identifying issues with hardware and software,
· Reducing customer complaints.
By identifying and resolving these issues faster, the businesses and organizations can significantly improve customer experience.
Constant and regular data processing with analytics can help to be compliant with government and/or industry regulations, avoid preventable losses and improving business efficiency by pre-empting errors and problems
Share your comments on what do you think of Data processing with Data privacy?
Written By: Prajakta Jadhav
Keyword – Velocity, Data Protection, Business, Decision making, Techniques
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Referencing
Loon, A. R. van (2016) ‘How you can improve customer experience with fast data analytics’, Big Data Made Simple, 4 July. Available at: https://bigdata-madesimple.com/how-you-can-improve-customer-experience-with-fast-data-analytics/ (Accessed: 26 February 2021).
Balakrishnan, A. (2017) Bezos shareholder letter: Don’t let the world push you into becoming a ‘Day 2’ company, CNBC. Available at: https://www.cnbc.com/2017/04/12/amazon-jeff-bezos-2017-shareholder-letter.html (Accessed: 26 February 2021).
What Is Data Velocity? Data Defined (2020) Indicative. Available at: https://www.indicative.com/data-defined/data-velocity/ (Accessed: 25 February 2021).
Dykes, B. (no date) Big Data: Forget Volume and Variety, Focus On Velocity, Forbes. Available at: https://www.forbes.com/sites/brentdykes/2017/06/28/big-data-forget-volume-and-variety-focus-on-velocity/ (Accessed: 26 February 2021).
Traditional and Big Data Processing Techniques | 365 DataScience (2018) 365 Data Science. Available at: https://365datascience.com/trending/techniques-for-processing-traditional-and-big-data/ (Accessed: 26 February 2021).
The speed of access and the flow of data is the great challenge that Big Data poses today and - and above all - for the future. Its three "Vs. determine the undoubted value it brings to Business Intelligence projects.", the handling of which raises questions of such importance as, for example, whether traditional storage tools should be left aside to give way to management systems that do not intend to capture data for subsequent processing and to structure indiscriminately, but rather carry out this task in real-time, capturing only those data that add value to BI systems.
ReplyDeleteThe adaptability to the new contexts that increase with the evolution of these three magnitudes will be the key to the success of the BI systems of a tomorrow just around the corner. How these adaptations will materialize and what novelties they will bring with them are questions that we will soon answer.
Thanks for your insights Prajakta :)
While market size, timing, and good old-fashioned luck all play a role in some businesses growing much faster than their competitors, it all boils down to how you approach growth internally. In the end, the firms that move the fastest usually win.
ReplyDeleteSpeed is said to be the secret weapon of many entrepreneurs. I've worked with dozens of fast-growing businesses and met some of the world's most inspiring leaders over the last decade. I've seen time and time again how great ventures' rapid growth is based on one thing: execution.
Founders can supercharge development by focusing on quality and speed of execution. To put it another way, your growth rate is determined by the number of decisions you make multiplied by the speed at which you make them.
Good Content Prajakta !
Really helpful content and very well explained concept of velocity of big data. Keep it up.
ReplyDeleteVery well explained in detail and with example...
ReplyDeleteGood and informative blog I personally feel companies should be more transparent as showing their image to the people and data privacy is must as people can misuse sensitive information regarding a company and also a personal individual well I found it informative and more interest thanks @prajataka
ReplyDeleteCustomer Satisfaction is of utmost importance if an organization has to sustain and grow. In today's competitive business world an organization needs to have velocity in data processing to achieve customer satisfaction. Use of advanced tools/techniques such as analytics and algorithms helps in getting the appropriate information for quick and correct decision-making in business.
ReplyDeleteAt the same time, Data Privacy is also important to retain the trust of the customers in the organization. A breach in Data Privacy can amount to losing customers and can have negative impact on business.
Your blog rightly assesses the need of the businesses to keep up the pace while achieving their target with perfection.
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