End of the Big Data Era

Cybercrimes can never become obsolete. The need for cyber analysts will always remain a requirement of current technologies. Thus, it is safe to say that over time data will only increase, people will always be demanded to handle the large amount of data that has been formulated and encapsulated over a long period of time.  But, is there a chance for this to change, will big data come to an end?

End of the Big Data Era
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Big data thus, is a term used for the presence of an abundance of data to analyze and capture the visions and intuitions to further draw deductions and make fitting decisions.

What and Whys of Big Data

Big data came into existence. It has kept itself strong. Therefore, in buzz ever since. Big data has 5 Vs at the core namely:

  1. Volume: Understanding the depth, industrial development, and storage platforms of and for the data.
  2. Velocity: Speed with which the data comes in.
  3. Variety: The structure and format of the data.
  4. Veracity: Quality and characteristic of data.
  5. Value: The ability to transform the data into something worthwhile.

For instance, to visualize and embed the concept of big data, think of a sky full of stars. Comprehend that the process of recognizing patterns to bring out the constellations that are hiding in that gathering is governed by you.

End of the Big Data Era
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Below are a few real time approaches which explain what big data and big data analytics is.

  • Campaigning and Marketing Techniques: Identifying the indulgent set of customers that suit the product/ business is a crucial bit of information. This has a direct impact on setting the right campaign and marketing techniques.
  • Machine learning models: Input and algorithm driven models need a way to treat the uniqueness of structured and unstructured datasets.
  • Predictive, Descriptive, Diagnostic and Prescriptive Analytics: Different sizes and formats of data contribute to the volume of the data supplementing to the outlook of developments of advanced tools to draw insights.
  • Customer Services: Analyzing and understanding customer data gives a clearer picture of what the customer needs and wants. Moreover, through custumers/consumers unstructured and structured data is collected. Consequently, outlining relevant information from the same is a huge game changer.
  • Combining health records: Identification of mass records and reports of numerous patients and keeping them proper to deduce and extract valid information is a need that will always pertain to the health and medical care industry.
  • Combining health records: Identification of mass records and reports of numerous patients and keeping them in a proper format, for instance, will help in deducing and extracting valid information is a need that will always pertain to the health and medical care industry.

Big Data and Privacy

As the number of companies and organizations trying to use and imbibe the insights given by big data analytical models, the capacity of data has started to take a toll on various aspects of security with respect to confidentiality and breaches. Undermentioned are some thin on the ground cases.

Barricade to Privacy: There is a constant unprecedented fear among consumers and customers. Privacy laying on and between social media platforms is one such fear. Privacy breaches are supposedly more accounting and possible when it comes to big data analytics’ understandings.

Unmanageable Anonymity: Hiding the identification of certain features which belong to consumers/customers becomes almost impossible. To clarify the reason why this happens is that data in most instances is available raw. Such type of data is available everywhere on the internet very easily.

The Analysis might not be always accurate: The chance of acquiring wrong insights increases with improper data pre-processing and application of algorithms in an ill manner.

Breaches: Data can be accessed in an unauthorized fashion which can be anything from outdated software models to malware attacks.

Discrimination: Discrimination among people happens on the basis of race, sex, religion, etc. As a result, retrieval of such data in an unauthorized manner might just boost the cause.

What is likely to replace Big Data?

An unintended gamble that will grow over time is static data. Manually jotting down data, importing, and generating is what adds to its increase. In other words, the likelihood of the graph of the data vs time to have a negative slope is quite questionable. Increased use of social media, online business communications, shopping, etc. very well complements the same.

To handle such an amount of data in the near future, manually, is very honestly donkey’s work. Privacy breaches, modeling errors, prediction inaccuracies, detailed monitoring of such amount of surplus data will eventually lead to the conception of more labor. With this, one can come to a conclusion that the big data era has come to end

Here is where the cloud comes in. All this data subsequently is more probable to migrate to the cloud.

End of the Big Data Era
Source: Pexels

To illustrate, imagine a clouded sky, these clouds hide the stars that are visible to the eyesight. Thus, each individual cloud has its own set of stars to hide. Similarly, each cloud has data saved according to the customers, divided, and organized. Furthermore, this data is accessible only to particular or respective users.

Why Cloud ?

  • Power and performance: Data and infrastructure of the model used plays a major role in centralization and analytics.
  • Exponential graph of data volume: Increase in diversity and data used by companies/organizations makes it grim to deal with, storing and organizing such data. This leads to much more reliability, security and flexibility making the job furthermore laid back.
  • Everlasting Advantages of Cloud: Cloud is cost-effective and self sufficient. Further, it is scalable, easier to implement, adaptable, and has the same amount of tools required for analyzing big data

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To sum up, over the next ten years, the accumulation and abundance of data will complicate situations and validation will spontaneously become the need of the hour. For the data to be more organized, secure, and relevant, this technology: Cloud. Thus, it can very well take over the advancements with respect to skill and performance.

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