Big Data is one of the most futuristic technologies of our times and is enabling the collection, storage, and utilization of user data to understand their behavior and develop predictive models that will effectively take autonomous decisions as per their outcomes. We are not talking about a gigabyte or two of data; big data analytics targets data that is accumulated at the rate of 1.2 megabytes per second from every online subscriber (data that cannot be contained with traditional means of data storage).
Defining Big Data and its Usage
As the term ‘Big Data’ itself implies, it relates to eons of data that might be structured or unstructured and that can be used by businesses by varied means to understand their customers, their expectations and requirements, as well as the developing market trends. This data is also being utilized to develop predictive modeling strategies to help smart devices become smarter and customized as per user patterns.
In simple terms, under the purview of AI, Big data is utilized to develop the ‘intelligence’ of these smart gadgets.
Big Data now forms the centerpiece of various business strategies to compete, innovate, and capture value as well as to tackle industry-wide competition. The most important aspect of these functionalities is the fact how businesses manage their required Velocity (the speed with which this data is collected through billions of connected devices worldover), Volume (the way this enormous amount of data gets stored including solutions like clouds and Hadoop), and Variety (as the data might be unstructured or unstructured and collected in various formats like audio, images, videos, etc.)
However, the technology, as well as the scope it entails, can help businesses mitigate their work risks and help in enhancing their overall customer relationship management, overall work efficiency, and evolve into a better customer-centric brand altogether.
Trends that are set to be the norm of Big Data Analytics Developments in the coming times
Let us now try and analyze how big data will be transforming its ways and structures to be more viable and effective for businesses globally:
1. Inclusion of all aspects of Artificial Intelligence
As stated earlier, Big Data is a concept that comes under the purview of the much broader AI spectrum. But, they actually work simultaneously to grow smart systems. Data herein, makes the concept of Big data more effective with better predictions, enhancing AI and AI in return helps data to transform into ways that it can be more effective (actionable data). They together form a vicious circle of interdependence. Since, Smarter machines are the need of the hour for all businesses, we ought to see a lot of work and applicability of both these technologies in the coming times.
2. More utilization of Data as a Service
Have you witnessed the embedded data of covid-19 death and patient count in the post-pandemic era on the various websites?
This is an example wherein, businesses tend to develop and offer data as a service to other businesses to embed and utilize within their work fabric. Though some users may term it as being detrimental to user privacy and security concerns; the technology development has been helping businesses to move data easily from one platform to the other in a no-nuisance kind of presentation, without any vendor lock-ins or data accessibility, administration, and collaboration issues. DaaS is thus touted to see its own share of glory in the times to come.
3. Things tend to get faster with Quantum Computing
Technologies are evolving by the day and most of them require data as food. But, it is mainly the speed at which they can ingest and digest this ‘food’ that separates them in functionalities and efficiencies.
Do you know that Google has already developed a Quantum computing (wherein, decisions of yes or no are not taken by binary digits 1 and 0, rather with much faster qubits or quantum bits) based processor named Sycamore, that claims to have solved a problem in 200 seconds, that another state-of-the-art supercomputer would take more than 10,000 years to resolve. Machine Learning algorithms as of now, have been limited by the slow computational speeds and the prowess of classical computers. Quantum computing is a novice development trend that herein tends to administer large data sets at much faster speeds to analyze data at a faster and efficient pace to identify patterns and anomalies in real-time, making it much more effective for businesses worldwide. Quantum computing can easily integrate data by running comparisons to quickly analyze and understand the relationship between two or more predictive models or the effectiveness of algorithms.
4. Edge Computing for better problem solving
There are more than 30 billion connected devices out there with the numbers soon rallying to touch the 50 billion mark. These IoT devices are the new normal of the world, and businesses are thus, on the lookout for ways to better utilize the enormous data that they tend to generate all the time. Edge Computing is a new development framework in this regard, wherein processors are located closer to the source or destination for data, rather than directly going to the clouds. As businesses become more possessive of the data they generate and the value it holds, the trend is sure to see much wider use and scope in the future.
5. Hybrid Clouds in Big Data Analytics
With the rise of cyber-attacks and privacy and security issues of data within clouds, businesses are opting for the usage of hybrid clouds. This one-infrastructure cloud model enables the utilization of one or more public clouds to work in synchronization with one or more private clouds, leading to a more comprehensive environment with mobile app security a major concern. For this cloud topology development, an organization must have a private cloud to gain adaptability with the aspired public cloud.
Things in the pipeline for Big Data Analytics
Big Data Analytics is still evolving. Though the year 2020 has been witness to its widespread use, its applicability and scope are further set to improve with the passage of time and more technological developments. All above stated Big Data trends are sure to be an important part of them.
