Blog

7 Key Big Data Trends to Watch in 2021


The time for Big Data is here and how. With an average individual generating about 1.7 megabytes of data through their online activities every second; its usage to track user habits, requirements, expectations as well as in market research and evolution and growth strategies for businesses is seeing new light of the day.

Up until now,’Big data’ was mostly a concept to assimilate and utilize data through powerful computations, to give out the requisite results. The year 2020 has been witness to its maturity and development of applications for its common use for businesses. Its application developments are further set to evolve in 2021.

What exactly is ‘Big Data’?
When you open a website or a mobile app or for that matter access any form of ‘smart devices’, you generate data; when you browse through them you generate lots of data (your browsing history, your clicks, your locations, etc.) and when you close them, you again generate data. In fact, when you are not even accessing these devices directly, but are connected with them with certain autonomous service permission (as in a smartwatch tracking your heartbeat constantly!), you again generate data. Big data is the term given to this collection of ‘scores of data’ and the computations over and above it.

There is no particular minimum size assigned to big data, but the term is generally referred for the data that is voluminous and complex enough to not suffice within the storage capacities of traditional data management tools. Think about the data generated by the various stock exchanges, social media platforms, global navigation apps, etc. in one day.

Technology trends that shall further help ‘Big Data’ to evolve in 2021
As per an IDC report, the global data volume was predicted to grow exponentially from 4.4 zettabytes to 44 zettabytes between 2013 and 2020. With the advent of newer technologies and more connected devices per individual, this number is touted to reach 163 zettabytes by 2025. We definitely need sound technology developments to store and sort through this enormous amount of data. Latest trends in them include:

1. Actionable Data for smarter decision making
Actionable data is basically the data outcomes, derived from scores of data records that can enable a machine to take a particular decision, thus making it ‘smarter’. As businesses realise that collecting more and more data through varied sources, won’t be of any much significance, until and unless it can be well-utilized to transform into actionable data (usable form of data); the true value of big data developments would not be harnessed. For instance: Businesses will have to sieve through investor data for different days and market cues, to analyse their responses for actionable decision making within a stock exchange.

2. Tools to develop data as a product (DaaP)
The collected data from websites, acquired users, mobile apps, page traffic, etc. cannot be used in its raw form. It would require sieving, analysis and hence, development of outcome data as a final product that can directly be used to make decisions by businesses. This final development of usable data products is what exactly ‘DaaP’ stands for and the trend is further touted to witness great development scope in 2021. For instance: A chocolate selling brand would require its data engineers to analyze user data to find which flavors their clients and page visitors have been looking for, in order to evolve newer chocolate products and flavors for the coming season.

3. Cloud Computing is further touted to evolve with hybrid clouds
When you have an enormous amount of data, you would also require enormous space to store it and ‘clouds’ are that space. But, owing to the security issues of private models, wherein the data may be jeopardized; utilization of hybrid clouds is gonna be a trend for businesses in 2021. Hybrid clouds use one or more private clouds in conjunction with one or more public clouds within one cloud infrastructure helping to improve infrastructure efficiency as well as making it more secure. With businesses now understanding their importance and opting for their services; sooner than later, utilization of these technology developments will form an intrinsic part of mobile developer skills the world over.

4. Development of Data as a Service (DaaS)
Data as a Service (DaaS) is mostly a cloud-based system, wherein information is gathered (from the data) and distributed amongst the customers in the form of data files (including text, images, sounds, and videos) as per their requirements and used functionalities. Delivering data as a service increases the flexibility of data with better data maintenance at an affordable price and minimum time period. For instance: Urban Mapping is a geography data service that provides data (DaaS) to its customers to embed into their own websites and applications and Xignite is another company that specializes in providing financial data only.

5. Usage of ‘Augmented Analytics Engine’
System tools can process structured data, but what about the eons of unstructured data being constantly generated. Augmented analytics Engine is Machine Learning and Artificial Intelligence based technology development that processes this unstructured data and its outcomes to transform them into the usable actionable data forms. It automatically sieves through a company’s data, and simultaneously cleans it for further analysis. Augmented Engine then effectively converts the collected data insights into action steps that can be directly utilized by business executives or marketers, making analytics accessible to even small and mid-sized business owners.

6. Quantum Computing is the future of Big Data
What is the point of collecting scores and scores of data by organizations within clouds and other storage devices, if they cannot use it well. The sad part about the collected data is that small and mid-sized businesses still do not have the computational prowess or acumen to sort through the amount of data they generate. Quantum Computing could be their rescue as it can easily process large data sets at much faster speeds and can simultaneously provide it to AI- based algorithms to analyze data at a more granular level to identify patterns and anomalies. Quantum Computing shall soon become the technology of choice for most application developers and businesses the world over.

7. Data Professionals shall be in demand
Since the requirements and importance of data is increasing, so is the need of professionals who can handle and help businesses to utilize this data well. Remember, we are talking about several gigabytes of data on a single day and processing through them is no simple task. With a plethora of specialization and work options opening up in this field; data scientists, chief data officers and chief data analysts are some of the work positions to be in great demand in 2021.

Conclusion
Data is one of the biggest assets for businesses today and companies worldover are awakening to this reality. In fact, the innovations and developments in the field of ‘big data’ will have the prowess to transform the global business scenario in the coming times. The above stated market trends will give you a sneak preview of the same. You could try using them for your business as well.

Fuente: Veronica Hanks

Volver

7 lessons to ensure successful machine learning projects


When Michelle K. Lee, ’88, SM ’89, was sworn in as the director of the U.S. Patent and Trademark Agency in 2015, she saw an opportuni

Ampliar

CDO’s Next Major Task: Enabling Data Access for Non-Analysts


The chief data officer (CDO) has taken on far greater digital responsibility than her predecessor has. She spearheaded the digital transf

Ampliar

9 Distance Measures in Data Science


1. Euclidean Distance

We start with the most common distance measure, namely Euclidean distance. It is a distance

Ampliar
developed by Avilasoto