Data Science Trends we’ve seen in 2022
The 2020s have seen a new wave of digital transformation, and data is at its core; we’re witnessing the revolution in IT. Voted the most demanding field of study, data science has created a new corner for hundreds of other small areas that can work coherently with data.
According to Google trends, the search for the term “data science” has increased about 2x in the past 12 months.
With companies accepting data as the core of their business for growth, small, medium, and large enterprises are collectively generating about 2.5 quintillion bytes in a day.
As data size gets bigger, the need for advanced tools to handle and process data is evident.
With the advanced tools cometh the jobs that pay you substantial salary packages. As the demand for skilled job professionals increases, the skill gap in data science has become the new normal.
If you’re willing to enter the data science field and get a 7-figure salary package, you can opt for Console Flare Data Science Certification Programs that can train you to prepare you for 7+ job profiles in data science.
As 2023 approaches, let us discuss the 3 biggest data science trends we have witnessed in 2022.
Data Science Trends in 2022
You may not have known that all of the world’s data, about 90% of it, has been created in the past 2 years only. As data gets bigger only, advanced fields of study like Machine Learning & Artificial Intelligence are being used by IT professionals to tackle data problems.
Here are 3 most seen data science trends this year:
1. Data For Everyone
2. DaaS – Data as a Service
3. Growth of Predictive Analysis
Let us now take you through each trend and explain why these trends are in our list of top 3 data science trends.
1. Data For Everyone: With the emergence of the platforms like Kaggle, thousands of free data sets are available online that anyone can work with. Data scientists, analysts, and engineers joining platforms like Kaggle made it easy for the community to access data and solve issues.
As the Indian government also working towards making data available to everyone on Data.gov.in, 2022 was a treat for data professionals across India and the globe.
Contains data sets from almost every domain (healthcare, banking, insurance, manufacturing, pharmaceutical, sales, real estate, and many more), these publicly available data sets can be unprecedentedly helpful for anyone who is either trying to enter the data science field or already working but wants to improve their knowledge and gain experience on working with real-time data.
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2. DaaS – Data as a Service: It is a newly coined term where organizations leverage data as part of their service to generate revenue.
According to Wikipedia, “In computing, data as a service, or DaaS, is a term used to describe cloud-based software tools used for working with data, such as managing data in a data warehouse or analyzing data with business intelligence. It is enabled by software as a service (SaaS). Like all “as a service” (aaS) technology, DaaS builds on the concept that its data product can be provided to the user on demand, regardless of geographic or organizational separation between provider and consumer.”
This is a business model or concept where two or more organizations barter, sell, or trade data in exchange for something of the same value(primarily data or money).
With a lot of new startups in the market, big companies leverage the power of data to benefit from small companies in exchange for services offered by them.
Facebook advertising is one of the best examples of Data as a Service.
Facebook offers advertising services on its platform and promises to show ads to the relevant audience based on the acquired data by Meta platforms in exchange for advertising costs.
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3. Growth of Predictive Analysis: When a crowd comes, finding relevant data is vital for organizations to prevent irrelevancy, build perfect strategies and save costs. Here comes the role of machine learning.
With the ML tools like Scikit-Learn, companies can now analyze and predict future trends with the help of past data. E-commerce companies like Amazon & Flipkart now use such tools to boost their sales during the festive season.
With the help of these predictive analysis tools, one can figure out the pattern of things based on the data received from past events.
Let’s hope the upcoming year brings more advanced trends into the picture. Hope you liked reading the article 3 Awesome Data Science Trends We’ve Seen This Year.
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