Top 14 Crucial Data Science Trends For The New Decade - ClicData (2023)

There are a considerable number of data and analytics trends to prep for 2019. As time goes on, it’s really important to take note of the present trend so that you can better explore the world of data science.

Weare all past the fact that big data and advanced analytics are very important-almost everyone knows this by now.

There are so many reasons why data is being generated by fast- almost doubling in size every two years. The introduction and evolution of IoT and connected devices is one of them. The ever-rising need for data is another important reason why there are so much data available.

What’s more important is the data science trends that are formed as the results of digitally-reliant solutions.

The ever-changing trends help finetune the business and opens more avenues for business analysts to make the optimum use of data.

To stay up-to-date, check out these hottest data science trends of this year that are set to propel your business for achieving more success.

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1. Rapidly growing IoT industry

According to IDC, the worldwide technology spending on the Internet Of Things would reach $1 trillion in 2022 at the CAGR of 13.6% over the period of 2017-2022.

According to the prediction of Ericsson, the IoT of the cellular industry is expected to reach $3.5 billion in 2023 at a CAGR of 30%.

Top 14 Crucial Data Science Trends For The New Decade - ClicData (1)

It has become quite a common thing that our smartphones are being used to control home appliances like TV, AC, etc. And, it has become possible due to the Internet Of Things. With smart devices like Google Assistant and Microsoft Cortana used in homes to automate the regular things, the growing IoT trend is grabbing the attention of most companies to invest in technology development, especially mobile application development services that make use of IoT.

This technological phenomenon will lead to collecting a vast amount of data, along with the means to manage and analyze it in a proper manner.

Industries in 2019 are focusing more on reaching new devices that are more efficient in collecting, analyzing, and processing data.

2. Accessible Artificial Intelligence

Another data trend you might have heard about is AI. Indeed, Artificial Intelligence is now mainly utilized to help both small and big businesses to improve their overall business processes. AI can perform more complex tasks in a faster and more precise manner than humans. The best part of using AI is that eliminates the chance of getting an error along the way and improves the overall flow of the work.

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Utilizing AI, a human can focus on more critical tasks and further enhance the quality of service.

Read also: AI’s Role in Your Business’ Future?

3. Evolution of predictive analysis

Big data analysis has always been a crucial strategy for businesses to have a competitive edge and achieve their goals. These days companies use different tools to analyze big data and find the reasons behind certain events that are happening at present. This is exactly the reason why Predictive Analysis plays a crucial role as it can tell you what may happen in the future.

So now, you might have realized that predictive analysis helps in using the gathered data to predict the customers’ behavior and so that businesses can come up with smarter strategies for targeting new customers and retaining the present number.

4. Dark data migration to the cloud

Information that is yet not transformed into digital format, is known as dark data. The important part is that dark data is a huge reservoir that is still untapped. The dark dataor analog data is expected to be migrated to the cloud so that it can be used for predictive analytics that will help the businesses in a significant manner.

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5. Machine Learning experience will play a vital role

It is expected that by 2020, over 40% of the data science work will be automated. The rapidly growing machine learning technology is the major driver of automation.

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With the smart combination of powerful machine learning and automation, businesses can extract unique and smart insights that are not possible to extract by skilled analysts.

6. The rise of regulations

GDPRhelped to spike the importance of data governance and it happened so fast thata lot of companies are still struggling to comply.

These regulations have a substantial effect on data processing and handling, consumer profiling, and data security. It has become mandatory for businesses not only to comply with these regulations but also to understand their impact on current and future operations. Data scientists who possess the proper knowledge of these regulations are going to be a huge help for businesses.

7. Have an edge over your competition

When it comes to running a business successfully, it’s imperative to stay up to date with the present technology. New solutions and technologies are evolving at a fast pace. A good data analyst never stops with one technology, platform, or toolset. Data processing is another skill vital to stay updated with the current data trend. The professionals who have proper experience and skills in data processing will be in more demand in the market.

8. Right to explanation

When it comes to having a fully automated decision, it should be explainable. The first thing you need to know is -what does actually “explainable” mean?

Atrustworthy AI has two major components.

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1. It should adhere to the fundamental rights, applicable regulations, and core values and principles so that AI can ensure an ethical purpose.

2. It should be technically robust and reliable because even with a good intention, a lack of technological expertise can cause unintentional harm.

9. Edge computing and analysis

The Edge computing system takes advantage of proximity by processing the information as physically close to sensors and endpoints as possible. This is the exact reason why it can reduce the latency and traffic in the network. According to Gartner, the evolution of cloud computing and edge computing is becoming complementary models in 2019. The cloud services are expanding not to just live in the centralized server but also in distributed on-premises servers and edge devices. This model would not only lower the latency but at the same time, it would also reduce the cost for an organization to process real-time data.

10. Data visualization and storytelling

Another crucial data trend that is very much prominent – data storytelling and visualization will reach the next stage by the end of this year, 2019. The reason is pretty straightforward: most organizations are moving their conventional data warehouses to the cloud. With a surge in the use of cloud-based data integration tools and platforms, data would be more united. It means more and more employees will be able to accurate stories with the available data using a single truth version of the organization.

11. DataOps

The concept of DataOps has already started to emerge this year and it will grow more for sure this year. The reason is simple- the data pipeline has become more complex and requires even more integration and governance tools. DataOps applies the Agile and DevOps methods to the entire data analytics lifestyle. The DataOps involves the processes like the collection to preparation to analysis, testing automation, implementation of automated testing, and delivery for providing enhanced data quality and analysis.

12. Blockchain

Blockchain is a major technology that works behind cryptocurrencies like Bitcoin. Blockchain is a very secure ledger and has a variety of applications. When it comes to establishing strong data security, Blockchain can have a far-reaching implementation in the coming time.

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13. Quantum Computing and AI

Quantum computing is a very active research topic as of now. Quantum computing has several crisp points:

  1. It has the potential to become the greatest quantum leap since the invention of the computer itself.
  2. A quantum computer that can manipulate 100qubits to 200 qubits can easily break every single encryption algorithm.
  3. According to the experts, it could take 5-15 years to build a fully functional quantum computer which would herald a new era in the history of mankind.

14. Better user experience drives greater adoption

Advancement in speech and text recognition means users can ask questions to businesses using natural language. AI-assisted data discovery can easily mine data for insights and propose what’s new, exceptional, or different. ChatBots and personal assistance provide seamless access to the basic number used to run a business efficiently. With the use of a real-time system as a foundation, managers can finally get the dashboard with all the viable information that they need for running a business successfully.

So, now you might have become familiar with the trends in Data Science. If you are a data scientist or a running a business, with proper data science strategy, you can give solid boos to the overall performance of your business.


What are the current trends in data science? ›

Big data analysis automation

Much growth is to be visualized in analytic process automation (APA) which by offering many insights and predictive abilities, especially about the role of computing power in the decision-making process, will benefit business organizations in achieving efficiency in both output and cost.

Which four trends are driving the importance of data science? ›

Better Naming Conventions. Sustainable Applications Outside of Technology Industries. Data-centric Modeling. Decision Science Expertise.

What do you think is the most important emerging trend in the data space? ›

Cloud Automation and Hybrid Cloud Services

One of the big data predictions for 2022 is the increase in the use of hybrid cloud services. A hybrid cloud is an amalgamation of a public cloud and a private cloud platform. Public clouds are cost-effective but do not provide high data security.

What are the important topics in data science? ›

The syllabus of Data Science is constituted of three main components: Big Data, Machine Learning and Modelling in Data Science. The major topics in the Data Science syllabus are Statistics, Coding, Business Intelligence, Data Structures, Mathematics, Machine Learning, and Algorithms, amongst others.

What are key trends in data? ›

Data Science, Big Data Analytics, and Artificial Intelligence are the key trends in today's accelerating market. As more organizations are adopting data-driven models to streamline their business processes, the data analytics industry is seeing humongous growth.

What are the top trends of data analytics in 2022? ›

The key trends in today's fast-paced market are Data Science, Big Data Analytics, and Artificial Intelligence. The Data analytics industry is expanding rapidly as more companies adopt data-driven models to streamline their business processes.


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