Every year we are witnessing that Artificial Intelligence (AI) is booming and now there are many startups formed based on Artificial Intelligence. It is clear to everybody by far that Data Science is a problem-solving field.
With the availability of data everywhere, the science of using the data in a better way is gaining prominence. One can find lots of job offers in the field of Data Science by just doing a job search on any job portal. Let us now discuss the latest trends in Data Science.
Top Data Science Latest Trends 2019
1. Rapidly Growing IoT Industry
It is estimated that the worldwide technology spending on the Internet Of Things will cross $1 trillion by 2022, according to International Data Corporation (IDC) at an annual growth of 13.6%. It is also predicted that the IoT of the cellular industry will reach $3.5 billion in 2023 with a growth rate of 30% annually, according to Ericsson.
Now it has already become a common thing that we can control our home appliances like the air conditioner, television, etc. by just using our smartphones which have become possible only because of the Internet Of Things. Many companies are now investing in technology development due to the rapid growth trend of IoT devices such as smart devices like Microsoft Cortana and Google Assistant to automate regular things at home.
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All these rapid technological growth will lead to a vast amount of data collection, which will also lead to finding better means of managing and analyzing data in a proper and better manner. This will create a massive demand in the field of data science and also for data scientists.
2. Accessibility of Artificial Intelligence
Both small and large companies have been able to improve and enhance their overall business processes very efficiently by using Artificial Intelligence or AI. More complex tasks can be performed in a more precise and faster manner than humans by artificial intelligence.
Another best part about artificial intelligence is that it eliminates any chance of human error. It also improves the overall workflow along the way. Humans are now able to invest their time and focus more on critical tasks which in return enhances the quality of their service. Read: Real-world AI applications.
3. Predictive Analysis Evolution
Businesses can achieve their goals faster and are having a better competitive edge by including Big Data analysis in their crucial business strategies and decision making. Companies can find the reason for any specific events in real-time by using various tools in analyzing big data. The Predictive Analysis is very crucial in predicting what can happen in the future, which is done by analyzing the data.
Businesses are now able to create smarter business strategies by predicting customer behaviour using predictive analysis from the data collected. Thus, companies can retain the present number of customers and also target new customers in a better way.
4. Migration of Dark Data to Cloud
Dark Data is the type of data that is not transformed into digital format. This is a vast data reservoir that is not tapped yet. The dark data is going to be migrated to the cloud for predictive analysis which will be used by businesses to help them in more accurate future predictions.
5. Machine Learning
It is estimated that 40% of the work of data science will be on automation by 2020. There has been a rapid growth in the technology of machine learning, and this is the main factor for automation in machine learning. Businesses can extract smart and unique insights from Big Data by smartly using the combination of automation and powerful machine learning tools which cannot be obtained by skilled data analysts alone.
6. Rise of Regulations
GDPR has changed its policies related to data governance, and lots of companies are struggling to comply due to its fast implementation. These policies and regulations have affected data security, data handling, data processing, and consumer profiling. Now Businesses are needed to understand the impact of these regulations and policies on operations of future and current. Businesses take the help of Data scientists as they have proper knowledge about these rules and regulations related to Data Governance.
7. Competitive Edge
Those businesses which are up to date with present technology have a competitive edge in the present and future and are more likely to sustain because of their adaptability to the new technological trend. One should never stop at one toolset, platform or technology to become a good data analyst as the technology and solutions will keep evolving at a faster pace than ever before. There will be more demand in the market for experienced and skilful Data Science professionals.
8. Data Visualization and Storytelling
Data visualization and storytelling are reaching the next level every year, and many companies are moving to cloud from conventional data warehouses. Data will be more synchronized with the increasing use of cloud-based data platforms and integration tools within the organization. There will be higher accuracy in the storytelling as everyone will have only one version of the truth within the organization.
The data pipeline is becoming more sophisticated, and now it requires even more governance and integration tools. DataOps is relatively a new concept which is growing faster. DataOps is a process of delivering enhanced quality of data and data analysis, implementation of automated testing, automating the examination, analysis of data, preparation of data and collection of data.
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Blockchain technology has become very popular, thanks to Bitcoin. But many people don’t know the applications of blockchain other than in cryptocurrency. Blockchain is one of the most secured ledgers in the world which has many varieties of applications. For Data Security, Blockchain will be extensively used, and it has a far way to go in the future. Read about reasons you should learn blockchain technology.
11. Artificial Intelligence and Quantum Computing
Quantum computing is the most trending topic nowadays, which is being very actively researched by large companies like Google. As of now, Google claims to have to build a Quantum Computer which can do the calculation of 10 years by a supercomputer within 200 seconds by a quantum computer. Quantum computing has the potential to become the most significant quantum leap since the invention of the machine itself. All these indicate the extensive use of Big Data in the future in a much faster, efficient and straightforward manner.
12. Right to Explanation
In the future, lots of things are going to be on automation, and automated decision making will be one of those. To make the decision making fully automatic, it has to be explainable. There are two significant components in Artificial Intelligence (AI) which is very important to make a fully automated decision. Firstly, Artificial Intelligence should adhere to all the principles, core values, applicable regulations, and fundamental rights to ensure ethical practices and purpose. Secondly, Artificial intelligence should be reliable and robust, technically so as not to cause any unintentional harm.
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Data science has got a variety of applications and use cases. We hope this article has made clear the latest trends in data science and its benefits.
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Does machine learning use dark data?
Artificial intelligence and machine learning can rapidly and effectively transform dark data into insights for the healthcare and life sciences industries. These revelations might lead to new ideas, research, as well as medical development.
What is the storage location for blockchain data?
Since the blockchain is decentralized, there is no one location where it may be stored. As a result, it's stored on computers and systems all across the network. Nodes are the systems or computers that make up the network. Each of the nodes has a copy of the blockchain, which contains all of the network's transactions. It's a widely held belief that because blockchains are immutable, it's theoretically impossible to delete anything stored on them.
Is quantum computing posing a danger to blockchain technology?
Fault-tolerant quantum computers with sufficient computing power might decrypt all of the contemporary internet's encryption. When it comes to blockchain, this concern is extremely important. Due to the sheer transparency, security, and cost savings, more firms are adopting blockchain technology. The secured resources in blockchains are not readily separated from the encryption scheme in use. As a result, quantum technological developments render blockchain technologies extremely susceptible. It is impossible to accurately anticipate the advancement and development of future technologies.