Hottest Data Science Trends For 2020

Introduction

While the world is flooding with new technology, various methods of handling the same are being discovered. With the advent of the Internet, the surface of almost all operations began changing. There was a huge surge in data collection and, initially, companies did not know how to handle this. However, as technology evolved through the decades, corporations and organizations that are now leading the world, realized the importance of digitization. Hence, there came about a massive digital revolution all over the world. People began shifting from traditional, cumbersome methods to completely digitized processes. And all of this happened drastically.

Nonetheless, there was still one problem that was not solved yet. The problem of handling data. Now, we must understand that data here means millions of lines of raw, unprocessed gibberish that only a computer can understand. While previously, employees were hired to analyse a very few number of data sets, and then another group took decisions based on it, the advent of Artificial Intelligence changed the dynamics of that situation. With Artificial Intelligence, came Data Science. Data Science was a subject that provided a solution to the problems related to processing data manually. Companies looked no further. They immediately began the implementation of Data Science in taking important decisions that would have otherwise taken years. With the help of this subject, it hardly took a week, a month at tops.

Latest Trends in Data Science

In the introduction of this article, we spoke about the importance of Data Science. Similarly, it is important to note one more thing, especially for the ones aiming to get the job of a Data Scientist- the trends in Data Science. While Data Science is a subject that is much needed in the world today, there are a few things we tend to overlook. However, those are the same things that you, as an aspirant, will have to take special care of. Your Data Science Course should be taken carefully. If your Data Science certification is on a topic that is still in the shadows, then it might take you longer to establish yourself as a Data Scientist in essence. There are a few fields, nonetheless, which have performed better than the others. In fact, they are so popular that they are used almost everywhere! Make sure that your Data Science Course is about one of the courses that we have listed below. This will not only help you secure a job for yourself, but if you are good enough, you can also gain a lot of reputation from the same. There are plenty of Data Science Online Courses that help you understand these topics. One such website is Great Learning. Through their comprehensive courses and easily understandable language, you are sure to learn what you need to.

1. Natural Language Processing : Natural Language Processing is probably one of the most important fields in Data Science and Artificial Intelligence right now. Data Science interview questions largely encompass this particular field as it demands a large part of the industry. Natural Language Processing is responsible for giving the computer, be it a chat bot, or a smartphone, or any other device, a voice to convey the results through our language. You must be aware that a computer speaks in binary language. But this has modified greatly. While previously these computers were not smart or adaptive enough to convey everything using natural languages, with the advent of this field, this has changed. Due to the ease of communication between a machine and it’s masters, Natural Language Processing has assumed a very important position in the world today
2. Automated Data Science : Automated Data Science is rather an interesting field to learn about. It is an enriching journey, full of critical discoveries and comprehensive understanding of not just the systems, but also the subject as a whole. In Automated Data Science, the machines are taught to work regularly, without the assistance of their human counterparts. When data is fed into them, they immediately know that they have to process the same. They run the required programs and do the needful to present a proper result as early as possible. They do not need to be told when and how to do the work unless the humans want to do so explicitly.
3. Data Security and Privacy : In the world today, everything is available with considerable ease. While this is a boon in some cases, it is actually a great matter of concern otherwise. Due to the availability of almost all information, privacy and security of a system are often under threat. It is no big deal to learn hacking today because of all the courses and materials and software that are available at a cheap price. Hence, to protect vulnerable data, Data Science is largely used to protect data against malicious sources. This is done by teaching the software or the computer how to safeguard the concerned information from unwarranted sources. Once it learns the process, it decides to apply it wherever necessary.
4. Data Science in Law and Legalities : Another field where Data Science shines as bright as a diamond is in Law and Legalities. Quite strange? It is actually not. In fact, this was only predictable. Data Science is a field that requires a machine to analyze data and based on the same, deliver some results. Once it has learned the trends and the ways to translate and deliver the results, it is almost always accurate. These important characteristics can be employed in legal matters. This will ensure an amount of transparency and impartiality while delivering justice or resolving complicated issues. Also, a machine never gets tired. Hence, it is more likely to work better than a human in strenuous situations.
5. Data Science in cloud-based operations: Data Science encompasses the usage of large volumes of data. This data needs to be stored somewhere. That is when the cloud comes to the rescue. In the recent past, say a decade or so, the amount of data that is to be processed has increased drastically. While that is great news given how efficient machines can process them, it is also a matter of worry when it comes to storage.
6. Data Mining: Data Mining is the process of revealing and ‘mining’ new information from databases that are already in existence. Data Mining is especially important since the world works on databases today. For everything that is done online, some information is collected from the users. This information is then stored in databases to further use the same when the user comes back to avail the particular services. These databases are analyzed by Data Scientists, with the help of smart machines, to unearth some unknown trends or information. Needless to say, it is one of the hottest topics available and it will be a good move to learn Data Mining.
7. Big Data: Big Data is referred to the large amount of data that a computer processes. This is essentially done to find out some more patterns and trends from the existing sets of information. Big Data is much in use since these patterns which are newly discovered, can be used to process or put the data to better use.
8. Graph analytics in business management: Graphs are some of the most important things when it comes to statistical analysis. And Statistics is synonymous to running a business successfully. Graphs represent a lot of valuable data in a format that is coherent and comprehensive. These graphs are driven by Data Science as they are made on the basis of the information collected and processed by the machines.
9. Internet of Things: Internet of Things is an important and interesting part of Data Science. It encompasses all the devices that are not computers in essence, but are powered by artificial intelligence. This is much too common these days as we aim to make all our devices capable of ‘thinking’.
10. Database management systems powered by Data Science: Databases are, in themselves, humongous storage areas for a large volume of data. When driven by Data Science and Artificial Intelligence, these databases can be used to gather and present more information and patterns than normal databases would have.

Conclusion

Now that we have seen the various trends in Data Science, and why they are so important in the world today, you may want to jump right into the task of learning these skills. But do not pounce in. Not yet. There is something important that you must understand before taking a step. And that is the quality of your knowledge. While Data Science Applications promise a lot of great things, trying to learn them simultaneously will only make your capabilities weaker. You certainly don’t need that! Hence, stick to one or two of these topics and do your best to learn accordingly. A Data Science Career is in much demand right now and the best way to step into the game is to stick to a few areas of knowledge. Nonetheless, the topic or topics that you choose to learn must be learnt in entirety. Do not leave spaces in your knowledge and you are sure to gain a strong footing in this field.

Data Science and Machine Learning go hand in hand and if you wish to outperform everyone else, this is what you need to focus on. Great Learning gives you the opportunity to do so. You can easily get your priorities right with their easy to understand courses, their comprehensive collection of study materials and great articles powering all of these.