“Data Science is the sexiest job of the 21st century.” This is termed by Harvard Business Review. We all know that what Oil did in the 20th century, Data will do for this one. It has an immense opportunity right now and this is just the beginning.
But most people think that data science is just a subject. No, it is not. It’s a mix of many skills combined in one. Even programming need to be great at coding, data structures, algorithms, and computer network, then why not data scientists? Data science is one of the growing fields of interest in the coming times.
What is data science?
Now, I am not going into much detail, but here is a basic overview:
Data is all about combining various tools, sources, and statistics to get your job done. It starts with extracting raw data to filtering it for specific matters. It is one of the most powerful tools which help businesses to make informed decisions and solve various problems.
Now, we are going into super-detail but you should know that without practice nothing is possible, so you should be making data-science projects as a beginner in this domain. These are some cool projects to try and learn.
The 5 Super-Skills for Data Scientists
As we gear up for new changes in technology, here are five basic skills which every data scientist or an aspiring data scientist should know:
Statistics and probability
Data science uses various algorithms to extract raw data. Statistics and probability help in making estimates of the data for further analysis. With a good knowledge of this, you would be able to explore and understand data in a better way, identify relationships between variables, determine various patterns, uncover the anomalies, make decisions, create data models, and predict future trends.
Programming and software
It is no surprise that data science is essentially technical and programming. Hence, it is especially important to know some technical skills, coding, and programming languages like Python, R programming, SQL, Java, and TensorFlow, to name a few. Even little familiarity with these could help a lot. Most of these languages serve the need for problem-solving and helps transform raw data into actionable insights.
Database management
Database Management consists of programs that can edit, index, and manipulate the database. With this, you can define and manage all your databases, manipulate data, format data, change the data structure, test and validate data, etc. It is imperative for data scientists to be able to thoroughly manage their databases.
Data wrangling and visualization
Once the data is extracted and organized, the next step entails analyzing it. It is imperative to understand how the data functions and what it could deliver to your business. Data wrangling helps in processing data for further analysis, mapping and combining relevant fields, and then cleaning it. Once the data is presented, the next step is data visualization. One should learn how to represent the data in graphical forms and communicate what the data is trying to say. It provides a comprehensive presentation of the data and helps in concluding with your decisions. Hence, it is one of the most essential skills for any data scientist.
Cloud computing
Data science often includes using cloud computing products and services to help professionals access their resources. All your data is stored in the cloud and hence it is important to have a fair idea of cloud computing. It provides access to various databases, frameworks, and other operational tools. Data science involves a lot of interactions with volumes of data, size, and availability of data and others, hence this forms essential skills for data scientists.
My recommendation will be to start with programming and then learn statistics & probability. These two are super important. The information is collected from tutors at FavTutor. You might have a different employee for Database management, but you should also know that. Also, I will recommend learning cloud computing, since the future is this niche.
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