There is an immense growth in the rate of machine learning, data analytics, and data science. This steady growth has caused several firms to seek professionals that will help them attain efficient business decisions. For many who are new to them, data science, data analytics, and machine learning may be a tad alien to them, but that is no cause for worry as this text breaks down what they are all about.
Data Science
Over the years, there have been several attempts to give data science a concise definition, but none has stuck. However, in 2010 Hugh Conway innovated a Venn diagram that explains what data science is all about. The diagram has three circles (subject expertise, math and statistics, and hacking skills). Once you can master all three, you have successfully grasped the concept of data science.
Data Scientist Skills
In any field of expertise, skills are required to be regarded as a professional, and data science is no exception. Here are five skills you need to become a data scientist;
- The capacity to effectively work with unstructured data from different areas like social media, videos, and the likes.
- Machine learning knowledge
- Multiple analytical functions must be comprehended
- SQL database coding experience
Data Analytics
The definition of data analytics is more concise as opposed to data science. A data analyst’s job is to visualize data, communicate data points, and do descriptive statistics for the final decision. A data analyst must demonstrate perfect database sense, data visualization perception, ability to create new views, and of course, they must have basic statistics understanding.
Data Analyst Skills
Here are the skills that qualify you as a data analyst.
- Data wrangling
- You must know mathematical statistics
- PIG/HVE comprehension
- You must fluently understand R and Python
Machine Learning
Machine learning also has a concise definition, just like machine learning. It is the practice of the extraction of data with the use of algorithms. The extracted data is then studied and then used to forecast trends in the future for the studied topic. Traditionally, machine learning entails predictive and statistical analysis to reveal patterns and concealed insights based on the aforementioned perceived data.
Facebook is the best example of the implementation of a learning machine. The learning algorithm of the social network garners every user’s behavioral information. This data is gathered based on the users’ past behavior; this means that the social media platform studies how you use the Facebook software, what you do when you first log in, it studies the way you like and comment on posts, and everything between. After carefully studying these patterns, Facebook uses that pattern to predict articles, notifications, and interests whenever you go online. This is why it seems that all social networks know what you want. Well, they never did until you started using it. Machine learning is responsible for all that magic.
However, all of the “magic” performed by data science, data analytics, and machine learning discussed in this text do not happen on their own, and they are obviously not easy to facilitate. This is why our IT service is here for you. Yes, you can implement all of these in your business/online platform with our help and a small fee. Our dedicated team will ensure you get all the functions mentioned here.
Machine Learning Engineer Skills
A person who specializes in machine learning is called a machine learning engineer, and these are some of the skills they have.
- You must have knowledge of programming skills
- You must have data evaluation and modeling skills
- You must know statistics and probability
- You must be an expert in the fundamentals of computer
Data Science Vs. Data Analytics Vs. Machine Learning
At this point, the differences, functions, and importance of data science, data analytics, and machine learning are quite clear. However, it will all be wrapped up here.
Data science is a generic term that covers machine learning, data mining, and other connected areas. A data scientist predicts what is to come based on what happens in the past. In contrast, a data analyst predicts what is to come based on facts gathered from many sources in cyberspace. Machine learning fits perfectly into data science. It utilizes a plethora of techniques to adapt to what a user wants. Conclusively, all three of them work together. Do not forget that you can always rely on our IT service to make all of this “magic” happen.