A data scientist is a professional with the ability to collect massive amounts of data to examine and synthesize the data into actionable plans for organizations. Data analysts accumulate process and perform statistical analyses of data. Their skills may not be as advanced as data scientists, but their intentions are the same – to explore how data can be used to answer questions and solve difficulties.
WHY DATA SCIENCE AND DATA ANALYTICS SKILLS ARE REQUIRED?
Data science and analytics have come a long way over past few years. That is the reason why they are crucial part in understanding the working of many industries, however complex and intricate. Let’s discuss some of the reason why Data analytics training course will always remain crucial part of economy and why you need these skills.
WHICH DATA SCIENCE AND DATA ANALYTICS SKILLS YOU NEED
1. Being capable of handling unstructured data
Unstructured data refers to any data that cannot be made to fit into any database tables. As a data scientist, you must be able to work with a lot of unstructured data. Some software that you need to know how to use for this purpose are Microsoft HDI insight, NoSQL, Apache Hadoop, Polybase, Presto etc.
2. Good knowledge of Mathematics and Statistics
A good understanding of statistics is essential for anyone looking to become a data analyst. You must be familiar with all kinds of statistical concepts such as distributions and tests. Also, making predictions requires that you are familiar with the basic operation of calculus and linear algebra.
3. Using data to tell a story
It is always easier for clients to understand data analytics if it is presented in a visual format using graphs, charts etc. Therefore you must have the capability to visualize raw data in a form that the layman can understand.
4. Programming Skills
As a data scientist, you will be working with a lot of software that will require you to enter the code manually. As such, you must have a good knowledge of programming languages such as R and Python, which are normally used in data analytics. You must be able to write, understand and correct any code no matter the circumstances.
5. Working on Projects
You must take up some live project training so that you get some hands-on experience in the field. This is important since most companies are looking for data scientists who are experienced in the field. You can join Data analytics course to work on live projects.