What Are Data Science And Its Importance In 2021

As our globe enters the era of big data, the requirement for storage is grown. Today, Data science is a very necessary part of any industry as it gives a huge amount of data that are created. Nowadays, in the industries, Data science is the most discussing topic and its popularity is increasing day by day. Many companies start to implement techniques of data science for growing their business and increase the satisfaction of customers. Therefore, in this article, we are going to discuss that what is data science and its importance in 2021.

Due to the increasing demand for data scientists, many people having the interest to do Data Science Online Training from one of the best institutes. People who want to do Data science training in Delhi NCR can prefer ShapeMySkills Institute as it also offers live project training to their students.  

What is Data Science?

Using modern tools and techniques, Data science deals with a massive volume of data for finding hidden patterns from raw data and makes decisions of the business. For building predictive models, Data science uses difficult machine learning principles.

Why Data Science?

Data science makes better decision making and predictive analysis and it lets you:

• Model data by using various algorithms
• Communicate and visualize result via graphs, dashboards
• Do a deep study on the data
• Ask correct questions and find the exact reason for the problems etc

In practice, data science is already helping the industry of airlines. Airlines can optimize operations in many ways with the Data science help which includes:

• Plant route and decide whether to schedule direct or connect flights
• Make a decision, that which planes for purchasing for better overall performance.
• As per customer booking pattern, offer personalized promotional.
• Make a predictive analytics model for forecasting flight delays.

Data Science Fundamentals

Before starting to learn that what data science is, check some technical concepts you need to know:

• Machine learning: Data science backbone is Machine learning. Data scientists must know ML with basic knowledge of statistics.
• Statistics: It is the central part of data science. Complete knowledge of statistics helps you to extract more intelligence and get more meaningful results.
• Modeling: it is the part of machine learning and engages to identify which algorithm is appropriate for solving the problem and how to instruct these models. These mathematical models are enabling to make fast calculations and predictions based on what you already know regarding data.
• Databases: To become a capable data scientist, you must require to understand how databases work, how to manage, and how to extract data.
• Programming: For executing the data science project, some programming levels are needed. The most generally used programming language is Python and R. Python language is famous as it easy to learn and supports multiple libraries for Machine learning and data science.

Skills for Data Science

• Data Analysis: 

Skills: R, Python, Statistics

Tools: SAS, Jupyter, R Studio, MATLAB, Excel, RapidMiner

• Data Warehousing:

Skills: ETL, SQL, Hadoop, Apache Spark

Tools: Informatica/ Talend, AWS Redshift

• Data Visualization:

Skills: R, Python libraries

Tools: Jupyter, Tableau, Cognos, RAW 

• Machine Learning:

Skills: Python, Algebra, ML Algorithms, Statistics

Tools: Spark MLib, Mahout, Azure ML studio

What does A Data Scientist work?

A Data scientist studies data of business for extracting significant insights. By below given steps, data scientist solves the problem of business that is:

• For understanding the problem, ask correct questions

• Collect data from various sources
• Process the raw data and convert it into a format appropriate for analysis.
• Feed the data into a statistical model or Machine learning algorithm. ML algorithm is regression, decision tree, clustering, Support vector machines, Naïve Bayes, etc.
• For sharing with suitable stakeholders, prepare results.

Data Science Lifecycle

• Concept the Study: the first step of the data science project is to concept the study. In this, you require to understand the problem.
• Preparation of Data: It is the more important part of the data science lifecycle. Firstly, the data scientist needs to examine the data for identifying any gaps. During this procedure, some steps are included that are: Data integration, transformation, reduction, cleaning.
• Planning of Model: After cleaning the data, you need to choose a suitable model. The model which you use should be matched with the problem.
• Build the Model: Next step of the lifecycle is to building the model. Manipulate the data to discover useful details by using many latest tools and techniques.
• Communication: A good data scientist must be able to communicate to a business-minded audience.
• Operationalize: In this step, you need to give the final report, technical documents, and code.

Guys, this is all about data science and its importance. Hope this article helps you to understand the data science meaning or many other things. People who want to make their career in Data science are advised to do Data Science Online Training from ShapeMySkills Institute as it is one of the best Institutes of Data science training in Delhi, Noida. For the past 5 years, there are various Data science job vacancies in the market. Even in the US, Data science is the number one job. There are several job roles in Data science that are: Data scientist, Machine learning engineer, data consultant, data analyst, and more. If you want to make your career bright and want to become a data scientist, so join the Data science certification course in Noida at ShapeMySkills Institute.