Data science

All You Need to Know About to Become a Data Analyst!

Aspiring to be a data analyst? Then here is a complete guide to help you
Roles and responsibilities: A Data Analyst is a person who interprets data and turns it into information that can help make business-related decisions. Usually, data analysts gather information from different sources and trends. After collecting information then the data is thoroughly interpreted. The main responsibilities of a data analyst are to collect, interpret, analyze data and report it back to the relevant members of the business team. Along with this a data analyst also requires to work with teams within the business or management to establish business needs. He/She is also required to define new data collection and analysis processes. 

Average salary (per annum): US$69959

Qualifications: 

A degree in mathematics, or computer science or statistics, or economics 
Experience in data models, and reporting packages
Strong command over databases and programming 
Knowledge of collection, organizing, and analyzing data
An analytical mind for problem-solving

 

Top 3 Online Courses: 
Data Analyst Nanodegree- Udacity: will teach skills and tools needed to build a career in data analytics. The course covers both theory and practicals including regular 1-on 1 mentor calls with the active student community and career support services. It is the best one for students having experience in Python and SQL programming. 

Data Analyst Immersion (Thinkful): it is an intensive full-time training program. It has a customized schedule to help students to stay on track. The curriculum consists of Storytelling with data, Excel foundations, SQL foundation, Tableau, Business Research, Python foundation, and Capstone phase. During the final Capestone phase, students are trained to build their final projects along with two culture fit interviews. 

Data Science Specialization-Coursera: It is a program offered along with John Hopkins University which is a ten-course program that helps in understanding the data science pipeline from the basic levels. Students with a beginner level of experience in the Python programming language can cope with the course easily. 

 

Top 3 Educational institutionsInstitutes Offering the Program: with degree: 

Bachelor’s in Computer Science along with Data Science and Economics: Massachusetts Institute of Technology.  
BSc in Data Science and Masters in Data Science: Imperial College London
Bachelor’s and Master’s in Data Science: ESSEC – CentraleSupelec

 

Top Recruiters for This Job:
Amazon: Amazon is one of the biggest e-commerce companies around the world and is also among the top data science recruiters worldwide. Amazon is a giant of data and to comprehend the intensity of data it requires data analysts for its core operations from marketing streamlining, logistics, and inventory management to sales expectation and even HR analytics. 

Fractal Analytics: It has emerged as one of the top analytics services providers in the country.  The company has a global footprint boasting of several Fortune 500 companies from industries like retail, insurance, and technology. It has many branches in all parts of India hiring new positions. 

LinkedIn: The company was one of the first companies to have a team of data scientists. The operations of data scientists also need data analysts. Since it is a social networking service it allows its users to excel in their professional links. This also demands data interpreters to understand and enable businesses in making better decisions. 

Deloitte: It is part of the Big Four, offering services like consulting, financial advisory, tax audit, and enterprise risk across the globe since 1845. Data analysts at Deloitte undertake several analytics projects which may be multidisciplinary. Their responsibility is to simplify complex and large data and ensure that it is easy to understand my clients.

MuSigma: The company is the largest solutions provider relating to science decisions and analytics. Data analyst here would involve analyzing data, tuning it, and making it simple for evaluating results. These results then are used to make crucial decisions in the organizations.

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