gsmservice gsmservice
  • Our Story
  • How it Works
  • Browse
  • JOIN AS AN XPERT
  • Our Story
  • How it Works
  • Browse
  • JOIN AS AN XPERT
Want to become a
Data Analyst?

Join the World's First Social Learning App to accomplish your dream. Download the Xpert App to get to learn from genuises.

  • EXPERIENTIAL LEARNING

  • ONLY THE BEST

  • UNLIMITED
    ACCESS

  1. Technology
  2. Data Analysts

Which Data Analysts can I learn from?

LEARN

Abhishek Thakur

World's first 4xGM on Kaggle


LEARN

Allen Bonde

VP and Research Director at Forrester


LEARN

Anand S

CEO at Gramener: Insights as Data Stories


LEARN

Arvind Chandramouli

Head of Data Science at Tredence Inc


LEARN

Arvind Nagpal

Founder, TEG Analytics


LEARN

Avinash Patel

Senior Software Engineer at Accenture


LEARN

Dean Abbott

President of Abbott Analytics


LEARN

Dj Patil

Former U.S. Chief Data Scientist


LEARN

Dr Sunil Kumar Vuppala

Director-Data Science at ERICSSON


LEARN

Dr. Dj Patil

U.S chief Data Scientist


LEARN

Goda Ramkumar

Principal Data Scientist Ola cab


LEARN

Gregory Piatetsky

Founder and President of KDnuggets


LEARN

Hilary Mason

Founder of Fast Forward Labs


LEARN

Hindol Basu

CEO at Actify Data Labs


LEARN

Jeff Hammerbacher

Data scientist, cofounder at Cloudera


LEARN

Lillian Pierson

Lillian Pierson is a Data Strategist and traine...


LEARN

Manu Chandra

Co-founder at FN MathLogic Consulting Services


LEARN

Mayur Datar

Chief Data Scientist at Flipkart


LEARN

Naveen Xavier

Head Data & Analytics Products, Aditya Birla Gr...


LEARN

Neeraj Agarwal

Data Scientist at Walmart


LEARN

Noshin Kagalwalla

Managing Director of SAS Institute (India) Pvt ...


LEARN

Omprakash Ranakoti

Principal data scientist at Genpact.


LEARN

Praphul Chandra

Founder and Professor


LEARN

Prashant Warier

Data Analyst and Co-founder of Qure.Ai


LEARN

Prithvijit Roy

CEO and Co-Founder, BRIDGEi2i


LEARN

Rajeev Ramnarain Rastogi

Vice president,Machine learning at Amazon


LEARN

Rajeev Rastogi

Vice President, Machine Learning at Amazon


LEARN

Ronald Van Loon

CEO at Intelligent World


LEARN

Rwitwika Bhattacharya

CEO, Swaniti Initiative


LEARN

Sarita Digumarti

Co-founder, Jigsaw Academy


LEARN

Satnam Singh

Chief data analyst at Acalvio


LEARN

Satyamoy Chatterjee

Executive Vice President, Analyttica Datalab In...


LEARN

Shailesh Kumar

Chief Data Scientist, CoE AI/ML, JIO


LEARN

Sunil Kumar Vuppala

Director-Data Science at Ericsson


LEARN

Sunil Vuppala

Director of data science in Ericsson GAIA


LEARN

Viral Shah

CEO and Founder of Julia Computing


How is Xpert different?

Traditional Learning
via Classes/Courses

  • Academically Trained Teachers
  • Bookish Instructional Learning
  • Teachers have limited knowledge
    on real life application.
  • Marks and Fees gets you access
  • Time constraints
  • Offers certification/Degree
  • Strict Syllabus

Experiential Learning
at Xpert

  • Professional Geniuses
  • Hands-on Experience
  • Experts share and inspire learners
    with real life experiences
  • Passion to Learn is the sole criteria
  • Learn anytime anywhere
  • Unbeatable Exclusive knowledge
  • Unlimited Learning

Learn Only From The Best

Through experiential learning we give aspiring Data Analysts like you an opportunity to leverage the best experience of the best to solve real-world challenges.

DOWNLOAD APP HERE

What questions are bothering you?

  • Is PhD is requisite for Data analysts?
  • Is software background must data analysts?
  • Now Data Analysts is most sought profession but will it stay the same in the next 10-15 years?
  • What does a data analyst do exactly?
  • Is the data analyst's job more relevant to e-commerce companies rather than other sectors?Is Data analysis all about tools?

What can you do on Xpert?

LEARN DIRECTLY FROM TOP Data Analysts

Learn about Data Analysts' early days, education and career choice, challenges, success, techniques, and opinions.

STAY UPDATED ON THE INDUSTRY

If you're just getting into the game, you must stay abreast as to what key moves are being made by Data Analysts.

ASK ALL YOUR QUESTIONS

Your dilemmas would be addressed by the Data Analysts, inducing you to make the right career decisions and moves.

Who are we?

Our Mission

Making Experts Accessible to All

Xpert - is a social learning app to help you learn from the best. We are not your regular online course, but rather an experience that is beyond regular classes, lectures & assignments. We have India's top experts across each profession share their experiences, opinions, techniques & advice accumulated over the lifetime of their careers.

What is Data Analysis?

Anyone who learns from data is a Data analyst. Data analysis is defined as a process of cleaning, transforming, and modelling data to discover useful information for business decision-making. The purpose of Data Analysis is to extract useful information from data and taking the decision based upon the data analysis. Whenever we take any decision in our day-to-day life is by thinking about what happened last time or what will happen by choosing that particular decision. This is nothing but analysing our past or future and making decisions based on it. For that, we gather memories of our past or dreams of our future. So that is nothing but data analysis. Now same thing analyst does for business purposes, is called Data Analysis. To grow your business even to grow in your life, sometimes all you need to do is Analysis! If your business is not growing, then you have to look back and acknowledge your mistakes and make a plan again without repeating those mistakes. And even if your business is growing, then you have to look forward to making the business to grow more. All you need to do is analyse your business data and business processes. There are five types of analysis such as Text Analysis, Statistical Analysis, Diagnostic Analysis, Predictive Analysis & Prescriptive Analysis.

Brief description of all types of analysis is as follows. Text Analysis is also referred to as Data Mining. It is a method to discover a pattern in large data sets using databases or data mining tools. It used to transform raw data into business information. Business Intelligence tools are present in the market which is used to take strategic business decisions. Overall, it offers a way to extract and examine data and deriving patterns and finally interpretation of the data. Statistical Analysis shows ""What happen?"" by using past data in the form of dashboards. Statistical Analysis includes collection, Analysis, interpretation, presentation, and modelling of data. It analyses a set of data or a sample of data. There are two categories of this type of Analysis - Descriptive Analysis and Inferential Analysis. Descriptive Analysis analyses complete data or a sample of summarized numerical data. It shows mean and deviation for continuous data whereas percentage and frequency for categorical data. Inferential Analysis analyses sample from complete data. In this type of Analysis, you can find different conclusions from the same data by selecting different samples. Diagnostic Analysis Diagnostic Analysis shows ""Why did it happen?"" by finding the cause from the insight found in Statistical Analysis. This Analysis is useful to identify behaviour patterns of data. If a new problem arrives in your business process, then you can look into this Analysis to find similar patterns of that problem. And it may have chances to use similar prescriptions for the new problems. Predictive Analysis Predictive Analysis shows ""what is likely to happen"" by using previous data. The simplest example is like if last year I bought two dresses based on my savings and if this year my salary is increasing double then I can buy four dresses. But of course, it's not easy like this because you have to think about other circumstances like chances of prices of clothes is increased this year or maybe instead of dresses you want to buy a new bike, or you need to buy a house! So here, this Analysis makes predictions about future outcomes based on current or past data. Forecasting is just an estimate. Its accuracy is based on how much detailed information you have and how much you dig in it. Prescriptive Analysis combines the insight from all previous Analysis to determine which action to take in a current problem or decision. Most data-driven companies are utilizing Prescriptive Analysis because predictive and descriptive Analysis are not enough to improve data performance. Based on current situations and problems, they analyse the data and make decisions.

What are the qualities of a Data Analyst?

The purpose of data analysis is to reveal objective answers about an issue. However, effective data analysis requires the person doing the job must be curious. Broadly, the traits of a good data analyst are being both analytical and abstract. The person must understand the question, answer, and means to get to the answer. An effective analyst is one who understands how best to extract imperfect data using tactics make the information as objective as possible.:

  • Analytical
  • Dedicated
  • Diligent
  • Observant
  • Curious

Who are the top Data Analysts?

How can you start as a Data Analyst?

For starters, you will want to use a programming language so that you can record your work and share it with others. R is one programming language well-suited for data analysis and statistics. It’s a language that makes the computer to do the heavily lifting of computation and visualization so you can focus on thinking about your data. To make programming easier in R, there’s R Studio, which is a visual interface for writing code to crunch numbers and draw graphs with the R programming language. You can think of R Studio as an Excel-like program. If you are looking to learn data analysis, R Studio and the R programming language are must have tools. Above all else, they can make the process of learning data analysis easier.

What are the challenges of being a Data Analyst?

As data sets are becoming bigger and more diverse, there is a big challenge to incorporate them into an analytical platform. If this is overlooked, it will create gaps and lead to wrong messages and insights. Analysts may have sifted sand but missed gold – in haste, by oversight or technology gaps. The challenge here is for the analysts to understand the broader purpose of the data. Then use their expertise to analyse the datasets, and to piece together the insights for consumption. Visual analytics and setting up a rapid automation process can be the best ways to crunch enormous volumes of data, select and present the data for meaningful interpretation. The data loses value in the strategic decision-making process if the information is not precise or well-timed. Analysts are required to explore the voluminous data, gain business insights and weave a story in near real-time. Without a proper and contextualised narrative, even the greatest data is useless as an untold story. In most cases, analysed data is presented to a user or business leader who’s probably not a data specialist. The challenge then is to bridge the divide with effective communication. Unexpected or confusing results may be met with hostility – we can’t assume that we get the results we are after or they’re even understood. Analysts need to combat this with evidence (data) and clear, compelling presentation (Reports, Visualisation). As Sean Rad, founder Ad.ly, puts it: “Data beats emotions.”

How can you learn
Data Analysis at Xpert?

XPERT provides an opportunity to directly contact an expert in Data Analytics profession and get first hand information from them regarding career guidance and professional dilemmas. Apart from that we can know more about the industry trends and future of the Analytics professionals in various sectors. It provides an opportunity to understand what it takes for data analyst to take his career to the next level on their path to career peak.

Choose other Professions

  • AI Professional
  • Academician
  • Accountant
  • Activist
  • Actor
  • Advertising Professional
  • Anchor
  • Animator
  • Architect
  • Art Director
  • Artist
  • Athlete
  • Automobile Designer
  • Badminton Player
  • Baker
  • Banking Professional
  • Basketball Player
  • Blogger
  • Boxer
  • Business Analyst
  • Chef
  • Choreographer
  • Cinematographer
  • Civil Engineer
  • Comedian
  • Consultant
  • Content Writer
  • Copywriter
  • Corporate Communications Professional
  • Corporate Finance Professional
  • Corporate Strategy Professional
  • Cricketer
  • Cryptocurrency Expert
  • Dancer
  • Director
  • Disc Jockey
  • Economic Consultant
  • Economist
  • Editor
  • Engineer
  • Engineering Entrance Coach
  • Entrepreneur
  • Environmentalist
  • Event Manager
  • Fashion Designer
  • Fashion Merchandiser
  • Film Critic
  • Financial Analyst
  • Financial Trader
  • Fitness Instructor
  • Food Vlogger
  • Footballer
  • Gadget Reviewer
  • Gamer
  • General Counsel
  • Glamour Photographer
  • Golf Player
  • Graphic Designer
  • Hockey Player
  • Hotelier
  • Human Resource Professional
  • IAS Officer
  • IT Professional
  • Industrialist
  • Interior Designer
  • Investment Banker
  • Investor
  • Journalist
  • Kabaddi Player
  • Lawyers
  • Lifestyle Vlogger
  • Lyricist
  • MBA Coach
  • MakeUp Artist
  • Marketer
  • Media Correspondent
  • Medical Entrance Coach
  • Model
  • Motivational Speaker
  • Moto Vlogger
  • Music Composer
  • Music Producer
  • Musician
  • Nutritionist
  • Operations Professional
  • PR Professional
  • Painter
  • Photographer
  • Pilot
  • Poet
  • Politician
  • Producer
  • Product Manager
  • Project Manager
  • Property Manager
  • Psychiatrist
  • Publisher
  • Radio Jockey
  • Rapper
  • Sales Professional
  • Scientist
  • Script Writer
  • Sculptor
  • Singer
  • Software Developer
  • Spiritual Guru
  • Street Photographer
  • Stylist
  • Swimmer
  • TV Host
  • Tennis Player
  • Tests
  • Travel Vlogger
  • UPSC Coach
  • Venture Capitalist
  • Video Editor
  • Video Jockey
  • Videographer
  • Wildlife Photographer
  • Writer
  • Yoga Instructor

Want to learn Data Analysis?