Data Analytics Courses: Syllabus, online classes, offline institutes citywise, UG, PG, and diploma colleges in India
- Jatin Sharma
- Updated Date: July 17, 2023
Table of Contents
Data analytics is a popular field of study that can be pursued at top universities and certification institutes. It can be studied as a standalone program or as part of a specialization, such as business analytics, data science, big data, or machine learning. The future of data analytics is bright, as the demand for data-driven insights continues to grow.
There are many benefits to obtaining a data analytics certification. It can help you kickstart a career in the field, as it demonstrates your skills and knowledge to potential employers. Additionally, data analytics certifications are often more affordable than traditional degrees, and they can be completed online, making them convenient for working professionals.The scope of data analytics is vast, with applications in business, government, and healthcare.
Some of the top platforms that offer best online data analytics courses data analytics courses online include Coursera, Simplilearn, edX, and Udemy. These platforms offer a variety of courses, from beginner to advanced levels, so you can find one that fits your needs and goals. The data analytics salary in India varies depending on their experience, skills, and location. However, according to Glassdoor, the average salary for a data analyst in India is ₹6,00,000 per year.
In addition to online courses, you can also pursue an undergraduate or postgraduate degree in data analytics. This can be a good option if you want to gain a deeper understanding of the field and have the opportunity to network with other professionals.
No matter how you choose to pursue a career in data analytics, it is important to have strong analytical and problem-solving skills. You should also be able to work independently and as part of a team. With the right skills and education, you can have a successful career in this growing field.
Data analytics courses fees and syllabus In 2023
Here is a table of Data analytics fees and data analytics course syllabus
| Courses | Institutes | Fees | Syllabus |
|---|---|---|---|
|
Data Analytics Certificate
|
Coursera
|
₹4,015 |
Data collection and preparation, data analysis, data visualization, and communication of results. |
|
Data Analytics Bootcamp
|
Udemy |
₹16,309 |
Data wrangling, data cleaning, data mining, machine learning, and statistical analysis.
|
|
Data Analytics Degree
|
University of California, Berkeley
|
₹9,83,467 |
Data structures and algorithms, probability and statistics, machine learning, and data visualization.
|
Please note that these are just a few examples of Data analytics courses and their fees. The actual fees and syllabus may vary depending on the institution and the specific course.
Here are some of the topics that are typically covered in a Data analytics courses:
- Data collection and preparation
- Data analysis
- Data visualization
- Communication of results
- Data wrangling
- Data cleaning
- Data mining
- Machine learning
- Statistical analysis
Data analytics is a rapidly growing field, and there is a high demand for data analysts in a variety of industries. If you are interested in a career in data analytics, I encourage you to explore the many resources available to help you get started.
What is Data Analytics?
Data analytics meaning is the process of collecting, cleaning, and analyzing data to extract meaningful insights. It is a broad field that encompasses a wide range of techniques and tools. Data analytics can be used to solve a variety of problems, from identifying trends to predicting future behavior.
Data analytics is becoming increasingly important in today’s world. As the amount of data that is generated continues to grow, businesses and organizations are looking for ways to make sense of it. Data analytics can help them to do this by providing them with insights that they can use to improve their operations, make better decisions, and gain a competitive advantage.
Data analytics definition: Data analytics is a powerful tool that can be used to improve businesses and organizations in a variety of ways. It is a rapidly growing field, and there are many opportunities for those who are skilled in data analytics.
What is Data Analytics courses?
A data analytics courses is a program of study that teaches students how to collect, clean, analyze, and interpret data. Data analysts use their skills to help businesses make better decisions by identifying trends, patterns, and insights in data.
Data analytics courses typically cover topics such as:
- Data mining
- Data warehousing
- Data visualization
- Predictive analytics
- Statistical analysis
- Machine learning
Data analytics courses can be taken at a variety of levels, from introductory to advanced. There are many different online and in-person programs available, and the cost of a data analytics courses can vary depending on the program.
If you are interested in a career in data analytics, a data analytics courses can provide you with the skills and knowledge you need to succeed. Data analysts are in high demand, and the skills you learn in a data analytics applications course can be applied to a variety of industries.
Here are some additional tips for pursuing a career in data analytics:
- Gain experience. Internships and volunteer opportunities can help you gain valuable experience and make connections in the field.
- Network. Attend industry events, join online forums, and connect with people on LinkedIn.
- Stay up-to-date on the latest trends. The field of data analytics is constantly evolving, so it’s important to stay up-to-date on the latest trends. Read industry publications, attend conferences, and take online courses.
With hard work and dedication, you can build a successful career in data analytics.
What are the types of Data analytics?
There are many different types of data analysts, each with their own specific skill set and responsibilities. Some of the most common types of data analysts include:
- Business intelligence analysts: Business intelligence analysts use data to help businesses make better decisions. They collect data from a variety of sources, clean and analyze it, and then create reports and dashboards that help businesses track their performance and identify areas for improvement.
- Predictive analysts: Predictive analysts use data to predict future events. They use statistical models and machine learning algorithms to identify patterns in data that can be used to make predictions about future trends.
- Descriptive analysts: Descriptive analysts use data to describe what has happened in the past. They use statistical methods to summarize data and identify trends.
- Qualitative analysts: Qualitative analysts use data to understand the meaning of human behavior. They use methods such as interviews, focus groups, and surveys to collect data about people’s thoughts, feelings, and experiences.
- Quantitative analysts: Quantitative analysts use data to measure and quantify things. They use statistical methods to analyze data and identify patterns.
Data analytics tools list:
There are many data analytics tools available, each with its own strengths and weaknesses. Some of the most popular data analytics tools include:
- Microsoft Excel: Excel is a powerful spreadsheet software that can be used for basic data analysis tasks. It is a good choice for beginners who are just starting to learn about data analytics.
- R: R is a free data analytics courses and open-source programming language that is widely used for data analysis. It is a more powerful tool than Excel, but it can be more difficult to learn.
- Python: Python is another popular programming language that is used for data analysis. It is similar to R in terms of its power and flexibility, but it is easier to learn.
- Tableau: Tableau is a data visualization software that can be used to create interactive dashboards and reports. It is a good choice for businesses that want to share their data with others.
- Qlik Sense: Qlik Sense is another data visualization software that is similar to Tableau. It is a good choice for businesses that want to create interactive dashboards and reports.
- Power BI: Power BI is a data analytics and business intelligence platform developed by Microsoft. It is a good choice for businesses that want to integrate their data from different sources and create interactive dashboards and reports.
These are just a few of the many data analytics tools available. The best tool for you will depend on your specific needs and requirements.
Read more: Best Data analytics courses institutes in Bangalore
What is a big data analytics?
Big data analytics meaning: A big data analytics courses is a professional who collects, analyzes, and interprets large sets of data. Big data analytics definition is big data analytics use their skills to help businesses make better decisions by identifying trends, patterns, and insights in data. The big data analytics lifecycle is a process that organizations use to collect, store, analyze, and visualize big data.
Tools of big data analytics, big data analytics software data use a variety of tools and techniques to analyze data, including:
- Data mining
- Data warehousing
- Data visualization
- Predictive analytics
- Statistical analysis
- Machine learning
Application of big data analysts typically have a bachelor’s degree in a related field, such as computer science, statistics, or mathematics. Some employers may also require a master’s degree or experience in the field.
Types of big data analytics analytics
Big data analytics is the process of analyzing large and complex data sets to extract meaningful insights. There are some big data analytics examples:
- Descriptive analytics: This type of analytics is used to describe what has happened in the past. It can be used to identify trends, patterns, and outliers.
- Diagnostic analytics: This type of analytics is used to understand why something happened. It can be used to identify the root causes of problems.
- Predictive analytics: This type of analytics is used to predict what will happen in the future. It can be used to forecast demand, identify risks, and make decisions.
- Prescriptive analytics: This type of analytics is used to recommend actions. It can be used to optimize processes, allocate resources, and make decisions.
These four types of analytics can be used together to gain a comprehensive understanding of data and make informed decisions.
Characteristics of big data analytics include: Volume: Big data sets are typically very large, containing terabytes or even petabytes of data.
- Velocity: Big data sets are often generated in real time, which means that they need to be analyzed quickly.
- Variety: Big data sets can contain a variety of different data types, including structured, semi-structured, and unstructured data.
- Veracity: Big data sets can be noisy and contain errors, which means that it is important to clean and validate the data before analysis
What is Iot data analytics?
IoT data analytics is the process of collecting, analyzing, and interpreting data collected from IoT devices. This data can be used to improve business performance, make better decisions, and gain a deeper understanding of the world around us.
IoT data analytics can be used for a variety of purposes, including:
- Predictive maintenance: IoT data can be used to predict when equipment is likely to fail, so that preventive maintenance can be performed. This can help to avoid costly downtime and improve the overall reliability of equipment.
- Fraud detection: IoT data can be used to detect fraudulent activity, such as unauthorized access to a facility or theft of goods. This can help to protect businesses from financial losses.
- Product optimization: IoT data can be used to optimize products and services. For example, data from smart thermostats can be used to optimize heating and cooling systems, and data from smart meters can be used to optimize energy consumption.
- Customer insights: IoT data can be used to gain insights into customer behavior. This can help businesses to improve their products and services, and to target their marketing campaigns more effectively.
IoT data analytics is a powerful tool that can be used to improve businesses in a variety of ways. As the Internet of Things continues to grow, IoT data analytics will become even more important.
Resources you need to know about Data analytics course In 2023:
Data analytics is the process of collecting, cleaning, analyzing, and interpreting data to gain insights that can be used to make better decisions. There are many different aspects of data analytics, including data mining, statistical analysis, and machine learning. Data analytics is used in a wide variety of industries, including business, government, and healthcare.
- Data analytics basics: Data analytics basics include understanding the different types of data, how to collect data, and how to clean data.
- Data analytics consulting: Data analytics consulting firms help businesses to use data analytics to improve their operations.
- Data analytics courses online free: There are many free online courses available that can teach you the basics of data analytics.
- Data analytics services: Data analytics services provide businesses with the tools and resources they need to use data analytics.
- Data analytics subjects: Data analytics subjects include statistics, machine learning, and data mining.
- Data analytics with Python NPTEL: NPTEL offers a free online course on data analytics with Python.
- Data science analytics: Data science analytics is a subfield of data analytics that uses data science techniques to analyze data.
- Financial data analytics: Financial data analytics is a type of data analytics that is used to analyze financial data.
- Future of data analytics: The future of data analytics is bright, as the demand for data-driven insights continues to grow.
- Importance of data analytics: Data analytics is important because it can help businesses to make better decisions, improve their operations, and identify new opportunities.
- Google Analytics filter data: Google Analytics filters data in the following order: 1. Dimensions, 2. Metrics, 3. Filters, and 4. Segment.
Data analytics Roadmap In 2023
A data analytics roadmap is a plan that outlines the steps you need to take to become a data analyst. It can help you stay on track and make sure that you are learning the right skills. There are many different ways to learn data analytics, but some of the most common methods include:
Here are some of the steps that you might include in your data analytics roadmap:
- Learn the basics of data analysis. This includes learning about data types, data cleaning, and data visualization.
- Learn about different data analysis techniques. This includes learning about descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.
- Learn how to use data analysis tools. This includes learning about software like Excel, R, and Python.
- Get hands-on experience with data analysis. This could involve taking online courses, working on data analysis projects, or getting a job as a data analyst.
- Network with other data analysts. This can help you learn from others and find job opportunities.
Data analytics books In 2023
Some of the best data analytics books for beginners and experienced professionals:
- Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking by Foster Provost and Tom Fawcett: This book provides a comprehensive introduction to data science, covering topics such as data mining, machine learning, and statistical modeling.
- Introduction to Statistical Learning: With Applications in R by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani: This book is a great resource for learning about statistical methods for data analysis. It includes a variety of real-world examples and exercises.
- Python for Data Analysis by Wes McKinney: This book is a great introduction to using Python for data analysis. It covers topics such as data wrangling, data cleaning, and data visualization.
- R for Data Science by Hadley Wickham and Garrett Grolemund: This book is a great introduction to using R for data analysis. It covers topics such as data wrangling, data cleaning, and data visualization.
- Data Smart: Using Data Science to Transform Information into Insight by Peter Bruce: This book provides a practical introduction to data science. It covers topics such as data collection, data cleaning, and data visualization.
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron: This book is a great resource for learning about machine learning using Python. It covers a variety of machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
Data Analytics courses with placement In 2023
Here is a table of data analytics courses with placement and institute name:
Here are some additional details about each data analysts course with placement:
- Data Analytics and Machine Learning Course at Simplilearn: Simplilearn top courses. this course is a more advanced program that focuses on both data analytics and machine learning. The course covers topics such as regression analysis, clustering, and natural language processing. The course is taught by experts in the field, and it includes a hands-on project that allows students to build a machine learning model.
- Data Science Course at Great Learning: This course is a comprehensive program that covers all aspects of data science, from data collection and cleaning to data visualization and machine learning. The course is taught by experienced professionals with industry experience, and it includes a capstone project that gives students the opportunity to apply their skills to a real-world problem.
- Data Analytics Bootcamp at Udemy: The Udemy course cost is a more affordable option that covers the basics of data analytics. The course is taught by a certified data analyst, and it includes a variety of hands-on exercises.
- Data Analytics Courses for Beginners at Coursera: This Coursera course cost is a free online course that covers the basics of data analytics. The course is taught by a professor from Duke University, and it includes a variety of video lectures and interactive exercises.
What are the career options/jobs available after completing a data Analytics courses?
Here are some of the career options/jobs available after completing a data analytics courses:
These are just a few of the many career options available to data analysts. With the growing demand for data-driven decision-making, the job market for data analysts is expected to continue to grow in the years to come.
Data analysts who are interested in advancing their careers may also want to consider pursuing a master’s degree in data analytics or a related field. A graduate degree can help data analysts develop the skills and knowledge they need to move into more senior-level positions.
Data analytics job descriptions typically list the following skills and qualifications:
- Strong analytical skills
- Experience with data mining and machine learning
- Knowledge of statistical software
- Excellent communication and presentation skills
Data analytics resumes should highlight the following:
- Your experience with data analysis
- Your skills in data mining and machine learning
- Your knowledge of statistical software
- Your ability to communicate and present data effectively
What are the data analytics internship options?
There are many different data analytics internship options available, depending on your interests, data analytics projects and experience level. To be successful in a data analytics internship, you should have strong analytical and problem-solving skills. You should also be proficient in data mining, data visualization, and programming languages such as Python and R.
Data analytics is a growing field, and there is a high demand for skilled data analysts. If you are interested in a career in data analytics, an internship is a great way to gain experience and learn the skills you need to succeed.
When applying for data analytics internships, be sure to highlight your skills and experience in data analysis, data mining, data visualization, and programming. You should also be prepared to answer questions about your interest in data analytics and your career goals. Some popular options include:
- Data Analyst Intern: This is a general internship that will give you the opportunity to learn about data analysis and data mining. You will typically work on projects that involve collecting, cleaning, and analyzing data.
- Business Intelligence Analyst Intern: This internship will focus on using data to improve business decision-making. You will typically work on projects that involve developing and implementing data-driven solutions.
- Data Scientist Intern: This internship is for students with strong math and programming skills who are interested in developing new machine learning algorithms. You will typically work on projects that involve building and testing data models.
Data Analytics job for freshers In 2023
Here is a table of data analytics jobs for freshers with salary in INR:
Please note that these are just estimates and the actual salary may vary depending on the company, location, and experience of the candidate.
Here are some of the skills that you need to have to be a successful data analyst:
- Strong analytical and problem-solving skills
- Excellent communication and presentation skills
- Ability to work independently and as part of a team
- Proficiency in data analysis software, such as SQL and Python
- Knowledge of data visualization tools, such as Tableau and Power BI
Data analytics top companies In 2023
These are just a few of the many data analytics companies in India. The average salary for data analysts in India varies depending on the company, location, and experience level. However, the salaries listed above are a good starting point for research.
If you are interested in a career in data analytics, I recommend that you research the different companies in India and find one that is a good fit for your skills and interests. Data analytics companies in India with their average salary:
| Company | Location | Focus Area | Average Salary (INR) |
|---|---|---|---|
|
Mu Sigma
|
Bengaluru |
Decision science and big data
|
5,73,913
|
|
Fractal Analytics
|
Gurgaon |
Analytics and artificial intelligence
|
17,00,000
|
|
Manthan |
Mumbai |
Data analytics and business intelligence
|
12,00,000
|
|
Latent View |
Bengaluru |
Data analytics and big data |
9,46,769 |
|
Tiger Analytics
|
Bengaluru |
Data analytics and artificial intelligence
|
15,00,000
|
|
Absolutdata |
Bengaluru |
Data analytics and big data
|
7,14,237
|
|
Convergytics |
Gurgaon |
Data analytics and customer experience
|
6,00,000
|
|
UST Global
|
Bangalore
|
Data analytics and IT services
|
8,00,000
|
|
Cartesian Consulting
|
Mumbai |
Data analytics and consulting
|
10,00,000
|
Which is the Best Data Analytics Courses Online?
| Parameters | Coursera | Simplilearn | Udacity | Udemy |
|---|---|---|---|---|
|
Industry or College Accredited Courses
|
Yes |
Yes |
No |
No |
|
Duration
|
Few weeks to 6 Months
|
6 Months - 11 Months
|
Few weeks to 4 Months
|
Less than a week
|
|
Fees
|
Pay as per Study Pace (Certification Fee: INR 2,000)
|
INR 7,000 - INR 2,25,000
|
Up to INR 80,000
|
INR 455 - INR 3,499
|
|
Discount Coupons
|
No |
No
|
Yes |
Yes
|
|
EMI Options
|
No |
Yes |
Yes |
Yes |
|
Assignments
|
Yes |
Yes |
Yes |
- |
|
Coding Exercises
|
Yes |
No |
No |
Yes |
|
Projects |
Yes |
Yes |
No |
Yes |
|
Placement Assistance |
No |
Yes |
No |
No |
Best 5 Data Analytics Courses in India In 2023
The table below features the Best Data Analytics courses in India with certification to kickstart a career in Data Analytics.
Best Data Analytics Courses on Coursera In 2023
Coursera Data Analytics training courses including coursera google data analytics courses are taught by experts with years of experience in Data Analytics and related fields. The duration of the Data Analyst course is not more than 12 months. Students have the option to complete the Data Analyst course in 1 month, 2 months, or 6 months. The Data Analyst course fee varies according to the study pace. Also check best coursera courses with placement
Best Data Analytics Courses on Simplilearn In 2023
Simplilearn data analytics courses are available under the popular course category, master’s program category, and university postgraduate programs category. Explore the table below to discover the top simplilearn courses on data analytics courses on as per total student ratings.
Udacity Data Analytics Courses In 2023
Data analytics courses on Udacity are designed to teach the skills required to become a data analyst. Udacity offers both free and paid data analyst courses. Here are some of the best data analytics courses on Udacity.
Best Data Analytics Courses on Udemy
The data analytics courses by Udemy are the bestselling data analytics courses online. Udemy offers beginner-friendly and affordable data analytics courses. As part of the new student offer; Udemy offers courses for up to 90% off. Click here to check free udemy coures
Diploma in Data Analytics
The applicant should have a Bachelor’s degree in Science/Engineering/Business Analytics/Commerce/Mathematics/Computer Applications or a Masters’s degree in Mathematics/Business/Statistics/Commerce with 50% or equivalent passing marks to apply for an undergraduate or postgraduate diploma in data analytics.
Best Bachelor Degree in Data Analytics In 2023
Check out the top 10 undergraduate programs in data analytics as per the Analytics India Magazine (AIM) report. The eligibility criteria for these programs are basic knowledge of statistics, mathematics, engineering, or economics.
Best Masters Degree in Data Analytics In 2023
The following table includes the top postgraduate programs masters in data analytics in India in msc data analytics as per academic ranking 2021 by Analytics India Magazine (AIM). The following masters in data analytics programs have been evaluated based on 5 crucial parameters: Certification Value or Accreditation, Return on Investment, Student Enrollment, Program Structure, and Admission Criteria.
| Program Name (College) | Fees (INR) | Eligibility | Duration |
|---|---|---|---|
|
PGP in Business Analytics - GreatLearning
|
INR 2,50,000
|
- |
11 months
|
|
PGDM Big Data Analytics - GIM Goa
|
INR 18,31,200
|
Minimum of 50% in bachelor’s degree and appeared for exams like CAT, XAT, CMAT, GMAT
|
2 years
|
|
MBA in Business Analytics - RACE
|
- |
50% in BTech/BE in any stream, BSc/BCA in CS/IT/Electronics, MCA/MSc in IS/IT/CS, BCom, BBA with Computer Applications and Mathematics or Statistics in 10+2 along with 2 years of work experience
|
12 – 24 months
|
|
MBA in Data Science and Data Analytics - Symbiosis Pune
|
INR 10,50,000
|
Bachelor’s degree with 50% and mathematics in 10+2
|
2 years
|
|
PGP in Data Analytics - Simplilearn
|
INR 2,12,415
|
A bachelor’s degree with at least 50%
|
8 months
|
|
MBA in Business Analytics - Symbiosis Pune
|
- |
Minimum of 50% in bachelor’s degree and at least 2 years of work experience
|
- |
|
PGP in Applied Statistics & Analytics - Sunandan Divatia
|
- |
A bachelor’s degree in statistics with 60% marks or a bachelor’s degree in any discipline with 60% and 60% in class 12 examination with statistics/mathematics/mathematics & statistics
|
- |
|
ECP in Data Analytics - IIM Rohtak
|
INR 60,000
|
Graduation from any recognized university and a minimum of 2 years of work experience
|
5 months
|
|
Advanced Certificate in Data Analytics - Edvancer
|
INR 83,900 (Live online) INR 55,900 (Self-paced)
|
Graduation or pursuing in any field
|
180 hours
|
|
MBA in Business Analytics - Chitkara University
|
- |
Bachelor’s degree in any stream with a valid score of CAT/MAT/NMAT/XAT along with GD followed by personal interview
|
2 years
|
MBA in Data Analytics In 2023
These are just a few of the many MBA in data analytics programs available in India. The programs vary in terms of their curriculum, cost, and admission requirements. However, all of these programs offer students the opportunity to learn the skills and knowledge they need to succeed in a career in data analytics.
If you are interested in pursuing an MBA in data analytics, I recommend that you research the different programs available and find one that is a good fit for your skills and interests. You can also check out online resources like GMATClub and Clear Admit to learn more about MBA in data analytics programs.
Top Data Analytics Colleges in India 2023
Data Analytics Courses by Government Colleges In India In 2023
Due to the popularity of Data Analytics, Big Data, and Data Science; government institutions like IITs, IIMs, and NPTEL are introducing various short-term courses and/or professional certificate courses in data analytics. Explore the sections below to find out details about data analytics courses by government colleges/platforms.
IIT data analytics courses
data analytics courses in iit Many IITs are now introducing new data analytics courses in their curriculum for the academic year 2023. The table below lists upcoming IIT data analytics certifications and programs.
Data Analytics Courses by IIM
iim data analytics courses in India offers several courses, incuding data analytics courses. Some of the best data analytics courses offered by IIMs are mentioned below.
Data Analytics Certifications for Beginners In 2023
Beginners can pick up any of the following Data Analyst courses based on the parameters like cost, duration, and ratings.
Data Analytics Certifications for Working Professionals
Professionals seeking to pursue a certificate course in Data Analytics can check out the following popular courses available across various online platforms.
Data Analytics Certifications with Good Placement Opportunities In 2023
Anyone who wants to pursue a certificate course in Data Analytics with Good Placement Opportunities can check out the following popular courses available across various online platforms.
Best data analytics courses Institutes in Bangalore In 2023
| Institute | Location | Phone No. |
|---|---|---|
|
AnalytixLabs
|
Bldg 51/2, First floor 12th Main Road, Near BDA complex Sector 6, Opp A2B (Adayar Ananda Bhavan), Bengaluru, Karnataka – 560102
|
+91- 9555219007
|
|
360DigiTMG
|
360DigiTMG, 15th Main, HAL 2nd Stage, Indiranagar, Bengaluru, Karnataka – 560008
|
+91- 80-4242-9000
|
|
Learnbay
|
55, 1st Floor, 80 Feet Road, HAL II Stage, Indiranagar, Bengaluru, Karnataka – 560008
|
+91- 80-4242-9000
|
|
Simplilearn
|
16th Floor, Prestige Shantiniketan, 100 Feet Road, HAL 2nd Stage, Indiranagar, Bengaluru, Karnataka – 560008
|
+91- 80-4242-9000
|
|
Great Learning
|
601, 6th Floor, Prestige Shantiniketan, 100 Feet Road, HAL 2nd Stage, Indiranagar, Bengaluru, Karnataka – 560008
|
+91- 80-4242-9000
|
Best data analytics courses in delhi In 2023
These are just a few of the many data analytics courses near me in Delhi including Gurgaon and Noida. The institutes vary in terms of their curriculum, cost, and admission requirements. However, all of these data analytics course institutes in Delhi offer students the opportunity to learn the skills and knowledge they need to succeed in a career in data analytics.
Best Data analytics courses in Chennai In 2023
Data analytics courses in Kolkata In 2023
Here are some data analytics courses in Kolkata with placement:
Best data analytics courses in Hyderabad In 2023
These are just a few of the many data analytics offline institutes in Hyderabad. The institutes vary in terms of their curriculum, cost, and admission requirements. However, all of these institutes offer students the opportunity to learn the skills and knowledge they need to succeed in a career in data analytics.
Best data analytics courses Institutes in Mumbai In 2023
Here are the some of the Data analytics courses institutes in Mumbai
Best data analytics courses Institutes in Pune In 2023
Best Data analytics courses In Canada In 2023
Master’s in Data Analytics in Canada is a great way to gain the skills and knowledge you need to succeed in this rapidly growing field.
Data analytics lifecycle
The life cycle of data analytics is a process that organizations use to collect, clean, analyze, and interpret data to gain insights that can be used to make better decisions. The lifecycle is typically divided into the following six phases:
- Data discovery and formation: This phase involves identifying the data that is needed, gathering it from various sources, and formatting it so that it can be analyzed.
- Data cleaning: This phase involves removing errors and inconsistencies from the data, such as duplicate records, missing values, and outliers.
- Data analysis: This phase involves using statistical techniques to find patterns and trends in the data.
- Data visualization: This phase involves presenting the data in a way that is easy to understand, such as through charts, graphs, and dashboards.
- Data interpretation: This phase involves making sense of the data and drawing conclusions.
- Data communication and presentation: This phase involves communicating the findings of the data analysis to stakeholders in a way that is clear and concise.
The data analytics lifecycle is an iterative process, meaning that it can be repeated as needed. For example, if the data analysis reveals that the data is not clean enough, the data cleaning phase may need to be repeated.
Comparison of Data Science vs Data analytics and more
Difference between data science and data analytics. These are just a few of the many skills, tasks, and salaries associated with data analytics, data science, business analysis, and big data analyst roles. Data science and business analytics are two closely related fields that use data to solve problems and make decisions. The specific skills and tasks required for each role will vary depending on the company and the industry. However, all of these roles require strong analytical and problem-solving skills, as well as the ability to communicate effectively with stakeholders.
data science and data analytics difference, the salary for these roles varies depending on the company, the industry, the level of experience, and the location. However, data analytics, data science, business analysis, and big data analyst roles are all in high demand and offer competitive salaries.
| Role | Skills | Task | Salary (INR) |
|---|---|---|---|
|
Data Analyst
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Data mining, data analysis, data visualization, statistical analysis, machine learning, programming
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Collect and clean data, analyze data, create reports and visualizations, communicate findings to stakeholders
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5,00,000 - 10,00,000
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Data Scientist
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Data mining, data analysis, data visualization, statistical analysis, machine learning, programming, artificial intelligence
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Develop and implement data-driven solutions, build and manage data pipelines, create machine learning models
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10,00,000 - 20,00,000
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Business Analyst
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Business analysis, data analysis, problem-solving, communication, collaboration, project management
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Understand business requirements, gather and analyze data, identify and recommend solutions, communicate findings to stakeholders
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5,00,000 - 10,00,000
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Big Data Analyst
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Data mining, data analysis, data visualization, statistical analysis, machine learning, programming, big data technologies
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Collect and clean big data, analyze big data, create reports and visualizations, communicate findings to stakeholders
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10,00,000 - 20,00,000
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Business analytics vs data analytics
Business analytics and data analytics for business are two closely related fields that use data to help businesses make better decisions. However, there are some key differences between the two fields.
Business analytics is a broader field that encompasses all aspects of using data to improve business performance. It includes data mining, data visualization, and business intelligence. Data analytics is a more technical field that focuses on the analysis of data. It includes data mining, machine learning, and statistical modeling.
Business analysts typically have a business background and are more focused on the business implications of data. They use data to identify problems, develop solutions, and track progress. Data analysts typically have a technical background and are more focused on the technical aspects of data analysis. They use data to extract insights, develop models, and make predictions.
data analytics vs data analysis
Difference between data analysis and data analytics is Data analytics and data analysis are often used interchangeably, but there are some key difference between data analysis and data analytics.
Data analysis is the process of collecting, cleaning, and analyzing data to extract insights. It is a broad term that can encompass a variety of techniques, such as statistical analysis, machine learning, and data mining.
Data analytics is a more specific term that refers to the use of data analysis to make decisions. It is a more strategic approach to data analysis that is focused on using data to improve business performance.
difference between data analytics and business analytics If you are simply referring to the process of analyzing data, then “data analysis” is the more appropriate term. If you are referring to the use of data analysis to make decisions, then “data analytics” is the more appropriate term.
FAQS
A data analyst reviews data to identify key insights into a business’s customers and ways the data can be used to solve problems. They also communicate this information to company leadership and other stakeholders.
The salary and progression are excellent.
Data analysis is not necessarily an IT (information technology) job but requires working with IT tools and systems. Data analysis involves using statistical and computational techniques to derive insights from data, which can be applied in various industries such as healthcare, finance, marketing, and more.
Several data professionals have defined data analytics as a stressful career. So, if you are someone planning on taking up data analytics and science as a career, it is high time that you rethink and make an informed decision.
Data analysis is neither a “hard” nor “soft” skill but is instead a process that involves a combination of both. Some of the technical skills that a data analyst must know include programming languages like data analytics using python Pdf, Python, database tools like Excel, and data visualization tools like Tableau.
- Tell me about yourself and your experience in data analytics.
- What are your strengths and weaknesses as a data analyst?
- What are your favorite data analysis tools and techniques?
- Can you walk me through a data analysis project that you have worked on?
- What are your thoughts on the future of data analytics?
Data-driven analytics is of interest to companies because it allows them to make better decisions based on data. This can lead to increased profits, improved customer service, and better decision-making overall.
If you are interested in pursuing a career in data analytics, an MS in Data Analytics from a top university in the USA can be a great way to get started.
A data science and analytics course is a course that teaches you how to collect, analyze, and interpret data. These courses typically cover topics such as statistics, machine learning, data visualization, and big data.
Data analytics is the process of collecting, cleaning, analyzing, and interpreting data to extract meaningful insights. It is a broad field that encompasses a variety of techniques and methods.
There are many free data analytics courses with certificates available online. Some of the most popular options include:
- Google Data Analytics Professional Certificate
- Udacity Data Analyst Nanodegree
- DataCamp
Healthcare data analytics is the process of collecting, cleaning, analyzing, and interpreting data from healthcare organizations. This data can be used to improve patient care, identify fraud, and manage costs.
HR data analytics can be used to improve a variety of HR processes, including:
- Recruitment: HR data analytics can be used to identify the best candidates for open positions. This can help to improve the hiring process and reduce costs.
- Performance management: HR data analytics can be used to track employee performance and identify areas where employees need improvement. This can help to improve employee productivity and morale.
- Compensation: HR data analytics can be used to determine fair compensation levels for employees. This can help to attract and retain top talent.
- Benefits: HR data analytics can be used to determine which benefits are most important to employees. This can help to improve employee satisfaction and productivity.
MCA in Data Analytics is a Master of Computer Applications degree that focuses on data analytics. This degree program typically covers topics such as data mining, machine learning, big data, and data visualization.
The National Data and Analytics Platform (NDAP) is a platform that provides access to data and analytics tools for government agencies. The NDAP can be used to improve government decision-making, increase transparency, and improve public services.
SQL is a language for querying and managing databases. It is a powerful tool that can be used to extract data from databases and analyze it. SQL is a valuable skill for data analysts, as it allows them to access and manipulate data more easily.
John W. Tukey wrote The Future of Data Analysis in 1962
Analytics Vidhya is a website and community for data science and machine learning professionals.
Data science and data analytics are closely related fields, but they are not the same. Data science is a broader field that encompasses data analytics, as well as other areas such as machine learning and artificial intelligence. Data analytics is a more specific field that focuses on the analysis of data.
Business analytics and data science are two closely related fields that use data to solve business problems.
Data sufficiency is a type of question that is asked in the TS ICET exam. These questions test the candidate’s ability to determine whether or not the given data is sufficient to answer the question.
Google Analytics offers a variety of options for filtering data. These filters can be used to exclude or include specific data from your reports.
Here are some of the most common types of filters in Google Analytics:
- Predefined filters: These filters are pre-defined by Google Analytics and can be used to exclude or include specific data from your reports. For example, you can use a predefined filter to exclude internal traffic from your reports.
- Custom filters: These filters allow you to create your own criteria for filtering data. For example, you could create a custom filter to exclude traffic from a specific country or region.
- Advanced filters: These filters allow you to create more complex criteria for filtering data. For example, you could create an advanced filter to exclude traffic from a specific country or region that also came from a specific device type.
