“Data Analytics’ is one of the most heard and talked about terminologies of the present tech world. For all those people who like playing with data but still have queries regarding the term, its application, and scopes, then this may prove the right read for you. In today’s world of ever-increasing competition, there is always a need to upskill oneself, and ‘data analytics’ is one such skill that is in high demand nowadays. There are a number of Data Analytics Courses at Coursera, that are available online for anyone who is interested in upskilling themselves.

List of best data analytics courses at Coursera

What is Data Analytics?

Today all companies are going digital, by virtue of which they tend to generate a vast volume of data, including log files, transactional data, web servers, and customer-related data.

The social media websites of companies also generate tons of data nowadays. Companies store and evaluate this data to derive value from it which can help them to make meaningful and thoughtfully crafted decisions.

It is here, where the need for data analytics comes into the picture. In simplest words, Data Analytics can be defined as a process of analyzing a set of raw data to make impactful and meaningful conclusions from it, by virtue of which a business can make efficient, strategically guided, and profitable decisions for the future.

In most simple language, a data analyst’s job is to explore and analyze a given set of large data and find out hidden patterns and trends, discover correlations between them, and then derive valuable insights as to how the business can be taken to the next level. A business analyst’s job in simple words is to improve the speed and efficiency of any business.

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Importance of Data Analytics

Data analytics is one of the most important bases for a company to accelerate its growth. It’s due to data analysis only that a company evaluates its performance by converting its raw data into meaningful findings that help it strategically craft solutions or ventures for future growth.

The raw data available in companies about their performances can only be evaluated properly by using tools and processes that are part of data analytics. Data analysis helps companies to understand their customers better, evaluate their ad campaigns, personalize content, create content-driven strategies, and develop their products as per market needs.

In short, data analytics helps companies to optimize their performances, by analyzing each and every aspect very carefully and providing solutions for better future business models.

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What Are the Different Types of Data Analytics?

Data analytics is basically of four types:

  1. Descriptive analytics: Here the overall happenings/activities related to a particular business, in a given frame of time, are carefully studied and evaluated.
  2. Diagnostic analytics: This type of data analytics is basically concerned with the reasoning as to why something followed a particular pattern only. The process requires a lot more different types of data inputs and their manipulation.
  3. Predictive analytics: Here we analyze, after studying a given set of data, what is going to happen in the near term. It is basically a prediction of the events of the future by evaluating the past course of action.
  4. Prescriptive analytics: Here we suggest what needs to be done in order to achieve the desired output or target. What needs to be amended or added to the existing system of business to fulfill the anticipated result?

 

 

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Data Analytics Tools

There are a number of tools involved in the process of data analytics.

1. Python:

Python is an object-oriented open-source programming language. It supports a range of libraries for data manipulation, data visualization, and data modeling.

2. R:

An open-source programming language, R is majorly used for numerical and statistical analysis. It provides a range of libraries for data analysis and visualization.

3. Tableau:

It is a simplified data visualization and analytics tool. This helps you create a variety of visualizations to present the data interactively, build reports, and dashboards to showcase insights and trends.

4. Power BI:

Power BI is a business intelligence tool that has functions on a ‘drag and drop’ system. Power BI is supported with features that help one ask questions about the given set of data and get immediate perceptions on the same.

5. QlikView:

QlikView offers interactive analytics with in-memory storage technology to analyze vast volumes of data and use data discoveries to support decision-making.

6. Apache Spark:

It is an open-source data analytics engine in which the data is processed in real-time. It carries analytics in the most sophisticated way using SQL queries and machine learning algorithms.

7. SAS:

Being a  statistical analysis software, SAS helps one perform analytics, visualize data, write SQL queries, perform statistical analysis, and build machine learning models to make future predictions.

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Data Analytics Application

Data analytics is applied in almost every sector of the business world. A few of its applications are mentioned below:

1. Retail:

In the retail segment, Data analytics proves helpful by making the retailer understand the buying habits and customers’ needs that help them to predict upcoming trends and recommend new products. This helps them boost their business efficiently and smartly.

2. Healthcare:

In the field of Healthcare, Data analytics helps to evaluate patient data to provide diagnoses and treatment options for the ailment. Data analytics has been helpful in discovering many new drug development methods as well.

3. Manufacturing:

In this sector, Data analytics helps analyze the old patterns of profit and loss and the reasons behind them. Hence it helps the manufacturing market discover new cost-saving opportunities.

 

4. Banking sector:

Data analytics proved to be a boon to the banking and financial sector as it helps them to find out probable loan defaulters and customer churn-out rates.

5. Logistics:

Data analytics is used by various logistics companies to develop new business models and optimize routes. This, in turn,  ensures that the delivery reaches on time in a cost-efficient manner.

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About Coursera

  • Coursera is an online education provider that offers all the courses via online mode only.
  • Popularly known as MOOCs or Massive Open Online Courses, at present, Coursera boasts of offering more than 5400 online courses created by partner institutions/universities, from all across the globe.
  • Coursera helps you get job-ready in less than a year’s time, for many in-demand career fields by offering professional Certificates on successful completion of courses.
  • Coursera provides a platform for participants to earn career credentials; they also get to apply their knowledge to hands-on projects that help them showcase their skills to potential employers, and many times they get access to job search resources.
  • The certificates from Coursera hold a good value in the market. In spite of not being equivalent to traditional degrees or certifications that the universities offer, the certificates from Coursera still prove to be valuable add-ons for your resume and for professional development or enhancing job opportunities.
  • The best feature of Coursera courses is that they provide a series of pre-recorded video lectures that can be watched as per any convenient and comfortable schedule by the participant. They also offer a wide variety of channels such as student discussion forums, homework/assignments, and online quizzes or exams, where students can test their abilities stand amongst their counterparts, and get prepared for greater challenges and opportunities.
  • In general, Coursera courses are free to audit (i.e. watch videos) but if one wants to earn a Course Certificate, he/she will need to pay. There is an option to pay for a certificate of completion that varies from course to course.

 

  • For the participants who cannot afford the cost of the certificate, there is a provision for financial help from Coursera.
  • Coursera is accessible on any web browser.
  • Registration is mandatory to get access to the full course (lectures, videos, and supplemental materials).
  • There is an option to download lecture videos and other course materials for viewing offline.
  • The majority of courses are offered in English. There are some other languages also in which certain courses are being offered including Chinese, French, Russian, Spanish, Portuguese, Turkish, Ukrainian, German, Arabic, Italian, Japanese, Hebrew, and Italian.
  • Any kind of Technical support is available via the learner help center or via peer-led help forums. Coursera does not provide any dedicated help desk or phone number for technical issues.
  • The best part is there are a number of data analytics courses at Coursera, the details of which have been shared below.

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 Data Analytics Courses at Coursera

There are 8 Data analytics courses at Coursera, that will earn you a Google Data Analytics Professional certificate.

Best features of Data analytics courses at Coursera:

  • The participants gain skills and certificates from in-demand courses and get prepared for entry-level jobs.
  • The participants get the opportunity to learn from Google employees and get to interact with them and get to know their inspirational journey.
  • The certification can be completed in less than 6 months, by dedicating as little as 10 hours a week.
  • After successful completion of the course, the participants become job-ready for the role of a junior or associate data analyst, database administrator, and many more.
  • Upon completion of the certificate, you can directly apply for jobs with all good companies across the globe.
  • These programs include instruction of 180+ hours and hundreds of practice-based assessments, which will help you synthesize real-world data analytics scenarios that prove beneficial in critical situations in actual work scenarios.
  • The content for Data Analytics Courses at Coursera is developed by Google employees with decades of experience in data analytics and hence it is very exclusive and highly interactive.
  • During the course time, participants are exposed to a wide variety of tutorials, videos, assessments, and hands-on labs that are required for an entry-level job as a data analyst.

 

The Courses With Their Highlighting Features and Takeaways Are Mentioned Below:

 

1. Foundations: Data, Data, Everywhere

About the course:

  • This is one of the Data analytics courses at Coursera and the first course in the series of Google Data Analytics Certificate courses.
  • On successful completion of this certificate program, the participant will become eligible for data analyst jobs at an introductory level.
  • To participate in this program, no prior experience or any kind of expertise is required.
  • Once the course is completed, the participant will gain an understanding of how junior or associate-level data analysts function in their day-to-day jobs.
  • The participant will also have complete knowledge of the key analytical skills and tools that help them to upskill themselves and add value to their professional CVs.
  • The participants will get familiar with a range of terms and concepts, such as data life cycle and data analysis process, that are crucial for a junior data analyst role.
  • Upon completion, the participant will have exposure to all the jobs available in the market and they can apply wherever they find it suitable.

Skills you will gain:

  • Spreadsheet
  • Data cleansing
  • Data analysis
  • Data visualisation(dataviz)
  • SQL

 

2. Ask Questions to Make Data-driven Decisions

About the course:

  • This is another course in the series of Data analytics courses at Coursera and the second of the Google Data Analytics Certificate courses.
  • On successful completion of this certificate program, the participant will become eligible for data analyst jobs at an introductory level.
  • To participate in this program, no prior experience or any kind of expertise is required.
  • During the course timeline, the participants will be exposed to effective questioning techniques that empower them to make data-driven decisions and also train them to present their findings in the most appropriate and professional manner.
  • The participants get to explore a variety of real-world business scenarios where they can use their understanding of powerful decision-making, realize the importance of spreadsheets as an important tool for data analysts, examine the power of structured thinking and how all this, as a process, helps an analyst towards the proper evaluation of the problem and the needed solution for the same.
  • The participants are also taught the strategies to manage the expectations of stakeholders and also establish clear communication with their data analytics team,  to achieve the objectives they are intended to.

Skills you will gain:

  • Spreadsheet
  • Questioning
  • Decision-making
  • Problem-solving
  • Data-Analysis

 

3. Prepare Data for Exploration

About the course

  • This is another course in the series of Data analytics courses at Coursera and the third course of Google Data Analytics Certificate courses.
  • On successful completion of this certificate program, the participant will become eligible for data analyst jobs at an introductory level.
  • To participate in this program, no prior experience or any kind of expertise is required.
  • By the end of the course, the participant gets a sound knowledge of the kind of data necessary or needed for analysis, i.e. understanding of what to keep and what to discard.
  • The participants get an understanding of the value of structured and unstructured data, data types, and data formats.
  • The participants learn to use spreadsheets and SQL with databases and data sets for the process of analysis.
  • The participants gain knowledge of open data and the relationship between and importance of data ethics and data privacy.
  • The participants learn to access databases and the process of extraction, filtration, and sorting the data they contain. They become well-versed in organizing data and keeping it secure.

Skills you will gain:

  •    Spreadsheet
  • Metadata
  • Data collection
  • Data ethics
  • SQL

 

4. Process Data From Dirty to Clean

About the course

  • On successful completion of this certificate program, the participant will become eligible for data analyst jobs at an introductory level.
  • To participate in this program, no prior experience or any kind of expertise is required.
  • By the end of this course, the participant will have good knowledge and understanding of checking data for integrity, cleaning techniques using spreadsheets, developing basic SQL queries for use on databases, and application of basic SQL functions for cleaning and transforming data.
  • The participants gain a thorough understanding of how to verify the results of cleaning data. By now they are well aware of the importance of data-cleaning reports.

Skills you will gain:

  • Spreadsheet
  • Data cleansing
  • SQL
  • Data Integrity

 

5. Analyse Data to Answer Questions

About the course

  • This is another course in the series of data analytics courses at Coursera and the fifth course of Google Data Analytics Certificate courses.
  • To participate in this program, no prior experience or any kind of expertise is required.
  • The key takeaways of the course are that the participants learn organizational data for the process of analysis.
  • The participants learned the importance of formatting and adjusting data and the process involved in doing so.
  • The participants also learn the aggregation of data in spreadsheets and by using SQL. They become aware of the formulas and functions that can be used in spreadsheets for data calculations and how to complete calculations using SQL queries.

Skills you will gain:

  • Spreadsheet
  • Data analysis
  • SQL
  • Data calculation
  • Data aggregation

 

6. Share Data Through the Art of Visualization

About the course

  • This is another in the series of  Data analytics courses at Coursera and the sixth of Google Data Analytics Certificate courses.
  • On successful completion of this certificate program, the participant will become eligible for data analyst jobs at an introductory level.
  • To participate in this program, no prior experience or any kind of expertise is required.
  • By the end of this course, the participants learned the importance of data visualization and gained expertise in preparing a worthy narrative from all the data stories extracted from the database provided.
  • The participants learn to use Tableau to create dashboards and dashboard filters and use Tableau to create effective visualizations.
  • They learn the importance of good presentations and explore the principles and practices involved with effective presentations. They also learn how to apply best practices to a Q&A with your audience.

Skills you will gain:

  • Data analysis
  • Tableau Software
  • Data visualisation(Dataviz)
  • Presentation

 

7. Data Analysis With R Programming

About the course

  • This is another in the series of Data analytics courses at Coursera and the seventh of Google Data Analytics Certificate courses.
  • On successful completion of this certificate program, the participant will become eligible for data analyst jobs at an introductory level.
  • To participate in this program, no prior experience or any kind of expertise is required.
  • By the end of this course, the participants are aware of the benefits of using the R programming language.
  • They become well equipped in using RStudio to apply R to their analysis as they have already explored the fundamental concepts associated with programming in R.
  • They get to explore the contents and components of R packages including the Tidyverse package.
  • The participants gain an understanding of data frames and their use in R.

Skills you will gain:

  • R programming
  • Data analysis
  • Data visualisation (dataviz)
  • R Markdown
  • R Studio

 

8. Google Data Analytics Capstone: Complete a Case Study

About the course

  • This is another in the series of Data analytics courses at Coursera and eighth of Google Data Analytics Certificate courses.
  • This course offers the opportunity to complete an optional case study that helps the participants become ready for the data analytics job hunt as a case study is one of the parameters used by employers to assess analytical skills.
  • On successful completion of this certificate program, the participant will become eligible for data analyst jobs at an introductory level.
  • To participate in this program, no prior experience or any kind of expertise is required.
  • By the end of this course, the participant will have a clear understanding of the importance of good case studies and portfolios in becoming job-ready and in getting the desired jobs in the market.

 Skills you gain

  • Job Portfolio
  • Data cleansing
  • Data Analysis
  • Data Visualization (Dataviz)
  • Case study

 

FAQs

Below are the FAQs about Data Analytics Courses At Coursera.

Difference between data analytics and data science?

In simple language, a data analyst’s job is to explore and evaluate existing data and work on the findings of that data whereas a data scientist’s job is to explore new ways and techniques to capture and analyze data that could be used by a data analyst. One who is interested in starting a career in analytics can choose data analytics over somebody who is keener on creating advanced machine learning models.

Is a certificate from Coursera valid in India?

Certificate from Coursera holds good value across the globe including India as these courses are provided by top-level universities and companies. There are a number of data analytics courses at Coursera that open good job opportunities in India and across the globe.

Is data analysis a good career option?

Yes definitely as in today’s world, the rate of internet usage is increasing day by day and therefore the scope of collecting databases is increasing. The future planning of any business is now dependent on the analysis of the data hence data analytics is a blooming career option for those who are interested in the exploration and evaluation of data.

Conclusion

As already mentioned in this article, data analytics is one of the most in-demand career options across the globe today. Anyone who has a basic education and knowledge of mathematics, statistics, or computer science and who loves to play with data, can make a good career in this field. There are a number of online and offline courses available for the same and Data analytics courses at Coursera are among one of the best and most sought-after certificate courses.

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