Glowing letters on the wall read ‘data has a better idea’

Learn Big Data: The Best Courses and Resources



Imagine you have data available at your fingertips but no idea what to do with it. With the help of technology, a large amount of data is generated every day. This massive stream of information has made it important for us to learn big data.

The rise of big data has opened more room for professionals to collect, process, and interpret data quickly and more efficiently. Data scientists and analysts, for instance, have had to revisit the way they do data analysis. 

If you want to know how to use data to your benefit, countless resources can guide you in your journey. Read on to find out how you can utilize big data and improve business operations through data-driven insights and actions.

What Is Big Data?

Big data refers to a complex set of data from numerous sources. The traditional data processing methods are no longer recommended to process them. In the first place, these traditional methods might not even be powerful enough to come up with adequate results.

Oracle further defines big data as having these three qualities:

  • Volume. Big data entails having high volumes of unstructured data to process, as seen with Twitter data and website clicks.

  • Velocity. This refers to the rate at which we receive data. Some data, such as post engagement on social media, are generated in real-time.

  • Variety. Big data is a collection of unstructured and varied types of data. A data set, for instance, may include different types such as text, audio, video, and more.

What Jobs Use Big Data?

So many disciplines use big data technologies especially those that use large amounts of data daily. Artificial intelligence, for instance, uses big data because of the massive calculations that it needs to prove theories and conduct experiments. Retail industries also use big data for predictive analytics, which helps them understand and respond to consumer needs.

Jobs related to computer and information research earn an average of $122,840 per year, according to the US Bureau of Labor Statistics. The job outlook is even better at a foreseeable 15 percent rise in the next decade. This is much faster than the average growth rate across all occupations.

Nowadays, various jobs use big data skills, such as:

  • Big Data Engineer. These professionals are responsible for managing the big data archives of the company. This means expertly yielding results out of huge amounts of data. Computing knowledge is a must for data processing and analysis.

  • Data Architect. A data architect develops the database resources of the company. Part of his/her job includes ensuring that a solid information system is in place. This is important for big corporations with lots of data coming in every day.

  • Database Manager. With the massive volume of unstructured big data coming their way, database managers develop applications to organize these data. They maintain order by establishing standards and controls and troubleshooting when necessary.

  • Business Intelligence Analyst. With the rivers of data collected daily, analysts lead the careful selection of relevant data. They are the ones who review and validate these data to ensure that a correct analysis will be drawn from them. 

  • Data Scientist. A data scientist collects and interprets data, after which s/he recommends an actionable insight to relevant stakeholders. Such insights help a company formulate plans for improvement. Programming skills help process these big data.

Steps to Learn Big Data

Presenting graphs and data findings among peers



It takes a serious commitment to study and learn big data. This does not simply involve collecting data and figuring out what to do with them. You need to have certain skills related to data science and machine learning to really excel at it.

Below are some steps that you can consider learning big data. The steps you will take will depend on whether you have already learned how to become a data analyst or not.

Step 1: Live With Data Daily

Venturing into big data analytics means living with data daily. Doing so will help you gain insights into whatever information your company needs. It means having various sources of data to examine and select from every day.

Make sure to only read analyses from reliable sources. This will help you see techniques and strategies that can help you in presenting accurate data. Remember that maintaining credibility in your work is important when utilizing big data.

Step 2: Decide Which Software to Master

Big data software programs and tools are necessary to ensure correct data processing. You are not obliged to learn how to use all of these software programs, but knowing more enhances your versatility. The software programs either come for free or with a fee.

These programs use computing scripts like Java, HTML, and more. If you want to be an expert on these tools, a background in programming is essential. Choosing to master specific software is enough of a first step to learning big data.

Step 3: Take on Personal Projects

Taking on personal projects will help you understand big data on a practical level. You learn to apply these on different topics and discussions. You also get to hone your skills in processing data and extracting analyses from them.

Personal projects may include commissioned ones from students who need research assistance. You can also opt to work on your own if you’re aiming to get an article published in a journal.

Step 4: Learn How to Extract and Communicate Insights

Big data is meaningless if it can’t be read or understood. Visual storytelling plays a huge part in communicating your findings from datasets. Not all executives in a company can keep up with the jargon of big data. 

So, make sure that your target audience understands your insights. Visual aids, such as graphs and bars, and analysis tools such as data flows can help you achieve this.

The Best Online Courses to Learn Big Data

There are lots of big data courses available online for you to choose from. These courses cover the basics of big data and all the skills required for learning it. Most of these courses also provide certificates that you can add to your credentials.

Some of these courses need full-time commitment as they’re designed like that of an actual graduate school program. It’s up to you whether you’ll go for a full-time big data course or a short-term course. Beginners are recommended to take the former while professionals looking to upskill can choose the latter.

The Ultimate Hands-On Hadoop: Tame Your Big Data!

  • Provider: Udemy
  • Level: Beginner to Intermediate
  • Duration: 14.5 hours of on-demand video

Hadoop is one of the well-known software programs related to processing and managing big data. This course focuses on teaching the intricacies of Hadoop and the platforms associated with it. You also get to analyze relational data through Hive and SQL.

MicroMasters Program in Statistics and Data Science

  • Provider: edX and MIT
  • Level: Advanced
  • Duration: 1 year, 2 months

This is a course offered by the Massachusetts Institute of Technology (MIT). It covers data science, statistics, and machine learning in a full-study course that culminates in a virtually proctored exam. One of its primary aims is to teach big data analysis and predictions through modeling.

Introduction to Data Science in Python

  • Provider: Coursera and the University of Michigan
  • Level: Intermediate
  • Duration: Approximately 31 hours to complete

Python is a well-known programming language in the field of big data. This course is meant for beginners as it teaches the basics of programming in Python. You’ll learn data manipulation and cleaning techniques, as well as other important Python functions.

Harvard Business Analytics Program

  • Provider: Harvard University
  • Level: Advanced
  • Duration: Approximately 11 weeks

This course is specifically made for those who want to be a leader in the big data analytics industry. The curriculum builds your technical and analytical skills especially in interpreting findings. You can also expect to gain better data analysis and management skills.

Data Science: Wrangling

  • Provider: edX and Harvard University
  • Level: Beginner
  • Duration: 8 weeks

Importing data into R is this course’s main agenda. It covers all topics including string processing, HTML parsing, and more. Data scientists face related problems to these every day so knowing how to address such issues prepares you for future encounters.

Why Learn Big Data?

Big data is a vital part of information systems and businesses. Nowadays, a lot of companies rely on big data to make informed, cost-efficient, and actionable business decisions. This is especially true for companies that implement the Internet of Things (IoT) in their products.

Let’s review the data points. There’s a 15 percent increase in terms of job outlook for big data analytics. Digital improvements play a key role in process automation. The need for data scientists grows day by day to make sense of massive volumes and varieties of data.

Learning big data is, therefore, crucial to successfully running businesses, organizations, and even institutions. Thanks to big data, there’s now a better way to process, analyze, and communicate information.

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