Learn big data with online courses

Why learn big data?

Analyzing big data allows decision makers to uncover patterns, correlations and insights that can drive future strategy. Big data has become an important part of how businesses operate in nearly every vertical. With the rise of big data comes the need for data professionals, making big data analytics a valuable skill. It’s possible to take big data courses online, making it easier for individuals to manage their education alongside other responsibilities and life events. There are a variety of data analytics programs, courses, and certifications available to help improve a learner’s knowledge about the topic.

Online courses in big data

Through paid and free online courses, individuals can learn the foundations of data science, as well as how big data is stored, processed, and analyzed. Additionally, those pursuing a career in this field can learn how to use key tools and systems for working with big data, such as Azure, Hadoop, and Spark. These skills can help aspiring professionals understand how to design and implement big data analytics solutions. 

Learning about big data may take weeks to months depending on a person’s previous knowledge, educational background and experience as well as the time they can commit to the task and the length of the course(s) taken. Upon completion of big data engineering courses and online big data classes , students may receive a big data certificate as proof of their competence on the subject matter. 

What are examples of big data?

Big data can be used in a variety of contexts across several industries. Examples of how different industries use big data analytics include: 

• Commerce — Customer loyalty programs allow people to earn coupons, discounts and special offers. In addition to encouraging shoppers to return, these programs provide a lot of data that can be used to optimize which offers are sent to customers based on demographics, trends and their purchase history. 

• GPS technology — Navigation apps such as Google Maps require constant updates to maintain a positive user experience. Changes in road construction, information about businesses and imagery for the street view function are just a few examples. Google utilizes data from multiple sources, including business submissions, satellite imagery and user location information to ensure maps are accurate and find new ways to improve navigation, like providing traffic information for potential routes. 

• Healthcare — Data scientists working in healthcare are finding new ways to harness the power of big data to improve patient outcomes. There are many ways data can be leveraged to predict what line of treatment may be best for someone with certain health factors, monitor quality of care in institutions and detect the spread of diseases more effectively.

Explore big data jobs 

A career in big data may be a good fit for people interested in data processing, analysis, and computer programming. The Internet of Things (IoT) is producing massive quantities of data, making it beneficial to companies to gain insights from this data to remain competitive.^{Footnote 2}

There are a variety of computer and information technology occupations that involve big data, including developer, engineer, and database architect roles, where employees are responsible for building scalable, real-time big data analytics systems. Programming languages and tools that big data professionals may need to know include Spark, Hadoop, Sqoop, HDFS, MapReduce, Scala, Apache Spark, Apache Hadoop, Java, C++, SQL, Python and others.^{Footnote 3}

Online programs are a great way to learn more about these languages and tools, but depending on the role and company you have in mind, you may require a bachelor’s degree or master’s degree.^{Footnote 4}

How to become a big data engineer

A big data engineer is responsible for working with data scientists to outline business objectives and transform them into data-processing workflows. Big data engineer jobs can be found across industries.

An analytics boot camp may be helpful for those looking to break into this profession. To learn the ins and outs of this field, aspiring professionals may need to consider earning a bachelor’s degree in computer science or data science or a master’s degree in data science. Individuals can also learn the foundations of big data and sharpen existing skills through big data courses online. Additionally, it can be helpful to understand big data platforms such as Hive, Pig, Spark SQL, Hadoop, HBase, and others. Learners may also benefit from honing their analytical skills, logical thinking, ability to solve problems, and foundational knowledge of mathematics.^{Footnote 5}