How to Learn Big Data and Utilize Big Data Analytics
Every prediction, suggestion, and analytical insight in today’s world is possible because of big data. Can you imagine life without Google Maps, personalized news feeds, shopping suggestions, or disease tracing? If you’ve ever wondered how to learn big data or where to find the best big data analytics courses, this article brings you the answers.
If you want to become a web developer, a software engineer, a data scientist, or a UX designer, or are just looking to start any career in tech, you will need to understand big data. Even business, arts, and agriculture have a foot in this world.
For the key to a successful career, don’t waste any more time. Use this guide to put yourself on the brink of learning big data.
What Is Big Data?
Big data refers to the process of collecting data, compiling large numbers of data sets, and analyzing all the data to provide solutions to business problems. The big in big data gets at the massive scale of the enterprise. You need powerful software to break down such large quantities of structured, semi-structured, and unstructured data.
Data storage, data mining, data management, data modeling, and data analysis are all part of big data. Where big data differs from traditional database management, however, is in the scale and complexity of its analytical insights and predictions. More precisely, there are four distinctive features of big data, which can be described as follows.
- Volume. The large volume of incoming data is what separates big data from traditional data.
- Variety. In big data, the servers receive many different types of data. Facebook, for example, collects UX/UI data, personal information data, preferences and opinions data, and more. Facebook pools all of this data into its own data frameworks, which it then uses to provide you with the best suggestions.
- Velocity. Just because it’s big doesn’t mean it has to be cumbersome to conduct real-time analytics. Big data uses strong data mining software to capture and account for every piece of data integrated into the system.
- Veracity. This refers to the accuracy of big data predictions. Big data employs artificial intelligence (AI) to improve the quality of big data analytics over time.
What Is Big Data Used For?
Without big data, we wouldn’t be able to make progress in medicine, computer science, or business. While the uses of big data are many, we’ll touch on three below.
Business and Finance
Businesses use big data marketing analytics to find the best possible solutions for their problems. Due to in-depth data on user experience and user interaction, for example, businesses are able to create more convenient and user-friendly web pages.
In the financial sector, the stock exchange runs on big data. Financial analysts use big data to determine a company’s worth and project the value of its stock. Stock traders rely on artificial intelligence analysis to make predictions about market behavior.
Big data is also one of the main contributors to modern-day medical research. Medical scientists use big data to generate hypotheses, make medicines, and develop treatment plans. A fantastic example of this is the COVID-19 vaccine. Oxford and Pfizer were able to release vaccines to fight the novel coronavirus so quickly because of data analytics.
Speaking of the pandemic, big data helps with the daunting task of tracing the virus. Thanks to the volume and variety of our data, we can track Coronavirus cases more effectively and give public officials better information to make their decisions.
Flight Blackbox Data
Even airlines use big data. While a plane is in the air, the data systems in place send all the flight information to the black box. This helps us recover data in the event of a crash.
Learn Big Data: Step-by-Step
You can pursue a successful big data career in data engineering, database management, data science, data architecture, and countless more fields. To fully understand this subject, you must have good analytical skills as well as an understanding of AI and algorithms.
This might seem like a lot, but you can get pretty far just by taking the right online courses and keeping up with the latest computer science news. Though everyone’s experience is slightly different, you can follow this step-by-step beginner’s guide to start learning big data.
1. Learn the Basics
You should start by learning the background skills. After mastering some of the easiest programming languages, you can tackle object-oriented programming languages such as Java, Hadoop, and DynamoDB. You can even learn to code for free online. There are plenty of resources online that will help you learn the basic requirements of big data.
2. Take Beginner Big Data Courses
Once you have a strong foundation of technical skills, it’s time to learn the ins and outs of big data. Take online courses that teach the key concepts and applications. You should be able to understand the difference between linear and non-linear data structures, implement the correct big data analytics tools, and solve big data problems.
3. Practice Big Data
Next, you should practice everything you learned about implementation, analysis, and storage. Install the necessary software on your computer, and start building practical skills.
4. Take Advanced Big Data Courses
Now it’s time to enroll in advanced courses. If you want to pursue analytics, then take courses that teach you big data analysis. Similarly, if you enter a design track, then take courses that will teach you how to design optimal big data frameworks.
5. Join Big Data Online Groups
Now you’re ready to network with like-minded people in big data online communities. Make connections and contact mentors in those communities to get insider tips and tricks. Some of the best places to link up with other data scientists are LinkedIn, Slack, Kaggle, and Meetup.
The Best Big Data Courses
Now that you know what big data is all about, let’s take a look at some big data analytics courses that you can enroll in. There are plenty to choose from, but you can start with the seven listed below.
Foundations for Data Analytics
As the name suggests, this curriculum will help you build a solid foundation in data analytics. Offered by the University of Washington’s Milgard Center for Business Analytics, it is a fully live introduction for anyone interested in data science and data management.
But this isn’t some rigid training program. On the contrary, you can specialize, get certified, or simply separate out the courses you want to take. At a price of $119 per course, this is a deal you don’t want to miss out on.
Big Data Analytics Courses and Certification Training
Simplilearn is one of the best learning platforms out there. Its many options for learning big data analytics include courses on AI, Hadoop, R, Tableau, and countless more. These courses are designed to take you step-by-step through all the applicable subtopics, and you can sign up for whichever courses suit your interests most.
Big Data Specialization
In partnership with UC San Diego, Coursera is offering six in-depth courses on topics related to big data. The best part about Coursera is its free features. In addition to big data applications for business optimization, you will learn data management, machine learning concepts, Cloudera, MongoDB, Apache Hadoop, and Splunk.
Big Data Fundamentals
This edX course focuses on how big data is bringing about change in the business world. Its ten modules will teach you the basics of big data and its various components, including design algorithms and PageRank. While the course content is free, you can pay $199 for a certificate of completion.
The Ultimate Hands-on Hadoop: Tame Your Big Data
One of the best ways to learn practical technical skills is to take hands-on courses. This Udemy course teaches you about big data management by way of a tour through the Apache Hadoop software library. Its 14.5 hours of video lessons explore Cassandra, HBase, MongoDB, MySQL, Hive, and more. You will earn a certificate upon completion.
Big Data and Education
Offered by the University of Pennsylvania via edX, this advanced course is for anyone interested in applying data mining methods in the education sector. You will learn how to use programming languages such as Python and RapidMiner for data analysis. The course is free, but you have to pay $169 if you want the certificate.
Spark and Python for Big Data with PySpark
For 10.5 hours of on-demand video, beginners get an introduction to using programming languages for big data purposes. Specifically, you will learn how to analyze big data using a combination of Python and Spark.
You will also learn to use the AWS Elastic Service, data frame syntax, MLlib, and the AWS EC2 cloud platform. Overall, we think this course is a comprehensive foray into programming with big data.
Is Learning Big Data Right for You?
Big data is omnipresent and is used in a multitude of jobs. By learning big data, you can secure a spot for yourself in finance, social media, government, medicine, or education. The demand for big data experts continues to rise, and in fact, many predict a shortage of big data professionals in the future.
So yes, learning big data is right for you. Acquire this professional skill today and significantly improve your chances of getting your dream job tomorrow.