Data analysis is not a new area. Since the nineteenth century, when Henry Ford timed the speed of every component in his new assembly line to determine where it might be made more efficient, people have been evaluating data.
When academics began to utilise computers to make business choices in the 1960s, analytics became even more significant.
Data now affects every organisation, regardless of size, location, or sector. According to International Data Corporation, 80% of firms use data in numerous business tasks such as product management, customer service, and manufacturing.
That comes as no surprise. Data analysts may assist corporate executives in making better decisions by identifying trends and resolving business issues, such as why sales declined in a certain quarter.
Data analysts and data scientists are not the same things. Although data analysts and scientists deal with data, their approaches differ.
A data analyst assists company executives with decision-making by utilising data to discover answers to specified questions. On the other hand, data scientist originates their questions, performs tests, and develops new algorithms. Many data scientists start as data analysts.
If data analytics seems interesting, keep reading for the finest data analytics courses available. The online data analytics courses listed below will teach you all you need to know to become a great data analyst – for less than a fraction of the price of a traditional degree.
You shouldn't be afraid if you don't have a degree and want to be a good data analyst. As of 2022, most data analyst employment will be no degree occupations, which means you will not need a degree to be qualified.
However, taking a high-quality online data analytics course will teach you all you need to know to succeed. Several data analysts with no formal schooling have landed high-paying jobs.
Why is Big Data a great career option?
According to a Mckinsey report, by 2036, 90% of occupations will be automated, with 30% of those jobs utilising Big Data technologies. These statistics demonstrate that Big Data is in high demand. However, there are other reasons why Big Data is in great need:
- Big Data influences the outputs of Machine Learning models since the more data fed into these Machine Learning models, the more robust and accurate they become.
- The absence of Big Data results in project management failure or loss since a Big Data-based analysis reveals numerous characteristics such as trends, patterns, and other relevant patterns that the project has worked on.
- Predictive analytics is used extensively to create future forecasts and detect dangers and possibilities. Predictive analytics used Big Data approaches such as data mining, modelling, and AI/ML to assist organisations in making future predictions.
- Big Data may collect data from call logs, social media platforms, feedback forms, website logs, and product evaluations through user experience. By advertising their products or services, businesses may improve their client experience.
The availability of additional data in the cloud increases the likelihood of data theft. This creates a need for other cybersecurity specialists who can assess expanding data quantities and take the necessary precautions to avoid data theft.
With technology improvements, professional opportunities in Big Data will continue to expand, as will the skills connected with Big Data.
Big Data is used in various industries, but healthcare, finance, media, retail, energy, and utilities gain the most from it. At the moment, Big Data analytics is the best career move you can make because the need for skilled Big Data experts will increase in the next five years, resulting in more work chances.
According to Entrepreneur magazine, organisations that use Big Data in their operations have seen a profit boost of 8-10% and an average cost reduction of 10%.
There is an increased need for Big Data Analytics abilities, yet it is an irrefutable reality that there is a considerable shortage of qualified people worldwide.
Even though Big Data is one of the most in-demand positions with high-paying wages, there are many unfilled vacancies due to a scarcity of essential competence.
Courses For Becoming A Data Scientist
These are our picks for the best data analytics course:
- Data Analyst Nanodegree (Udacity)
- Data Analyst with R (DataCamp)
- Data Science Specialization (Coursera)
- Excel to MySQL: Analytic Techniques for Business Specialization (Coursera)
- Business Analytics Specialization (Coursera)
- Data Analytics Immersion (Thinkful)
- Become a Data Analyst (LinkedIn Learning)
- The Data Science Course 2022: Complete Data Science Bootcamp (Udemy)
- Data Analytics Bootcamp (Springboard)
- Big Data Analytics with Tableau (Pluralsight)
Data Analyst Nanodegree (Udacity)
The Data Analyst Nanodegree from Udacity will teach you all the information, skills, and tools you'll need to launch a career in data analytics. The curriculum offers frequent 1-on-1 mentor calls, an active student community, and one-of-a-kind career assistance services, in addition to addressing theory and practice.
Students with prior familiarity with Python (particularly NumPy and Pandas) and SQL programming are best suited for this program. However, don't be dismayed if you don't have these qualifications.
If you do not satisfy this program's criteria, a similarly organised beginner-level Nanodegree called "Programming for Data Science" is an excellent alternative. The beginner-level program covers exactly what you need: Python programming fundamentals from a data science standpoint.
The Data Scientist Nanodegree program is divided into four courses, each of which contains practical projects that you may present to potential employers:
- Data Analysis Fundamentals. Students must use Numpy and Pandas to analyse weather trends using one of Udacity's curated datasets.
- Statistics in Action. Students must apply data analytics and statistical analysis methodologies to interpret big data sheets and report the findings.
- Wrangling with data. In this course, students learn how to utilise Python for data manipulation (collecting data, evaluating its relevance, cleaning it up, and getting it for analysis).
- Python Data Visualization Students will learn how to utilise Python to put data visualisation ideas into reality.
The lesson subjects in this program are completely chosen, and the curriculum includes just the most important and practical topics for working as a data analyst. It also covers some of the most popular data analytics tools, such as R, Python, and Tableau, and challenges you to apply what you've just learned to real-world projects inspired or provided by industry firms.
We chose Udacity's Data Analyst Nanodegree as the top online data analytics course for all these reasons and more. It won't be simple, but it will teach you the principles of data analysis better than any other course.
Data Analyst with R (DataCamp)
This program includes bite-sized learning resources handpicked by leaders in the data business. Regardless of how much spare time you have to study, it will help you acquire your ideal career in data analysis.
This course is special because
- There are no requirements.
- Courses recommended by industry experts
- Interactive Exercises
- Possibility to deal with real-world datasets
The Data Analyst with R Career Track at DataCamp comprises 19 data science analytics courses curated by industry professionals to help you launch a new career in data science.
Because each race is around 4 hours long, the full track should take approximately 77 hours to complete. Students should be able to manipulate and analyse data using R after this course.
The path is simple to follow. It helps that each course is separated into smaller classes, which are further divided into "chapters." The material is delivered via videos and interactive exercises.
Students learn to utilise some of the most popular R packages, including ggplot2 and tidyverse, and SQL abilities for searching databases and connecting tables. Furthermore, students interact with real-world statistics such as Australian population figures and baby names from the United States.
The classes are presented by 15 professors, including DataCamp co-founder Jonathan Cornelissen. Starting this Career Track has no prerequisites.
If you want to change careers but don't have much time to study daily, DataCamp's Data Analyst with R is unbeatable. This Career Track, divided into bite-sized learning portions, is undoubtedly one of the greatest data analytics courses. It will teach you all you need to know to begin your career in data science.
Data Analytics Immersion (Thinkful)
This course is as near to individualised learning as you can get, with a tailored timetable, 1-on-1 mentorship, and 24/7 assistance from teachers.
This course is special because
- There are no requirements.
- Mentoring one-on-one
- You are not required to pay until you earn $40,000 annually.
Thinkful's Data Analytics Immersion is a full-time, rigorous training program. Although it is one of the expensive data analytics courses available (it costs $12,250), it claims to take you from novice to expert in four months. On the other hand, students must study for 50 to 60 hours each week.
When you enrol in the course, you will be given a personalised timetable to help you remain on track. The program is divided into seven sections: Excel Foundations, Data Storytelling, SQL Foundation, Tableau, Business Research, Python Foundations, and Capstone Phase.
Students not only complete two cultural fit interviews during the Capstone Phase, but they also develop a final project.
There are no lectures or seminars scheduled. The course material is instead text-based. As a result, those who prefer video teaching may find the application unsuitable.
Each student is assigned a personal mentor who may answer questions regarding the course in general. In addition, a career coach and an academic achievement manager are also provided. The latter can help you in difficult situations, such as when you get behind and need your deadlines pushed back.
This course does not have any requirements. However, the admissions process is rigorous and involves a "fit interview" to see whether your schedule and study style are compatible with the course.
If you are approved, you have the option of paying nothing until you are working as a data analyst and earning at least $40,000 per year.
Thinkful's Data Analytics Immersion program can help you get to your ideal job if you're ready to put in the effort.
Data Science Specialization (Coursera)
This John Hopkins University course teaches R programming, data processing, and regression analysis. You require Python and regression knowledge to do this course.
Data Science Specialization is a ten-course curriculum given by Coursera in collaboration with the famous John Hopkins University that helps you comprehend the whole data science pipeline at a fundamental level.
Although anybody may enrol in this course, students should have some expertise with Python and some knowledge of regression.
The curriculum is delivered through videos and additional texts. Auto-graded practice quizzes and peer-graded projects are used to assess student understanding. The curriculum concludes with a hands-on project in which students construct a suitable data product.
According to Coursera, most students can expect to complete the program in around 11 months if they study 7 hours weekly. However, due to the monthly cost charged by Coursera, there is a strong incentive to complete the Specialization as soon as feasible.
Students can also choose to read course content for free, but they will miss out on the capstone project and course certification as a result.
There is a 7-day free trial if you are unsure if this course is correct. Coursera also provides financial assistance to students who cannot afford the procedure.
Coursera's Data Science Specialization is one of the greatest data analytics courses available. According to Coursera, 43% of students who took this course began a new career.
In addition, 19% obtained a wage raise or promotion. However, to get the most out of this course, students should be comfortable with Python programming and regression.
Business Analytics Specialization (Coursera)
This five-course series aims to teach how to utilise big data to make data-driven business choices in finance, human resources, marketing, and operations.
This course is special because
- It has a final project
- There are no requirements.
- The content is free to audit.
The Business Analytics Specialization, developed by the University of Pennsylvania's Wharton School and available on Coursera, is separated into four discipline-specific courses (customer, operations, people, and accounting analytics). The fifth and final course is devoted to a capstone project.
Videos and texts are used to teach the Specialization. Quizzes are used to assess your knowledge. You may also take part in online forums. Students execute a Capstone Project built in collaboration with Yahoo at the end of the semester.
The whole Specialization takes roughly 40 hours to complete, which means that students may complete the program in as little as six months if they study three hours each week.
This course does not require any prior understanding of business analytics. Students must, however, have access to a full-featured version of Microsoft Excel and a basic comprehension of its functionalities.
If you wish to be able to design innovative business strategies utilising data, this Specialization from the University of Pennsylvania's Wharton School is for you.
Excel to MySQL: Analytic Techniques for Business Specialization (Coursera)
This Duke University course will teach you how to address business challenges using data through various hands-on projects.
This course is special because
- Beginners are welcome.
- There are several hands-on tasks available.
- Potential contribution from Airbnb data scientists
But one of the downsides is that it is very long and time-consuming.
The Excel to MySQL: Analytic Techniques for Business Specialization course, offered by Duke University and accessible on Coursera, is a beginner-friendly course that teaches students how to extract as much information as possible from the current data.
There are five courses in the curriculum. You begin by studying best practices for leveraging data analytics to make a firm more competitive before progressing to Excel, Tableau, and MySQL classes.
Every course concludes with a project. For example, at the end of the third course, you must provide a five-minute presentation on how a company may boost the number of tests that customers complete.
The capstone project focuses on the last course, which Airbnb sponsors. Students must propose how a firm might increase its revenues as part of this assignment. Ten students will receive feedback on their projects from Airbnb data scientists every year.
Although no prior Excel expertise is required, students must have access to Microsoft Excel 2007 (or a more recent version). Students who devote five hours each week to the program may expect to finish it in around seven months.
Big Data Analytics with Tableau (Pluralsight)
Pluralsight's highly rated short course can help you become a Tableau expert in under four hours.
This course is special because
- Content in bite-sized portions
- focuses on Tableau software
- Only 4 hours long
But prior experience is essential.
Big Data Analytics with Tableau from Pluralsight will improve your understanding of large data and show you how to access big data systems using Tableau Software. The course covers big data analytics and how to use Tableau to access and interpret huge data.
Ben Sullins, who has 15 years of industry expertise and has provided consulting services to organisations such as Facebook, LinkedIn, and Cisco, teaches the course.
Sullins imparts his expertise to pupils in the form of bite-sized morsels of material. As a result, students may tailor their education to their own needs. You may complete the course in a single day or take your time and finish it over a week or two.
This course is not intended for complete novices. However, you should have some familiarity with data analytics. If you're a total newbie, try taking Sullins' Data Analysis Fundamentals with Tableau course.
Tableau is a prominent data visualisation software. Pluralsight's Big Data Analytics with Tableau course will teach you how to use this program technically.
It makes little difference if you have prior statistics, computer science, or business knowledge. Everyone will learn something new from this training.
The Data Science Course 2020: Complete Data Science Bootcamp (Udemy)
A thorough, beginner-friendly course that covers a lot of ground while requiring no prior knowledge of any programming language or statistics.
This course is special because
- There is no prior experience necessary.
- Discounts galore
- Money-back guarantee for 30 days
Complete Data Science Bootcamp, available on Udemy, is a thorough data science course with 471 lessons.
In addition, there are about 30 hours of on-demand video, 90 articles, and 154 downloadable materials in the lectures. While the course is not new, initially covered in 2020, it has been revised for 2022 with new learning resources.
Students may expect to master in-demand data science skills such as Python and associated libraries (such as Pandas, NumPy, Seaborn, and matplotlib), machine learning, statistics, and Tableau course.
Although the course may appear daunting initially, it is well-structured and needs no prior knowledge. To get started, all you need is Microsoft Excel.
The course will cost you several hundred dollars. However, Udemy offers huge discounts so that you may acquire the system for less than $20. This course is a deal, especially given you have lifelong access to it and any future upgrades.
Overall, Udemy Data Science Course 2020: Complete Data Science Bootcamp covers many subjects without overly technical or practical. Overall, it's an excellent general beginning course in data science.
Become a Data Analyst (LinkedIn Learning)
In just 24 hours, you'll have a deeper knowledge of data science, thanks to this online course.
This course is special because
- It is free to use.
- Beginner-friendly
- There are no requirements.
- Quizzes are included.
Join LinkedIn and become a Data Analyst. Learning is a "learning path" in data science for novices. Learning pathways are playlists related to `video courses on a certain topic or profession.
Learning Data Analytics, Data Fluency: Exploring and Describing Data, Excel Statistics Essential Training: 1, Learning Excel: Data Analysis, Learning Data Visualization, Power BI Essential Training, and Tableau Essential Training are the seven courses in this program (2020.1). The length of each course varies.
Most courses, however, are between two and four hours long so that you can complete the full trail in around 24 hours.
There are no prerequisites for embarking on this educational journey. You don't even need to understand what data analysis is. The course starts with a definition of data analysis and then teaches you how to locate, evaluate, clean, and display data.
Six separate professors, all of whom are industry specialists, teach the program through video. In addition, some courses have quizzes, and all systems have a Q&A area where you may ask the lecturer questions about the course. The only disadvantage? There are no hands-on activities.
Become a Data Analyst by LinkedIn Learning is another excellent data analytics course for learning fundamental data analysis skills. What's better? It is entirely free. If you're unsure if data analysis is what you want to do, this course will help you decide.
Data Analytics Bootcamp (Springboard)
Springboard will refund you if you do not find work as a data analyst or business analyst within six months of graduating from Data Analytics Bootcamp.
This course is special because
- Job security
- Mentoring on a one-on-one basis
- two major projects
- Unrestricted career counselling
Data Analytics Bootcamp, created by Springboard in collaboration with Microsoft, is a six-month career-focused curriculum with a job guarantee.
The boot camp covers basic business statistics ideas, sophisticated analytical methodologies, and analytics and visualisation technologies such as Excel, Python, SQL, Tableau, and Microsoft Power BI.
Students complete several small projects and two Capstone Projects from Harvard Business School and Khan Academy throughout the course.
The entire course takes around 320 hours to finish, or six months. Most students devote 15 to 20 hours each week to the system. In addition, each student receives unlimited mentor calls and 50+ hours of career coaching.
However, not everyone will be admitted into this program. Students must be proficient in English and have at least two years of professional experience with Microsoft Office or G-Suite.
Students should also be able to think critically and solve problems. If you don't fulfil the qualifications, Springboard offers a free Intro to Business Analytics course that will get you up to speed.
You don't have to worry about wasting hours studying just to stay in your current employment because you can't find work in the field because Springboard guarantees a job.
Since 2016, only one employment guarantee has been refunded out of 1,730+ students. Furthermore, most Springboard students have experienced a pay boost of more than $25,000.
Careers For Big Data
Big Data experts have several job alternatives accessible; they only need to explore their potential and interests.
- Data Scientists,
- Big Data Engineers,
- Big Data Analysts,
- Data Visualization Developers,
- Machine Learning Engineers,
- Business Intelligence Engineers,
- Business Analytics Specialists,
- Machine Learning Scientists
The top ten in-demand Big Data skills for a prosperous profession are:
- Data Visualization in Analytics
- Understanding of Business Domains and Big Data Tools
- Structured Query Language is a problem-solving programming language (SQL)
- Data Exploration
- Technical abilities
- Understanding of public and hybrid clouds
- Working knowledge
Professionals must attend a Big Data course, whether classroom-based or online, to obtain the Big above Data abilities.
Professionals with Big Data analytics abilities and the capacity to interpret data, have great business acumen, and provide insights are in high demand.
This is why IT workers with strong Big Data Analytics skills are in great demand as firms seek to harness the potential of Big Data. A professional with these strong skills can master Big Data and become an asset to an organisation, benefiting both the business and their career.
