Why You Should Consider Becoming a Data Analyst this Year—And How to Start

Humanity has been using visuals to understand data for centuries, from 17th-century maps to the invention of the pie chart in the early 1800s. Charles Minard's map of Napoleon's Russian campaign in 1812 depicts the size of Napoleon's army, the path of its retreat from Moscow, and ties that information to temperature and time scales for a more intricate understanding of the event. Even in 1812, data — and the clear presentation of it — was important.

In today's technological world, data has gotten bigger and more useful, thereby making it even more imperative to create accessible visuals. Data analytics is an essential component of business, guiding organizational decisions. Some business decisions may be made on a hunch, but nearly all successful decisions are based on data. Businesses use data in market research, product research, positioning, customer reviews, sentiment analysis, and much more, making competent data analysts some of the most important people in business today.

Beyond the analysis, visualization is equally important. The human brain needs help to identify patterns and trends — spreadsheets don't quite cut it. Even if a data analyst can pull insights from a spreadsheet, communicating those insights to others is significantly more difficult without clear visualizations. Rattling off numbers to a decision-maker won't get you anywhere in a conversation about data and a company's future. Analysis may be the science, but charts and graphs are the art.

The average salary for a Data Analyst in the United States is more than $60,000 and Data Analysts and Business Analysts are considered some of the best jobs in America. They're important, high-paying roles that get to deal with challenging problems and come up with innovative solutions on a daily basis. If that sounds like it might be something that interests you, check out The Dynamic Data Scientist Bundle.

This comprehensive bundle offers seven courses and 33 hours of instruction in analytics, visualization, preprocessing, and other data science skills. First, you'll get a crash course in advanced data structures, understanding how to code in a multitude of structures that will make you a better programmer.

You'll learn some of today's most important data processing tools, including Microsoft Power BI and MATLAB. While learning MATLAB, you'll discover how to use data in machine learning algorithms, creating AI-powered engines that can make recommendations, answer questions, and more.

From there, you'll delve into visualization using Python. This powerful, general-purpose programming language will help you automatically plot data and visualize it the way you see it in your head. Working in conjunction with Matplotlib, you'll discover many opportunities and methods for data visualization and learn the technical skills to create plots using Python. After a beginner-friendly course, you'll learn more advanced tactics and discover how to increase customization and create different types of plots.

People have been plotting data for centuries, but never has it seemed so crucial to running a business and succeeding in the industry. The Dynamic Data Scientist Bundle will teach you how to use and visualize data effectively so you can get a job as an analyst or run your own company more efficiently.

Right now, this bundle is available for just $29.99, more than 90% off the usual price.

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