Choosing a career means finding something to do for a living that’s interesting and rewarding and can also provide you with a sustaining wage. Coding and data science are related fields that both play increasingly important roles in modern society, and the job outlook for people who understand code and how to interpret data sets is very good. Coding and analytics may sound a bit daunting, but luckily, the Internet has many resources to make learning about these topics doable even for people who have no background in either subject.
Data science might sound like it would be hard to learn, but a wide variety of resources are available to help you. Google Analytics is a user-friendly option for learning some basic analytics skills while also learning how to analyze large amounts of data. A basic understanding of statistics is also needed to understand what the data is (and is not) revealing about customer behavior or other metrics. Videos, worksheets, and textbooks are available online so that people can learn the fundamentals of statistics as well.
Data science is a field that makes use of large amounts of data to support the goals of businesses and institutions. For example, a data scientist might use information about abandoned shopping carts to figure out why shoppers don’t complete purchases so they can better understand how to reduce the number of abandoned carts. Data scientists use data to inform business decisions, improve website design, and understand how software can be improved for users. They interpret data into written, illustrated reports that can be understood by people without deep knowledge of the field.
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- How to Become a (Good) Data Scientist: Beginner Guide
Also called computer programming, coding is the way software, app, and website developers communicate with computers, devices, and networks. Coding involves the coder giving directions to the computer. Having the ability to communicate efficiently with a computer is a valuable skill, as the things people create with code are all around us every day. Writing code is like writing anything: It’s important to be clear and concise. There are different coding languages used for different types of projects, from the simplest app to a robot-operated factory. Coders are also known as software engineers, Web developers, and programmers.
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Analytics is the way that data patterns are found, interpreted, and shared. Businesses depend on analytics to make decisions that will increase customer satisfaction, improve sales, and increase operational efficiency. Smartphones, computers, and other devices collect data that businesses can use to better understand their customers. For example, Google Analytics provides an analysis of data collected from websites. Website owners can use this information to understand how visitors interact with every aspect of their site.
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- Learning Analytics 101
- How to Teach Yourself Data Analytics: The Ultimate Guide
- What Is Data Analytics?
- Four Types of Data Analytics to Improve Decision-Making
- Introduction to Data Analytics Handbook
Statistics is another field related to analyzing data. It’s an interdisciplinary topic, encompassing science, math, and social science. The two primary concepts in statistics are uncertainty and variation. There are many situations in business, science, and life where the outcome is unknown; probability is a mathematical concept used to discuss the likelihood that certain outcomes will happen. But variation can always come into play. For example, statistics can show the probability of customers abandoning their online shopping carts, but variation (like a certain item going viral on TikTok) can mean the outcome is very different than what was expected.