Data Analytics
What is data analytics?
Data analytics is a multidisciplinary field that employs a wide range of analysis techniques, including math, statistics, and computer science, to draw insights from data sets. Data analytics is a broad term that includes everything from simply analyzing data to theorizing ways of collecting data and creating the frameworks needed to store it.
How is data analytics used? Data analytics examples
Data is everywhere, and people use data every day, whether they realize it or not. Daily tasks such as measuring coffee beans to make your morning cup, checking the weather report before deciding what to wear, or tracking your steps throughout the day with a fitness tracker can all be forms of analyzing and using data.
Data analytics is important across many industries, as many business leaders use data to make informed decisions. A sneaker manufacturer might look at sales data to determine which designs to continue and which to retire, or a?health care administrator?may look at inventory data to determine the medical supplies they should order. At Coursera, we may look at enrollment data to determine what kind of courses to add to our offerings.
Organizations that use data to drive business strategies often find that they are more confident, proactive, and financially savvy.
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Familiarize yourself with the world of data analysis with the Google Data Analytics professional certificate.
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Data analytics: Key concepts
There are four key types of data analytics: descriptive, diagnostic, predictive, and prescriptive.?Together, these four types of data analytics can help an organization make data-driven decisions. At a glance, each of them tells us the following:
People who work with data analytics will typically explore each of these four areas using the data analysis process, which includes?identifying?the question,?collecting?raw data,?cleaning?data,?analyzing?data, and?interpreting?the results.
Read more:?What Is Data Analysis? (With Examples)
Data analytics skills
Data analytics requires a wide range of skills to be performed effectively. According to search and enrollment data among Coursera’s community of 87 million global learners, these are the top in-demand data science skills, as of December 2021:
While careers in data analytics require a certain amount of technical knowledge, approaching the above skills methodically—for example by learning a little bit each day or learning from your mistakes—can help lead to mastery, and it’s never too late to get started.?
Data analytics jobs
Typically, data analytics professionals make higher-than-average salaries and are in high demand within the labor market. The US Bureau of Labor Statistics (BLS) projects that careers in data analytics fields will grow by 23 percent between 2021 and 2031—much faster than average—and are estimated to pay a higher-than-average annual income of $82,360 [1]. But according to the Anaconda 2022 State of Data Science report, 63% of commercial organizations surveyed expressed concern over a talent shortage in the face of such rapid growth [2].
Entry-level careers in data analytics?include roles such as:
As you gain more experience in the field, you may qualify for?mid- to upper-level roles?like:
Click through the links above to learn more about each career path, including what the roles entail as well as average salary and job growth.