What is data analysis?

Data analysis is the process of applying statistical analysis and logical techniques to extract information from data. When carried out carefully and systematically, the results of data analysis can be an invaluable complement to qualitative research in producing actionable insights for decision-making. If that sounds a lot like data science, you’re right! It’s a closely related field, but there are important differences. Data scientists typically come from computer science and programming backgrounds and rely on coding skills to build algorithms and analytic models to automate the processing of data at scale. Data analysts typically have backgrounds in mathematics and statistics, and frequently apply these analytic techniques to answer specific business problems - for example, a financial analyst at an investment bank.

What skills do I need to become a data analyst?

Data analysts don’t do as much coding as data scientists, but it’s still important to know your way around certain programming languages. In particular, SQL (Structured Query Language) is the industry standard for navigating large databases, and statistical programming languages like R or Python are essential for performing advanced analyses on this data. Data analysts also rely on more typical business programs. While Microsoft Excel isn’t as powerful as SQL, R, and Python, it can get the job done when working with relatively smaller datasets, and may be the best (and cheapest) tool for the job for early-stage lean startups. Data visualization and presentation skills are also a huge part of the job, which typically requires learning new programs like Tableau as well as mastery of standard business software like Excel and Powerpoint.

How much do data analysts make?

According to Glassdoor , the average median annual salary for a data analyst was $69,291 as of November 2019. Of course, because data analysis is in demand across a wide range of industries, the salaries of two data scientists with similar job descriptions might be quite different depending on whether they're working with a small startup or a global hedge fund. Around this median, Glassdoor found data analyst salaries as high as $105,000 and as low as $48,000.

What kind of courses are available for learning data analysis online?

As with data science, online courses are a great way to learn data analysis skills, and Coursera offers professional certificates, MasterTrack certificates, Specializations, and courses in data analysis from top universities like Duke University, University of Michigan and companies like IBM and pwc. Many courses are shared between data science and data analysis, such as introductions to data science and data science programming with SQL , Python , and R . There are also courses more specific to data analysis, such as data analysis and interpretation skills , Excel skills for business , exploratory data analysis , and a variety of courses on statistics and probability .

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Data analysis is the process of applying statistical analysis and logical techniques to extract information from data. When carried out carefully and systematically, the results of data analysis can be an invaluable complement to qualitative research in producing actionable insights for decision-making.
If that sounds a lot like data science, you’re right! It’s a closely related field, but there are important differences. Data scientists typically come from computer science and programming backgrounds and rely on coding skills to build algorithms and analytic models to automate the processing of data at scale. Data analysts typically have backgrounds in mathematics and statistics, and frequently apply these analytic techniques to answer specific business problems - for example, a financial analyst at an investment bank.
Data analysts don’t do as much coding as data scientists, but it’s still important to know your way around certain programming languages. In particular, SQL (Structured Query Language) is the industry standard for navigating large databases, and statistical programming languages like R or Python are essential for performing advanced analyses on this data.
Data analysts also rely on more typical business programs. While Microsoft Excel isn’t as powerful as SQL, R, and Python, it can get the job done when working with relatively smaller datasets, and may be the best (and cheapest) tool for the job for early-stage lean startups. Data visualization and presentation skills are also a huge part of the job, which typically requires learning new programs like Tableau as well as mastery of standard business software like Excel and Powerpoint.
According to Glassdoor, the average median annual salary for a data analyst was $69,291 as of November 2019. Of course, because data analysis is in demand across a wide range of industries, the salaries of two data scientists with similar job descriptions might be quite different depending on whether they're working with a small startup or a global hedge fund. Around this median, Glassdoor found data analyst salaries as high as $105,000 and as low as $48,000.
As with data science, online courses are a great way to learn data analysis skills, and Coursera offers professional certificates, MasterTrack certificates, Specializations, and courses in data analysis from top universities like Duke University, University of Michigan and companies like IBM and pwc.
Many courses are shared between data science and data analysis, such as introductions to data science and data science programming with SQL, Python, and R. There are also courses more specific to data analysis, such as data analysis and interpretation skills, Excel skills for business, exploratory data analysis, and a variety of courses on statistics and probability.