CareerFoundry Data Analytics Blog

How you visualize your data depends on the type of data you have. In this guide, we explain the most common types of data visualization and when to use them.

Data can be beautiful! And data visualization is a crucial part of the data analytics process. Allow these data viz examples to inspire you.

If you find that numbers have been stored incorrectly as text in your Excel spreadsheet, there are some simple ways to fix the issue. Learn about them here.

The VLOOKUP function allows you to look up data in a table within a Microsoft Excel spreadsheet. Learn how to use it here.

Bernoulli distribution is a simple yet important type of distribution, laying the foundation for more complex distributions and machine learning models. Learn more in this introductory guide.

As a data analyst, a crucial part of your role is presenting your insights visually. With that in mind, here are the best data visualization tools on the market right now.

Machine learning and deep learning are two subsets of artificial intelligence. What's the difference between them, and how do they relate? Find out here.

The AVERAGE function allows you to quickly and easily calculate the average of a given range of numbers. Learn how to use this handy function here.

The XLOOKUP function in Excel is a powerful search tool, allowing you to find particular values from a range of cells. Learn more in this guide.

The COUNTIFS function is used to count only the values in a list that meet specified criteria. Learn how to use it in this step-by-step tutorial.

The IFERROR function is used to catch formula errors in Microsoft Excel. Learn how to use this handy function here.

All statistical techniques can be divided into two categories: descriptive and inferential statistics. In this post, we explore the differences between the two, and how they impact the field of data analytics.

What do data scientists and data engineers actually do? Do the roles overlap, and what are the key skills of each? Find out here.

Machine learning is a complex yet exciting field, and programming languages have a key role to play. So what's the best language for machine learning? Find out here.

The big data market is growing exponentially—as is the demand for data scientists. Considering a data science bootcamp? Here are our top picks.

The IF function in Excel enables you to check for certain conditions within your data. Learn how to use the IF function in this step-by-step tutorial.

Exploratory data analysis, or EDA, is one of the first steps in the data analytics process. Learn what EDA is, why it's important, and a few techniques to help you get started here.

Data wrangling is the transformation of raw data into a usable format. But what exactly does the process entail? Find out in this introductory guide.

The STDEV function in Excel allows you to determine the standard deviation of a data sample. But what does this mean, and how does the function work? Find out in this guide.

Multivariate analysis enables you to explore several variables simultaneously—allowing for deeper, more complex insights. Learn all about multivariate analysis in this guide.

The Goal Seek function in Excel allows you to adjust an input value in a formula to determine a desired outcome. Learn how to use it in this step-by-step tutorial.

In data analytics, regression and classification are techniques used to carry out predictive analyses. But how do these models work, and how do they differ? Find out here.

Podcasts are a great way to learn on the go, gain broader industry knowledge, and hear from experts in the field. So which data podcasts should you tune into? Here are our favorites.

The SUBTOTAL function in Microsoft Excel returns the subtotal value from a range of cells. Learn how to use the SUBTOTAL function in this step-by-step tutorial.

Web scraping is a technique used by data analysts to gather data from the web. Learn what web scraping is, how it works, and why it’s so important in this guide.

Which industries are hiring data analysts and data scientists right now? How much do they pay? Find out in this guide.

The SUMIF function in Microsoft Excel allows you to calculate the combined values of different cells, based on specific criteria. In this tutorial, we’ll explain, step-by-step, how to use the SUMIF function.

Data quality is crucial in the fields of data analytics and data science. Want to know how to quality-check your data? Find out here.

Effective data cleaning is a vital part of the data analytics process. But what is it, why is it important, and how do you do it? Find out in this guide.

The data market is growing at a rapid pace—but how easy is it for newcomers to break into the field? In this post, we explain why you don't need years of experience to become a data analyst.

SQL is an essential skill for anyone working (or aspiring to work in) the data industry. Learn how to write SQL queries in this hands-on tutorial.

An internship can be an excellent way to gain hands-on experience in the data industry. Find out how to land one in this guide.

Are you fascinated by data? Want to know what's going on in the industry? Then check out these inspirational, insightful, and thought-provoking quotes.

The CONCATENATE function is one of many Excel formulas used by data experts. Learn what it's used for and how to apply it in this step-by-step tutorial.

Business analyst and data analyst—two distinct job titles, or just different names for the same role? Learn where the two overlap and how they differ in this guide.

If you're considering a career in data, there are two types of data you'll need to work with: Quantitative and qualitative. So what's the difference between the two? Find out here.

For data analysts, the healthcare sector offers a fascinating career path—and an opportunity to use your data skills for good. What does a healthcare analyst do, and how can you become one? Find out here.

Data analysts and data scientists work with quantitative data on a daily basis. Learn exactly what quantitative data is, how it differs from qualitative data, and how it's gathered and analyzed.

Random Forest is a handy machine learning algorithm used by data scientists across a variety of industries. Learn how Random Forest works and what it's used for here.

Data analysis skills serve as an excellent starting point for a career in data science. Find out how to make the transition from data analyst to data scientist in this guide.

How can you make sure your data analytics portfolio stands out and convinces hiring managers to give you a shot? Follow these five best practices.

What happens once you qualify as a data analyst? Is there a typical career path you can expect to follow? Find out in this guide.

Where do data analysts earn the most, and which industries pay the highest salaries? What can you do to increase your earning potential? Find out here.

Applying for a job as a data analyst? Learn how to write a winning data analytics resumé in this guide, complete with examples.

What's the job market like for remote data analysts, and how much can they earn? Where should you look for remote data jobs? Discover everything you need to know here.

Navigating the data analytics job market can be tricky. In this guide, we consider a variety of different data analytics job titles and what they really mean.

If you're in need of some inspiration for your data analytics portfolio, look no further. Here are nine of our favorite data portfolio examples from around the web.

When it comes to data analysis, there's a step-by-step framework you can follow to take you from raw data to meaningful insights. We've broken the process down in this guide.

In its simplest form, a decision tree is a type of flowchart that shows a clear pathway to a decision. So how are decision trees used in data analytics and machine learning? Find out in this guide.

Finding projects for your data analytics portfolio can be tricky, especially when you're new to the field. Stuck for inspiration? Here are nine project ideas to help you build your portfolio from scratch.