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First, download the dataset with all countries and their continents from Our World in Data. Then, also download the CSV file that has the population for each country here. After you have them both downloaded and saved onto your file system, we can join the datasets together. We drag the table...

Now that you’ve downloaded Tableau Public, we can start it and load the data. In this tutorial we will use the our world in data dataset related to water withdrawals per person. To provide some context, water withdrawal refers to the amount of freshwater that is collected from surface water (for...

When you are dealing with real data and you want to be able to work with it and derive information in an efficient way, you should consider using Tableau. Tableau allows you to simply push buttons and now you too can create beautiful, interactive, and dynamic visualizations of your data without...

Alteryx, like any tool, has some best practices to follow so you get the best output. We will look at 5, but if you want to find out more, look for the PDF with 24 Best Practices that was shared in the Alteryx community. 1. Eliminate any browse tools: The browse tool is beneficial during the...

Workflow automation means using software to execute jobs without human involvement. It is a tool that is commonly used in business that speeds up processes and minimizes the need for manual work and activities that are repetitive. We can automate workflows in Alteryx by utilizing Batch Macros...

Data can take on many forms, shapes, and structures. Sometimes, you may be set to jump right into analysis, but usually this is in a data competition. In the real world, data is messy and a data professional's job is to organize data in a way that can be queried to provide valuable meaning...

Data preparation is also known as pre-processing, which is simply the process of taking raw data and transforming it into a version that is easy and accurate enough to analyze or be used as input into a machine learning model. People typically don't like to talk about this aspect of being a data...

When you open Alteryx Designer, you would automatically be provided with a Workflow, but let's pretend that is not the case. To create a new workflow, click on “File” on the top left hand corner and select “New Workflow.” This will create a new tab in the Workflow Canvas for your new workflow...

Workflows are created in the Workflow Canvas space. For clarity, a workflow only defines a series of tools that execute various functions that ultimately process data. Within the workflow, you can save relative paths to the various data sources, and you will be able to share workflows with...

We have a complete guide talking about Alteryx and what it is. However, to make it brief, Alteryx is a data analytics and visualization tool that focuses on making advanced analytics automation simple and making it available for all data professionals. Alteryx is a tool that allows users to...

What Are Formats in SAS? Formats in SAS are used to control how data values are displayed rather than how they are stored. They can be applied in a number of ways, including :Displaying numeric values in a readable way (e.g., currency, percent) Grouping categories Formatting dates and times...

This tutorial will explain how to change a numeric variable to a date variable in SAS with examples. Assuming you have a numeric variable that contains dates, you are asked to convert it to SAS date format. Although this may seem easy, it can often be a troublesome task if you don't understand...

This lesson details a variety of approaches we can use to convert a character variable (string) to a date variable in SAS. Let's assume you run into a situation in which you need to convert character variable to SAS date format. This will typically happen when we upload raw data file type (TXT...

What Are Missing Values in SAS? In SAS, missing values indicate an absence of values. Missing values can occur in both numeric and character variables:Numeric Missing Value: A dot (.).Character Missing Value: A blank space (' ' or ""). Row 1 has a missing numeric value for age. Row 3 has a...

The IN operator in SAS is used to make a comparison between an individual value and a collection of values. It allows one to choose several values within a SAS dataset. It works as a substitute of several OR statements. The IN operator's syntax in SAS is as follows: Here a set of discrete...

Data represents any raw facts, figures, or information that may be gathered, measured, or analyzed. It could come in different forms: numbers, text, images, audio, or video. Generally, data is used in representing real-world phenomena or describing particular attributes of something, like the...

Below are the types of Machine Learning. 1) Supervised Learning Definition: The model is trained in supervised learning using a labeled dataset, meaning each training example is coupled with an output label or result. Goal: It learns mapping inputs to the right output such that it...

Below are some of the key concepts in Machine Learning. Data: It is the foundation of ML. The models are trained using this, and the performance of the machine learning system is impacted directly by its quality and quantity. Algorithms: These are the mathematical procedures or models that...

Machine learning (ML) can be taken as a subset of artificial intelligence, where computers learn from the data and make decisions or predictions based on the information without explicit programming. In simpler terms, it is the ability of machines to identify patterns from new sets of data and...

The four phases of analytics are usually defined as a systematic process of data understanding and extraction of value from data. The four phases of analytics help an organization move from raw data to actionable insights. The four phases are 1) What happened : Analytics of past - Descriptive...