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Introduction to Alteryx

Learn about data science using Alteryx and how to build Alteryx workflows in this free online course.

Publisher: SimonSezIT
This free online course will teach you about various tools and functionalities in Alteryx and how to create ETL (Extract, Transform and Load) Processes. You will learn how to develop repeatable Alteryx workflows and the concept of data parsing and data parsing technique. Also, learners will gain an understanding of how to create reports in Alteryx that run on demand and how to use the predictive tools in Alteryx to perform data analysis.
Introduction to Alteryx
  • Duration

    3-4 Hours
  • Students

    169
  • Accreditation

    CPD

Description

Modules

Outcome

Certification

View course modules

Description

The growth in technology has resulted in our growth in understanding. In today’s world, the impact of data science reaches far beyond the business sector and is helping to solve some of mankind's most pressing issues. Happily, there is a growing number of tools to help make sense of the volume of raw data now available. Alteryx is one of those. However, in this course, you will be introduced to Alteryx and you will be taught how to automate data processes with the power of Alteryx. A workflow consists of connected tools that perform different functions to process data. You will be shown what the workflow canvas is used for and you will be introduced to different parts of the interface design of the Alteryx overview window. You will be exposed to tools such as Spatial Mapping, Join, Union, Tile, Filter, Select, Sample, Parsing and Maps just to name a few. This course goes on to teach you how to configure these tools. Learners will gain an understanding of the concept of workflow and how you can save and share your workflow. Furthermore, learners will be taught how data comes into Alteryx, how to easily change the data types and best practices for working with data.

Next, in this course, you will be taught how to automate processes, designing robust optimization algorithms as well as combining several inputs to draw insights from data. There may be the need to combine data into one singular graph so that you can consume the data sets easily rather than adding multiple visuals from diverse sources into one report. So how do you bring this data together for analysis? How do you compare values across different sources? Based on these questions, you will be introduced to the concept of data blend and prep. You will learn how to quickly filter data to isolate rows that fit a given criteria and you will be shown how to remove data that is not needed. You will be shown a lot of the things people use Excel for, including Excel terminology and how that translates in Alteryx. You will also be taught how to leverage pre-existing SQL queries with Alteryx, how to translate common SQL keywords to their corresponding Alteryx tool and Alteryx basic functions.

An important aspect of data being fit for any purpose is the structure it is found in. Often, the structure itself may not be suitable for the needs of the data. Alternatively, the structure of the data may be sound, but the use of it is insufficiently controlled or subject to error. To solve the problem of keeping data fit for any purpose, we need to know what it means to parse data. You will be introduced to the concept of data parsing and data parsing techniques using the Alteryx parse tool palette. The dynamic rename tool has two inputs: left and right. You will be taught what they mean and how the tool can be used to parse text files. You will be shown the demonstration of how a VLOOKUP can be done using Alteryx and how to work on multiple fields in Alteryx. Also, learners will gain an understanding of the best way to clean up messy data input. This course is suitable for aspiring data scientists and analysts and also for anyone who is new to Alteryx. More so, this course is important for learners who want to gain the ability to work efficiently within the Alteryx designer platform. This course is perfect for beginners and basic knowledge of computers, SQL, statistics and intermediate to advanced Excel understanding will be a plus for anyone taking this course.

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