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Alteryx – Data processing, Data Manipulation and Analytics

A complete guide to ETL and Data Analytics for IT team and Data Scientists
Instructor:
Steven Martin
1,281 students enrolled
English [Auto-generated]
After taking this comprehensive guide to Alteryx, students will gain expertise in understanding of ETL process and data science concepts. This is not just limited to transforming structured data, data mining, data wrangling and deriving insights from data however it covers an extra mile in gaining knowledge in predictive modeling,analytical and statistical techniques for solving real time business problems

In this course we will make you a champion in Alteryx tool. From data extraction to business analytics this course will give you a good direction to kick start with your aspirations of delivering in Business Intelligence and/or Data Analytics. We will be majorly focusing on Business Intelligence and will add concepts of Analytics. You will learn how to extract data from raw data sources, manipulate data and utilize data for running linear and logistic regression models besides machine learning models like SVM and DT. You will also understand forecasting for a time series driven data.

Trainer & Course Introduction

1
Alteryx Course outline

A detailed discussion on what Alteryx and data analytics topics we are covering in this course. This course will be very useful for ETL developers and/or Data analysts and Data scientists looking for enhancing or starting their career into the world of Business Intelligence and Business Analytics.

2
What’s in it for the trainees?

A motivating video providing a reason of why you should take up the course. You should take up the course because Alteryx is an easy to understand tool, We have included intuitive slides so that we can make this training interactive, the course is very comprehensive as it is focused not just on data analysts but also on software developers, we are also covering interview questions and 2 elaborated projects towards end of this course.

3
Agenda Video

In this lesson we will discuss about agenda items for this lesson and entire course. The agenda items will be (1) Trainer introduction - Background and experience (2) Alteryx course outline. (3) Why you should take up this course

4
Discount code
5
Trainer Introduction, Industry and Training experience

An education background about trainer and how he evolved his career into development and data analytics industry. A brief about the extensive training experience Steven has on niche technologies like Informatica, Alteryx, Tableau, SAS DI Studio, Spark, Hadoop, Advanced SAS. These technologies are used in Business Intelligence and data analytics space.

Significance of data

1
Why data is becoming so popular now a days

Agenda slide on importance of data and history of data spurt. Database concepts and jargons.

2
Jargons used in Database engineering and Data Analytics Part I

Jargons used in databases like What is database, structured data

3
Jargons used in Database engineering and Data Analytics Part II

Jargons used in databases like semi-structured data, unstructured data, ETL, variable, observation, data type.

4
Core concepts of Relational database

Understanding of core concepts of data bases like Primary key, foreign key. How are tables maintained in a relational database and what is the relevance.

What is ETL and Analytics?

1
Agenda of this section

Agenda slide on Core Concepts of ETL & data processing tools, Core Concepts of Analytics & Analytical tools and Application of Analytics

2
Introduction to core concept of ETL & data processing tools

Understanding the ETL concept i.e Extract, transform and load of data. How does ETL work in creating a enterprise data warehouse. Discussion on various ETL tools available.

3
Introduction to core concept of Analytics & analytical tools

Evolution of data from raw data sources to a meaningful insights. Before a decision is made by the stakeholders of company how is data processed and the tedious transformation it goes through. Various analytical tools available.

4
Application of Analytics

Certain industry use cases where analytics can be used to take business decisions.

Downloading Alteryx. Getting familiar with Alteryx environment and Alteryx Serve

1
Agenda for Lesson 04

Agenda discussion on - Downloading Alteryx Designer  - 14 day trial version,  Alteryx at a Glance, Servers and platforms & A deep dive into Alteryx  - Options available in Alteryx Tool.

2
Downloading Alteryx Designer - 14 day trial version

A video on how to download Alteryx designer a 14 day trial software on your local desktop.

3
Alteryx at a Glance

Accessing Alteryx. Look and feel of Alteryx. What does various ribbon and tools do in Alteryx.

4
Alteryx Servers and platforms

Different modules of Alteryx with industry relevance. Modules of Alteryx are Alteryx Designer, Desktop Automation and Alteryx Server

5
A deep dive into Alteryx - Options available in Alteryx Tool

A detailed discussion on some of tools in Alteryx. How to make use of canvas to define workflows.

What is Alteryx? And Why Organizations are using Alteryx?

1
What is Alteryx?

History of Alteryx, What all can Alteryx do and capabilities of Alteryx.

2
Why Organizations are using Alteryx

Why Alteryx? - Alteryx as a ONE STOP SHOP. Provides solutions for ETL, Visualization and Data/Statistical Analytics. Alteryx – An end to end tool.

Data extraction: Raw files and Databases

1
Data extraction/Importing from raw files Part I

Importing a data from raw data file that can be csv or excel or flat files or a Database.

2
Data extraction/Importing from raw files Part II

Importing a data from raw data file using Input Tool in Alteryx and how to visualize data in Alteryx in table format.

3
Data Import from databases and creating data manually with Text Input Tool

Using Text Input tool to manually create a dataset in Alteryx with Variables and observations.

4
Types of data variables in Alteryx

Various kinds of Character, Numeric and date data types in Alteryx. Refer to below link for various data types:

https://help.alteryx.com/current/Reference/DataFieldType.htm

Saving Datasets and work flow. File and data formats in Alteryx

1
Saving Workflow and formats

Basic understanding of how to save a Alteryx dataset and workflow. Various formats of Alteryx files.

Efficient management of data space in tables with Auto field tool

1
Auto field tool

Efficient management of variables and tables size with Auto field tool functionality in Alteryx.

Browse Tool to view all records

1
Browse tool and its implications

Visualizing the large volume of data with Browse tool. Since all records are not visible by default in Alteryx and if you want to visualize data with more than 7,000 records, it can be visualized with Browse tool.

Know your data – Types of variables

1
Quantitative & Qualitative data

An understanding of data variables is imperative for a BI or Data Analyst. Types of variables are classified into Quantitative and Qualitative at a broader level. Quantitative variables are further classified into Continuous and Discrete. Qualitative variables are further classified into nominal and ordinal. 

Data Wrangling – Creating a new column with Formula Tool. Using Filter tool

1
Creating a copy of variables

Creating copy of a variable using Formula Tool and changing attribute of new variable from one data type to another.

2
Creating a new column (Categorical Variable) with if then else condition

Conditional statements: Using a "If then else" conditional statement to create a new Qualitative variable based on monthly usage for a telecom company.

3
Filtering records with single and multiple conditions using And/OR operators

Filtering records with filter tool. Also understanding if we want to use "And" & "OR" Operator along with the filter tool.

Data Wrangling – Selecting few variables and Mending variable attributes using S

1
Data transformation and selecting few variables into new datasets

Making subset of a dataset and changing attribute of a variable. Understanding the relevance of creating a subset of dataset.

Numeric functions

1
Creating a numeric variable with Numeric Operators (+, -,*,/)

Creating a new variable using arithmetic calculations. We can use numeric operators like +,-,* etc.

2
Creating a numeric variable with numeric function

Creating a variable with numeric attribute. Understanding numeric functions like sum, average, max, min, power, ceiling, floor, absolute.

Character functions

1
What are Char functions. Video on Scan function

Significance of character functions. Understanding Text to column Tool to split observation values in a variable on the basis of a delimiter. Difference between error and warning and how critical is error and warning.

2
Substring function to extract text string on the basis of position of text

When the data is not separated by delimiter necessarily and you would like to separate the observations in a variable on the basis of indexing or position of text string, substring function can be used to perform such operations.

3
Uppercase, lower case and trim function. Using Nesting functions

Data cleaning with Upper case, lower case and trim functions to bring observations at par. Nesting one function another inside to avoid multiple steps and create an efficient workflow.

4
Concatenating text strings and variables

Concatenating first name and last name into one column. Using character function with concatenation.

5
Replace function to replace text string

Replacing a text string to clean junk or unnecessary values in a Character variables, with use of Replace function.

6
Findstring function and Application of function

A complicated scenario to extract a text string with use of findstring function and other functions like substring.

Handling dates and other formats

1
Converting a variable into date data type

Handling date variables. Conversion of a character variable which as dates, into date variables is important so that Alteryx can do the computation in such variables.

2
Using Date functions

Date functions can be used in Date variables only. Certain date functions to add or substract days from a date variables.

3
Handling a currency variable

Handling currency formats in Alteryx and playing with a trick to convert currenty variable into numeric variable.

Summarize Tools - Functions in Alteryx to derive insightful data

1
Summarizing the data with Summarize tool

Understanding group by functionality to summarize data at grouping variable and aggregation variable levels.

2
Cumulative total with Running totals

Evaluating the cumulative totals for a numeric variable and how to evaluate running totals for a Retail sales data.

Arranging data - Sorting & Cascade sorting

1
Sorting a numeric variable and character variable

Sorting a variable to evaluate top 50 records with highest sales. Also understanding how to sort character variables.

2
Cascade Sorting – sorting by 2 variables

Sorting variables at 2 levels and the business significance of cascade sorting.

Handling duplicate observations and duplicate variable values with Unique Tool

1
Removing duplicate records

Removing duplicate records. Records are called as duplicates in case they have exactly same value throughout all variables.

2
Finding unique values of a single variable

Removing duplicates at a single variable level.

3
Application – Use case scenario of Unique tool

Understanding a business case scenario for a retail chain data and implementing Unique tool.

Sampling and Creating Union/concatenation of data using Sample and Union tools

1
Sampling and Union Tool

Creating subset of a data through Sample tool. Select first or last few records. Concatenating records of 2 tables.

Joining tables with a common key

1
Concept of Joins

Understanding industry relevance of joins and revising concept of relational database. We will discuss How are tables joined with respect to a key variable and how do we populate variables from different tables to make one consolidated table with all relevant variables required for analysis.

2
Left Join

Left join will consist of all the records from left table.

3
Right, Inner and Outer Join

Right join will consist of all records from right table. Inner join will give us common records. Outer join will give all observations across both the tables.

Transposing data

1
Long to wide transpose

Transposing a data which has higher number of records to lower number of records by converting one of variable into columns.

2
Wide to long transpose

Transposing a data which has lower number of records to higher number of records by converting few variables into one columns.

Frequency of categorical variables

1
One way frequency with frequency table tool

Creating frequency of a Qualitative variable so that business can draw some insights into volume of business driven through top products.

2
N way frequency with contingency table tool

Creating frequency of a 2 Qualitative variable so that business can understand which product has higher Order priority inclination.

Automating the workflows with Macros and Global Constants

1
Need for Macros as reusable workflow

Understanding the need for making macros for replicating workflows periodically i.e weekly or monthly.

2
Automation of Process – Creating/Compiling a Macro workflow Step I

Creating a macro workflow and setting up an automated process to be reused.

3
Automation of Process – Calling/Executing a Macro workflow Step II

Calling a Macro workflow post creation. Passing the input dataset values in runtime.

4
Global Constants: Make a dynamic process with input constants as dynamic

Concept of Global constants - Is a value of a variable which can be accessed anywhere in workflow. Integrating the global constants with workflow to make dynamic usage.

Replacing Missing values

1
Replacing missing values – Simple approach

Replacing missing values with overall averages.

2
Replacing missing values for cohorts with 1 variable averages

Replacing missing values with averages across one variable only.

3
Replacing missing values for cohorts with more than 1 variable averages

Replacing missing values with averages across multiple variable and business sense for doing so.

Intro to Data Analytics and decision making

1
Agenda for the Lesson

Agenda - (1) What is Analytics? (2) Types of Analytics with a Case study (3) Industry specific examples

2
What is Analytics?

Analytics is exploration and interpretation of data to find out meaningful and insightful patterns so that these can be applied towards decision Making

3
Use case of Analytics in E-commerce company

A perfect example of Analytics with a online retail company. How does company identify how much discount is optimal for meeting the sales targets for a business.

4
Types of Analytics

4 types of analytics viz. Descriptive, Diagnostic, Predictive and Prescriptive.  Understanding the concept of each of them with the online retail company.

5
Industry specific examples and use cases of Analytics

A elaborated discussion on how analytics can be used in various industries like retail, banking, Healthcare and telecom.

Linear and Logistic Regression - Running Statistical models with Predictive Tool

1
Understanding of Boston Data for Linear Regression

Linear regression is used to predict a continuous variable. Understanding a Boston data, each row represents one house and price of it corresponding to variables like crime rate in city, number of rooms etc.

2
Linear Regression with Alteryx : Running Model and selecting significant variab

Linear Regression tool to build a model on a continuous dependent variable. Identifying impactful variables and selecting those variables into final model.

3
Making predictions with Score Tool

Once the model is built next step is to make predictions on the basis of linear equation. We will understand how to use score tool to make predictions.

4
Understanding Need for Logistic Regression with banking data

Understanding the need for logistic regression. Logistic regression is used to predict a binary variable i.e variable which has 2 outcomes like pass or fail, success or unsuccess, default or non default etc.

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