Data Preparation for Analytics with Alteryx

Data Preparation for Analytics A-Zâ„¢: Alteryx Hands-on

Master the Art of Data Preparation using Alteryx

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Last Updated: 2024-11-19 06:11:18 English Course Type: Self Learning

In-depth understanding of common data sources and types of Data
How to identify and correct common issues with Data
To format data in useful ways for analysis
To blend data from multiple sources together
Throughout this course you'll also learn the techniques to apply your knowledge in a data analytics program called Alteryx. At the end of the course, you'll complete a project based on the principles in the course.

This is specially crafted course that provides in-depth knowledge of Data Preparation fundamentals.

Data preparation is an integral step to generate insights. It is one of the most time-consuming and crucial processes in data mining. In simple words, data preparation is the method of collecting, cleaning, processing and consolidating the data for use in analysis. It enriches the data, transforms it and improves the accuracy of the outcome. Some of the key challenges faced by analysts and data scientists in dealing with data preparation include:

Multiple data formats
Data inconsistency
Limited/large access to data
Lack of data integration infrastructure

Data preparation is mostly done through analytical or traditional extract, transform, and load (ETL) tools. Both of which have their own advantages and limitations. In order to effectively integrate a variety of data sources, organizations should align the data, transform it and promote the development and adoption of data standards. All these things should effectively manage the volume, variety, veracity and velocity of the data.

Basic knowledge of computers

You are new to the world of data and starting in the field of problem solving with Data
You should take this course if you are as aspiring Business Analyst
You should take this course if you are as aspiring Data Analyst
You should take this course if you are as aspiring Data Scientist

Section 1 : Understanding Data 13 Lectures 00:15:23
Lecture 1 :
Course Introduction Preview
Lecture 2 :
Lesson Introduction
Lecture 3 :
Structure of Data
Lecture 4 :
Three Types of Data Structure
Lecture 5 :
Course Outline
Lecture 6 :
Data Sources - Files
Lecture 7 :
Data Sources - File Example
Lecture 8 :
Data Sources - File Example Continued
Lecture 9 :
Alteryx Exercise - Solution
Lecture 10 :
Data Sources - Databases
Lecture 11 :
Data Sources - Web-based Sources
Lecture 12 :
Data Sources - Web-scrapping Solution
Lecture 13 :
Data Sources - Web-scrapping Exercise

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