Alteryx Self-Service Data Analytics A Beginner's Course

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Alteryx Self-Service Data Analytics : A Beginner's Course
.MP4 | Video: 1280x720, 30 fps(r) | Audio: AAC, 48000 Hz, 2ch | 2.06 GB
Duration: 3.5 hours | Genre: eLearning Video | Language: English

What you'll learn

    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.
    To blend data from multiple sources together
    To format data in useful ways for analysis
    Certification Preparation for Alteryx Core and Advanced

Requirements

    Basic knowledge of computers

Description

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.

Who this course is for:

    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
    You are new to the world of data and starting in the field of problem solving with Data
           

               

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