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    Data Analytics for Beginners: Introduction to Data Analytics
    Data Analytics for Beginners: Introduction to Data Analytics
    Data Analytics for Beginners: Introduction to Data Analytics
    Ebook79 pages1 hour

    Data Analytics for Beginners: Introduction to Data Analytics

    By Anthony S. Williams

    4/5

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    • Data Analytics

    • Big Data

    • Data Analysis

    • Machine Learning

    • Data Mining

    • Quest

    • Power of Knowledge

    • Advanced Technology

    • High Stakes

    • Expert

    • Future Is Now

    • Business Competition

    • Resource Management

    • Career Advancement

    • Technological Progress

    • Data Processing

    • Business Intelligence

    • Decision Making

    • Predictive Modeling

    • Data Collection

    About this ebook

    Data Analytics For Beginners

    Knowing the data generated by your business every day is a key to success in the Data Analytic World that you are competing in. As there is so much data so, the organizations need to collect and store them. The data becomes valuable to businesses when it is analyzed.

    Prior to the recent rise in analytics, businesses and organizations did not have the capacity to analyze a great deal of data, so a relatively small amount was maintained. In today's data-driven world, anything and everything may have significance, so there has been an attempt to record and keep virtually any data that we have the capacity to collect; and we have a great deal of capacity.

    There is so much to learn in this book about data analytics and I do invite you to grab your copy today and get started!

    By downloading this book you will discover...

    • Putting Data Analytics to Work
    • The Rise of Data Analytics
    • Big Data Defined
    • Cluster Analysis
    • Applications of Cluster Analysis
    • Commonly Graphed Information
    • Data Visualization
    • Four Important Features of Data Visualization Software
    • Big Data Impact Envisaged by 2020
    • Pros and Cons of Big Data Analytics
    • And of course much more!

    Get this book today and learn more about Data Analytics!

    LanguageEnglish
    PublisherAnthony S. Williams
    Release dateNov 2, 2019
    ISBN9798201285128
    Data Analytics for Beginners: Introduction to Data Analytics

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    Reviews for Data Analytics for Beginners

    4/5

    18 ratings6 reviews

    What our readers think

    Readers find this title to be an awesome book that provides a good starting point for understanding data analysis. Although it is repetitive in the beginning, it later picks up a good pace. The book is a quick and easy read, making it a great introduction to data analytics for those interested in pursuing this career.

    What did you think?

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    Review must be at least 10 words

    • 5/5

      Oct 31, 2024

      wow, this is amazing. beautiful summary. thanks for this. now i can make my decision
    • 5/5

      Aug 17, 2024

      Well, I agree that the book was somewhat repetitive. It is a very good book for a beginner or somebody just exploring the field. This really is an introductory book and doesn’t dive into any one subject or specifics.
    • 1/5

      Apr 6, 2024

      Didn’t like it so repetitive quite wasteful and I don’t get why it is a book
    • 5/5

      Sep 10, 2023

      Awesome book I'm glad a gave it the time to read. Now I have a better understanding on data analysis.
    • 5/5

      Mar 12, 2023

      Nice easy digestable intro to data analytics for people curious on pursuing this career.
    • 4/5

      Jan 21, 2023

      Gives you a good starting point I would imagine. Extremely repetitive in the beginning but later had a good pace. The book Is a quick read and if you're starting out, this is not a loss at all

    Book preview

    Data Analytics for Beginners - Anthony S. Williams

    Data Analytics For Beginners

    ––––––––

    Introduction To Data Analytics

    By Anthony S. Williams

    Table Of Contents

    Introduction

    Chapter 1: Becoming a Data Analyst

    What Do Data Analysts Do?

    Data Analytics Sector and Qualifications

    Choose Your Career Path

    Chapter 2: What is Data Analytics?

    Chapter 3: Types of Data Analytics

    Descriptive Analytics

    Predictive Analytics

    Diagnostic Analytics

    Prescriptive Analytics

    Cognitive Analytics

    Chapter 4: The Evolution of Data Analytics

    Data Analytics Then

    Data Analytics Now

    Data Processing

    Predictive Modeling

    Visualization Technologies

    Data Analytics in the Future

    Chapter 5: What is Big Data?

    Big Data Volume, Velocity, and Variety

    Big Data Variability, Value, and Veracity

    Why Big Data Matters?

    How Does Big Data Work?

    Chapter 6: Data Mining

    The Process of Data Mining

    Data Mining Requirements and Techniques

    Data Cleaning

    Data Visualization Tools

    Cluster Analysis

    Conclusion

    Copyright © 2021 By Anthony Williams - All Rights Reserved.

    This document is geared towards providing exact and reliable information in regards to the topic and issue covered. The publication is sold with the idea that the publisher is not required to render accounting, officially permitted, or otherwise, qualified services. If advice is necessary, legal or professional, a practiced individual in the profession should be ordered.

    From a Declaration of Principles which was accepted and approved equally by a Committee of the American Bar Association and a Committee of Publishers and Associations.

    In no way is it legal to reproduce, duplicate, or transmit any part of this document by either electronic means or in printed format. Recording of this publication is strictly prohibited, and any storage of this document is not allowed unless with written permission from the publisher. All rights reserved.

    The information provided herein is stated to be truthful and consistent, in that any liability, in terms of inattention or otherwise, by any usage or abuse of any policies, processes, or directions contained within is the solitary and utter responsibility of the recipient reader. Under no circumstances will any legal responsibility or blame be held against the publisher for any reparation, damages, or monetary loss due to the information herein, either directly or indirectly.

    Respective authors own all copyrights not held by the publisher.

    The information herein is offered for informational purposes solely and is universal as so. The presentation of the information is without contract or any type of guarantee assurance.

    The trademarks that are used are without any consent, and the publication of the trademark is without permission or backing by the trademark owner. All trademarks and brands within this book are for clarifying purposes only and are owned by the owners themselves, not affiliated with this document.

    Introduction

    Even if you know nothing about data analytics, you have probably heard of these two words, especially if you are interested in any computer science field. So, what is data analytics? And is there any difference between data analysis and data analytics?

    Data analytics, especially big data analytics, has been and will continue to change and modify the world we live in.

    More specifically, data analytics is transforming the ways companies and businesses use the raw data they gather to make valuable conclusions about their products and services.

    In this digital world, making the right decisions makes a huge difference between succeeding and failing, and this is why data analytics is necessary.

    At a basic level, data analytics is a computer science that involves gathering various kinds of raw data in order to detect and analyze different trends and draw valuable conclusions based on massive data batches collected.

    Data analytics involves numerous techniques, and many of these techniques revolve around transforming raw data collected into other forms, which make it possible for businesses and companies to detect and analyze those important business metrics.

    If no data analytics techniques are used, all of those important metrics and information that raw data has will

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