Data Analytics for Businesses 2019: Master Data Science with Optimised Marketing Strategies using Data Mining Algorithms (Artificial Intelligence, Machine Learning, Predictive Modelling and more)

By Riley Adams

Are you looking for new ways to grow your business, with resources you already have? Do you want to know how the big players like Netflix, Amazon, or Shopify use data analytics to MULTIPLY their growth? Keep listening to learn how to use data analytics to maximise YOUR business. 

Yes, you have customers that love your product. However, you're having trouble finding new customers and captivating their attention. You realized your also losing customers, and you have no clue what you can do to prevent this from happening. How do I stand out in a crowd of businesses? How do I target my perfect client and make them choose ME? If this sounds like you, Data Analytics for Businesses if the guide you need.

This book will walk you through the fundamental principles of data science and how to apply the "data analytic mindset" when approaching your business. You will learn how to extract valuable insights from data sources you ALREADY HAVE, and make informed business decisions to help you achieve your goals. 

With real world examples of how to apply data analytics to your business, this book does what others fail to do. Break the process down step by step, so you can optimize unique parts of your business; such as improving customer loyalty or reducing churn. This guide also helps you understand the many data-mining techniques in use today.

Discover the value of applied data science for business decision-making. You'll learn how to think data-analytically, and make connections between data sources to unveil insights you've never imagined. 

In this book you will learn:
* Why every company should be leveraging Data Analytics
* The difference between Big Data, Data Science and Data Analytics.
* How to achieve your goals by applying data-analytical thinking to your business
* The recommended data mining techniques for each of your business goals.
* The most important thing to remember when extracting knowledge from your data.
* How to use data analytics to improve brand loyalty and customer experience.
* How to hire the best data scientist, and more.

If you are overwhelmed by this whole new topic of data analytics, don't be. This guide is designed for beginners, with all the guidance you need to understand the fundamentals of harnessing data analytics for your business. So even if you have never heard about data analytics until today, I promise we will walk through this step- by-step.

By the end of this, you'll be able to think analytically and make informed business decisions. This book illustrates how EASY it is to find success by just applying a few principles.

So stop reading this description, and start reading Data Analytics for Businesses instead. Scroll up, and CLICK BUY now!

• Language: English
• Publisher: Riley Adams
• Release date: Jun 21, 2019
• ISBN: 9781393631958

Book preview

Data Analytics for Businesses 2019

Master Data Science with Optimised Marketing Strategies using Data Mining Algorithms (Artificial Intelligence, Machine Learning, Predictive Modelling and more)

by Riley Adams

© Copyright 2019 Riley Adams - All rights reserved

The content contained within this book may not be reproduced, duplicated or transmitted without direct written permission from the author or the publisher.

Under no circumstances will any blame or legal responsibility be held against the publisher, or author, for any damages, reparation, or monetary loss due to the information contained within this book. Either directly or indirectly.

Legal Notice:

This book is copyright protected. This book is only for personal use. You cannot amend, distribute, sell, use, quote or paraphrase any part, or the content within this book, without the consent of the author or publisher.

Disclaimer Notice:

Please note the information contained within this document is for educational and entertainment purposes only. All effort has been executed to present accurate, up to date, and reliable, complete information. No warranties of any kind are declared or implied. Readers acknowledge that the author is not engaging in the rendering of legal, financial, medical or professional advice. The content within this book has been derived from various sources. Please consult a licensed professional before attempting any techniques outlined in this book.

By reading this document, the reader agrees that under no circumstances is the author responsible for any losses, direct or indirect, which are incurred as a result of the use of information contained within this document, including, but not limited to, — errors, omissions, or inaccuracies.

Table Of Contents

Introduction

1  What is Data Science?

2  What is Big Data?

3  What is Data Analytics?

4  The Data Analysis Process

5  Where Do I Find My Data?

6  Introduction to Data Mining

7  Data Visualization

8  Ways to Optimize Your Business

9  How to Improve Customer Loyalty

10  How to Improve Customer Experience

11  How to Hire a Data Science Team

12  An Introduction to Predictive Modeling or Analytics

13  How to Predict Customer Behavior

14  An Introduction to Artificial Intelligence

15  Big Data and Artificial Intelligence

16  Embracing Emerging Technology

17  How does AI draw conclusions from Data?

18  Machine Learning

19  Supervised and Unsupervised Machine Learning

20  Naïve Bayes Estimation and Bayesian Networks

21  Regression Modeling

22  Clustering

23  Deep Learning and Artificial Neural Networks

24  Decision Trees

25  Association Rule Mining

26  Web Mining

27  Social Network Analysis

28  Glossary

Conclusion

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Data Analytics for Businesses 2019

Master Data Science with Optimised Marketing Strategies using Data Mining Algorithms (Artificial Intelligence, Machine Learning, Predictive Modelling and more)

Introduction

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I want to thank you for choosing this book, ‘Data Analytics for Businesses - Master Data Science for your Business with Step-by-Step Guides and Optimized Marketing Strategies using Data Mining Algorithms (Artificial Intelligence, Machine Learning, Predictive Modeling and more)’ and hope you find this book informative and interesting in your quest to learn about Data Analytics.

Big data, data science, and data analytics are revolutionizing businesses across the world. Data analytics plays an important role in a person’s life, right from the lifestyle choices that citizens make to the insights that businesses derive from the data to maximize their profits and sales. This is probably new for some businesses, especially the small businesses, but it is a skill that some employees in a firm must possess regardless of the industry. It is important for every business owner to hire a data scientist or analyst who can tell him about the progress that his business has made.

Until now there were only a few data scientists in the world who dominated the domain. It is because they are knowledgeable that they present the information in a manner that makes it difficult for a beginner to understand. They use technical terms and a lot of unnecessary jargon. Data science and analytics are not difficult to grasp, since these areas deal with using some tools to derive actionable insights from the data and use those insights to improve a business. The purpose of the fields is to enhance decision-making and also maximize processes. This will allow a business to generate value that can improve its revenue. This book covers different aspects of data analytics and data science, and also tells you how you can use these concepts to generate some insights.

There are a lot of times when data scientists get caught up with analyzing the minute aspects of data that they forget to look at the bigger picture. This is a pitfall that you have to avoid at all costs. This book presents the core purpose of most data science techniques and what you can accomplish by utilizing them.

This book has been organized in an easy to learn format. You will be able to use this book as a guide and as a reference book to improve your business. Over the course of the book, you will gather information on what data analytics is, how you can use it to improve your customer relations, and the different tools that you can use for the same. You will learn what association rule mining, big data, and artificial intelligence is, and gather information on different areas of data analytics. There are some case studies and real-world examples of how data science, data mining, and other tools improved businesses that will help you understand what you need to do for your business.

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Part I

The Fundamentals

1  What is Data Science?

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People across the world always collect data and use that data to make some analyses. In the past, it was difficult for people to collect data from devices like mobile phones and computers, but now, one can collect data from any device. Take smart watches as an example. You synchronize the smart watch with your phone. This means that one can access the data on your phone through your watch. In other words, every interaction made on social media using files or pictures generates data. You also generate data when you look for information on Google. Have you ever noticed that some advertisements pop up on your search page when you look for some information? If you pay close attention to these advertisements, you will notice that the products are similar to those that you were previously looking for or purchased.

The need to collect and use data, also called data immersion, is not a new phenomenon, but it is one that is accelerating at a rapid pace. The tiny puddles of data have become rivers and floods of data, and these data are available in different forms – structured, semi-structured, and unstructured. There are huge volumes of data that are being collected from every activity that is taking place across the globe.

You may wonder what the point of all this data is, and why we need to collect it. You may also wonder why we need to use resources to obtain this data. A few years ago, people didn’t worry about collecting data and using that data to make informed decisions. Today, the tides have turned, and data engineers across the globe are trying to identify different ways to capture, derive, collect, condense and analyze the large volumes of data that are collected. Data scientists look for a way to derive some value from the data. They analyze the data and look for different ways to improve businesses and processes.

In its truest form, data science represents the techniques used to gather insights and understandings from a set of data. It is the umbrella term that encompasses everything to do with the extraction and preparation of data, cleaning up the data so it can be interpreted, and the actual analysis of the data. One can produce a variety of insights from data analysis, and these insights can be used to improve businesses, investments, lifestyles, health, and social life. You can use data science to help you understand and predict the route that you should take to achieve your goals. You can also look at what types of obstacles you may face on your way. A Data Scientist would be responsible for discovering these insights, and forecast future trends based on previous patterns in the data.  There is a large overlap between machine learning, data science, and data analysis as they all relate to one another.  Each of these topics will be discussed in depth in this book, so don’t worry.

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The Importance of Data Science

The terms data engineering and data science are often misused. You must remember that these fields are separate and distinct domains. We will look at data engineering in the following chapters. Regardless of whether you are a data scientist or a data engineer, you will work with the following types of data:

Structured Data

Structured data is the data that are collected, collated, processed, manipulated, and analyzed using traditional relational databases.

Unstructured Data

Unstructured data are data that are generated through a variety of human activities. This data can be generated through pictures, files, texts, audio-visual files, and other types of data that cannot be categorized in a relational database.

Semi-structured data

Semi-structured data is that type of data which does not fit into any database system. This data, however, can be categorized using tags that will help you create some hierarchy and order in the data.

Most people believe that only organizations with massive funding are implementing data science technologies and methodologies to improve and optimize their business, but this is not the case. The expansion of data has given rise to a demand for insights, and this demand has embedded itself in modern culture. The need for data insights and data has now become ubiquitous since organizations and firms of all sizes have begun to recognize the competitive environment they are immersed in.

You might wonder what this has got to do with you. Firstly, you will need to understand that the culture has changed and you will need to keep up. This does not mean that you will need to go back to school and pursue a degree in computer science, data science, or statistics. The data