Data Analytics: Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life

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Introduction
How do you define the success of a company? It could be by the number of
employees or level of employee satisfaction. Perhaps the size of the
customer base is a measure of success or the annual sales numbers. How
does management play a role in the operational success of the business?
How critical is it to have a data scientist to help determine what’s
important? Is fiscal responsibility a factor of success? To determine what
makes a business successful, it is important to have the necessary data about
these various factors.
If you want to find out how employees contribute to your success, you will
need a headcount of all the staff members to determine the value they
contribute to business growth. On the other hand, you will need a bank of
information about customers and their transactions to understand how they
contribute to your success.
Data is important because you need information about certain aspects of
your business to determine the state of that aspect and how it affects overall
business operations. For example, if you don’t keep track of how many
units you sell per month, there is no way to determine how well your
business is doing. There are many other kinds of data that are important in
determining business success that will be discussed throughout this book.
Collecting the data isn’t enough, though. The data needs to be analyzed and
applied to be useful. If losing a customer isn’t important to you, or you feel
it isn’t critical to your business, then there’s no need to analyze data.
However, a continual lack of appreciation for customer numbers can impact
the ability of your business to grow because the number of competitors who
do focus on customer satisfaction is growing. This is where predictive
analytics becomes important and how you employ this data will distinguish
your business from competitors. Predictive analytics can create strategic
opportunities for you in the business market, giving you an edge over the
competition.
The first chapter will discuss how data is important in business and how it
can increase efficiency in business operations. The subsequent chapters will
outline the steps and methods involved in analyzing business data. You will

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gain a perspective on techniques for predictive analytics and how it can be
applied to various fields from medicine to marketing and operations to
finance.
You will also be presented with ways that big data analysis can be applied
to gaming and retail industries as well as the public sector. Big data analysis
can benefit private businesses and public institutions such as hospitals and
law enforcement, as well as increase revenue for companies to create a
healthier climate within cities.
One section will focus on descriptive analysis as the most basic form of
data analysis and how it is necessary to all other forms of analysis – like
predictive analysis – because without examining available data you can’t
make predictions. Descriptive analysis will provide the basis for predictive
and inferential analysis. The fields of data analysis and predictive analytics
are vast and complex, having so many sub-branches that add to the
complexity of understanding business success. One branch, prescriptive
analysis, will be covered briefly within the pages of this book.
The bare necessities of the fields of analytics will be covered as you read
on. This method is being employed by a variety of industries to find trends
and determine what will happen in the future and how to prevent or
encourage certain events or activities. The information contained in this
book will help you to manage data and apply predictive analytics to your
business to maximize your success.

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