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Data Science with Microsoft SQL Server 2016 Free eBook

Data Science with Microsoft SQL Server 2016 – R is one of the most popular, powerful data analytics languages and environments which is used by data scientists. Actionable business data is often stored in Relational Database Management Systems, and one of the most widely used RDBMS is Microsoft SQL Server. Much more than a database server, it’s a rich eco-structure with advanced analytic capabilities. Microsoft SQL Server R Services combine these environments, allowing direct interaction between the data on the RDBMS and the R language, all while preserving the security and safety the RDBMS contains. In this book, you’ll learn how Microsoft has combined these two environments, how a data scientist can use this new capability and practical, hands-on examples of using SQL Server R Services to create real- world solutions. Download free ebook Data Science with Microsoft SQL Server 2016.

Data Science with Microsoft SQL Server 2016 Free eBook

Data Science with Microsoft SQL Server 2016

Data Science with Microsoft SQL Server 2016 Free eBook

Contents

Introduction

  • How this book is organized
  • Who this book is for
  • Acknowledgements
  • Free ebooks from Microsoft Press
  • Errata, updates, & book support
  • We want to hear from you
  • Stay in touch

Chapter 1: Using this book

  • For the data science or R professional

Solution example: customer churn
Solution example: predictive maintenance and the Internet of Things
Solution example: forecasting

  • For those new to R and data science

Step one: the math
Step two: SQL Server and Transact-SQL
Step three: the R programming language and environment

Chapter 2: Microsoft SQL Server R Services

  • The advantages of R on SQL Server
  • A brief overview of the SQL Server R Services architecture

SQL Server R Services

  • Preparing to use SQL Server R Services

Installing and configuring
Server
Client

  • Making your solution operational

Using SQL Server R Services as a computer context
sing stored procedures with R Code

Chapter 3: An end-to-end data science process example

  • The data science process: an overview
  • The data science process in SQL Server R Services: a walk-through for R and SQL developers

Data and the modeling task
Preparing the infrastructure, environment, and tools
Input data and SQLServerData object

  • Exploratory analysis

Data summarization
Data visualization

  • Creating a new feature (feature engineering)

Using R functions
Using a SQL function

  • Creating and saving models

Using an R environment
Using T-SQL
Model consumption: scoring data with a saved model

  • Evaluating model accuracy
  • Summary

Chapter 4: Building a customer churn solution

  • Overview

Understanding the data

  • Building the customer churn model

Step-by-step

  • Summary

Chapter 5: Predictive maintenance and the Internet of Things

  • What is the Internet of Things?
  • Predictive maintenance in the era of the IoT
  • Example predictive maintenance use cases

Before beginning a predictive maintenance project

  • The data science process using SQL Server R Services

Define objective
Identify data sources
Explore data
Create analytics dataset
Create machine learning model
Evaluate, tune the model
Deploy the model

  • Summary

Chapter 6: Forecasting

  • Introduction to forecasting

Financial forecasting
Demand forecasting
Supply forecasting
Forecasting accuracy
Forecasting tools

  • Statistical models for forecasting

Time–series analysis
Time–series forecasting

  • Forecasting by using SQL Server R Services

Upload data to SQL Server
Splitting data into training and testing
Training and scoring time–series forecasting models
Generate accuracy metrics

  • Summary
  • About the authors

Data Science with Microsoft SQL Server 2016 Free eBook

Download free Data Science with Microsoft SQL Server 2016 and learn to install, configure, and use Microsoft’s SQL Server R Services in data science projects.

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