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Microsoft Power BI Quick Start Guide电子书

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25人正在读 | 0人评论 6.2

作       者:Devin Knight,Brian Knight,Mitchell Pearson

出  版  社:Packt Publishing

出版时间:2018-07-30

字       数:21.6万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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Develop robust, Scala-powered projects with the help of machine learning libraries such as SparkML to harvest meaningful insight Key Features *Gain hands-on experience in building data science projects with Scala *Exploit powerful functionalities of machine learning libraries *Use machine learning algorithms and decision tree models for enterprise apps Book Description Scala, together with the Spark Framework, forms a rich and powerful data processing ecosystem. Modern Scala Projects is a journey into the depths of this ecosystem. The machine learning (ML) projects presented in this book enable you to create practical, robust data analytics solutions, with an emphasis on automating data workflows with the Spark ML pipeline API. This book showcases or carefully cherry-picks from Scala’s functional libraries and other constructs to help readers roll out their own scalable data processing frameworks. The projects in this book enable data practitioners across all industries gain insights into data that will help organizations have strategic and competitive advantage. Modern Scala Projects focuses on the application of supervisory learning ML techniques that classify data and make predictions. You'll begin with working on a project to predict a class of flower by implementing a simple machine learning model. Next, you'll create a cancer diagnosis classification pipeline, followed by projects delving into stock price prediction, spam filtering, fraud detection, and a recommendation engine. By the end of this book, you will be able to build efficient data science projects that fulfil your software requirements. What you will learn *Create pipelines to extract data or analytics and visualizations *Automate your process pipeline with jobs that are reproducible *Extract intelligent data efficiently from large, disparate datasets *Automate the extraction, transformation, and loading of data *Develop tools that collate, model, and analyze data *Maintain the integrity of data as data flows become more complex *Develop tools that predict outcomes based on “pattern discovery” *Build really fast and accurate machine-learning models in Scala Who this book is for Modern Scala Projects is for Scala developers who would like to gain some hands-on experience with some interesting real-world projects. Prior programming experience with Scala is necessary.
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Title Page

Copyright and Credits

Microsoft Power BI Quick Start Guide

Packt Upsell

Why subscribe?

PacktPub.com

Foreword

Contributors

About the authors

About the reviewer

Packt is searching for authors like you

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Download the color images

Conventions used

Get in touch

Reviews

Getting Started with Importing Data Options

Getting started

Importing data

Excel as a source

SQL Server as a source

Web as a source

DirectQuery

Limitations

Live Connection

Limitations

Which should I choose?

Summary

Data Transformation Strategies

The Power Query Editor

Transform basics

Use First Row as Headers

Remove Columns

Change type

Add Column From Examples

Advanced data transformation options

Conditional Columns

Fill Down

Unpivot

Merging Queries

Appending Queries

Leveraging R

Installation and configuration

The R Script transform

M formula language

#shared

Summary

Building the Data Model

Building relationships

Editing relationships

Creating a new relationship

Working with complex relationships

Many-to-many relationships

Cross-filtering direction

Enabling filtering from the many side of a relationship

Role-playing tables

Importing the date table

Usability enhancements

Hiding tables and columns

Renaming tables and columns

Default summarization

How to display one column but sort by another

Data categorization

Creating hierarchies

Summary

Leveraging DAX

Building calculated columns

String functions – Month, Year

Format function – Month Year

Age calculation

SWITCH() – age breakdown

Navigation functions – RELATED

Calculated measures – the basics

Calculated measure – basic aggregations

Total Sales

Total Cost

Profit

Profit Margin

Optional parameters

Filter context

Calculate

Percentage of total calculation

Time intelligence

Year to Date Sales

YTD Sales (Fiscal Calendar)

Prior Year Sales

Summary

Visualizing Data

Data visualization basics

Visuals for filtering

Interactive filtering

The Slicer visual

Visualizing tabular data

The table visual

The Matrix visual

Visualizing categorical data

Bar and Column charts

Pie and Donut charts

The Treemap visual

The Scatter chart

Visualizing trend data

Line and Area charts

Combo charts

The Ribbon Chart

The Waterfall Chart

The Funnel Chart

Visualizing KPI data

The Gauge visual

The KPI visual

Visualizing geographical data

The Map visual

The Filled Map visual

The Shape Map visual

The ArcGIS Map visual

Leveraging Power BI custom visuals

Data visualization tips and tricks

Edit interactions

The Analytics pane

The Top N filter

Show value as

Summary

Digital Storytelling with Power BI

Configuring drillthrough filters

Storytelling with the Selection pane and bookmarks

Bookmarks pane

Selection pane

Summary

Using a Cloud Deployment with the Power BI Service

Deploying to the Power BI service

DATASETS

WORKBOOKS

Creating and interacting with dashboards

Creating your first dashboard

Asking your dashboard a question

Subscribing to reports and dashboards

Sharing your dashboards

Workspaces

Setting up row-level security

Scheduling data refreshes

Summary

On-Premises Solutions with Power BI Report Server

Deploying to Power BI Report Server

Securing reports

Scheduling data refreshes

Summary

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