Learning Einstein Analytics

图书信息

作者	Santosh Tukaram Chitalkar
出版社	Packt Publishing
ISBN	9781788478182
出版时间	2018-01-29
字数	16.4万
分类	进口书,外文原版书,电脑,网络

读书简介

Learn to confidently setup and create app, lenses, dashboards using Salesforce Einstein Analytics. About This Book ? Explore Einstein analytics on desktop as well as mobile platforms ? Turn data into smarter sales with Einstein Analytics for Sales ? Visualize your data with preloaded as well as customized dashboards Who This Book Is For This book is for data scientists, business users, developers who want to explore business data using the Salesforce Einstein Analytics. Knowledge of the Salesforce platform is required. What You Will Learn ? Create app, lenses, and dashboards using Einstein. ? Visualize data utilizing all the widgets available with Einstein. ? Understand Einstein for Sales, Service, and Marketing separately. ? Use Data monitoring tools to monitor data flow and system jobs. ? Abstract machine learning constructs and make predictions on events In Detail Salesforce Einstein analytics aka Wave Analytics is a cloud-based platform which connects data from the multiple sources and explores it to uncover insights. It empowers sales reps, marketers, and analysts with the insights to make customer interactions smarter, without building mathematical models. You will learn to create app, lenses, dashboards and share dashboards with other users. This book starts off with explaining you fundamental concepts like lenses, step, measures and sets you up with Einstein Analytics platform. We then move on to creating an app and here you will learn to create datasets, dashboards and different ways to import data into Analytics. Moving on we look at Einstein for sales, services, and marketing individually. Here you will learn to manage your pipeline, understand important business drivers and visualize trends. You will also learn features related to data monitoring tools and embedding dashboards with lightning, visualforce page and mobile devices. Further, you will learn advanced features pertaining to recent advancements in Einstein which include machine learning constructs and getting predictions for events. By the end of this book, you will become proficient in the Einstein analytics, getting insights faster and understanding your customer in a better way. Style and approach The book takes a pragmatic approach showing you installation of Salesforce Einstein Analytics, predictive analysis and applications of AI.

目录

Title Page

Copyright and Credits

Learning Einstein Analytics

Dedication

Packt Upsell

Why subscribe?

PacktPub.com

Contributors

About the author

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 Einstein Analytics

Einstein Analytics

Introduction to Einstein Analytics

Terminologies in Einstein Analytics

Concepts - terminologies

Datasets

Measures

Dimensions

Dates

Dataset builder

Lenses

Visualizations

Dashboards

Designers

Dashboard JSON

Explorer

Apps

Transformation

SAQL

Predicate

Metadata files

Dataflow

Dataflow jobs

Summary

Setting Up Einstein Analytics

The Einstein platform setup process

Enabling Analytics

User types

Creating permission sets

Assigning a Einstein Analytics permission set to users

Einstein limits

Summary

Say Hello to Einstein

Data preparation

Creating your first dataset

Updating datasets

Creating your first dashboard

Creating lenses

Creating your first lens

Adding lenses to dashboards

Creating a Bar chart

The Donut charts

Compare Table

Stacked Bar chart

Dashboard customization

Creating your first Einstein Analytics application

Set Smart Notification

Keyboard shortcuts for Wave dashboards and lenses

Summary

Diving Deep into Einstein Analytics

Quota, dataflow, and data manager

Creating a quota dataset

Dataflows in Einstein Analytics

Dataflow

Transformations

augment

sfdcDigest

sfdcRegister

Required permissions

Configuring a dataflow

Running a dataflow

Scheduling the dataflow

Einstein dashboards

Differences between Wave Dashboard Designer and Classic Designer

Creating a dashboard using Wave Dashboard Designer

The General option under LAYOUT settings

Displaying the top 10 opportunities in the Bar chart

Donut charts for the top five opportunity owners

Adding numbers for KPI

Closed Won and Closed Lost opportunity amounts

Listing widgets by Opportunity Type, Role Name, and Opportunity Owner

Owner Role Name and Opportunity Owner lists

The Range filter widget

What is faceting?

Connecting datasources

Setting initial values to filters

Creating a dashboard using Classic Designer

Creating your first chart in Classic Designer

Donut charts for Opportunities by Industry

Funnel chart for Opportunities by Stage

Converting your dashboard to a Wave Dashboard Designer

Summary

Einstein for Sales

Executive dashboard for a sales team

Expected revenue KPIs

Actual revenue earned

The static step

Bindings in Einstein

Selection binding

Data selection functions

Data serialization functions

Result binding

Formatting derived measures or fields

Funnel charts for Opportunities by Stage

Sales Cloud Einstein

Setting up Sales Cloud Einstein

Creating a permission set

Assigning permission sets to users

The Sales Analytics Apps license

Creating a Sales Analytics App

Summary

Einstein at Your Service

Service dashboards

Customer service dashboard – VP

Dashboards and lenses

Creating list filters

Static steps for country

Map chart for BillingCountry

Fine-tuning maps using map properties

The BillingCountry and BillingState tables

Connecting static steps as filters to the map and table

Adding key matrics to the dashboard using a Number widget

The Timeline chart for case count by AccountSources

Broadcast faceting

Optimizing dashboard performance

Einstein custom actions

What is a Salesforce action?

Summary

Security and Sharing in Einstein Analytics

Einstein Security

Salesforce data security

Sharing mechanism in Einstein

Mass-sharing the application

Row-level security

Security predicates for the record owner

Summary

Recipe in Einstein

Dataset recipe

What is a data recipe?

Creating a recipe

Running a recipe

Adding data

The column profile option

The ATTRIBUTES tab

The NAVIGATOR tab

Additional transformation suggestions

The bucket field

The formula field

The scheduling recipe

Exporting datasets using datasetUtils

Summary

Embedding Einstein Dashboards

Embedding dashboards

Embedding dashboards on the detail page in Salesforce Classic

Embedding the dashboard in Lightning

Lightning page attributes in embedding a dashboard

Embedding the dashboard in Visualforce Pages

Embedding dashboards to websites and web applications

Embedding and sharing dashboards in communities

Enabling Communities

Enabling Analytics for Communities

Embedding dashboards using Community Builder or Visualforce Pages

The Enable sharing with Communities option

Summary

Advanced Technologies in Einstein Analytics

Salesforce Analytics Query Language

Using SAQL

Using foreach in SAQL

Using grouping in SAQL

Using filters in SAQL

Using functions in SAQL

Extended metadata in Analytics

Downloading the XMD for the dataset

Configuring XMD

Uploading XMD in the dataset

Dashboard JSON in Analytics

Summary

Machine Learning and Deep Learning

AI in Einstein Analytics

Machine learning

Deep learning

Natural-language processing

Einstein Intent

Einstein Sentiment

Summary

Other Books You May Enjoy

Leave a review - let other readers know what you think