Learning Einstein Analytics E-Book

Santosh Tukaram Chitalkar

• Herausgeber: Packt Publishing
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 161

Veröffentlichungsjahr: 2018

Beschreibung

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.

Leseprobe

Learning Einstein Analytics

Unlock critical insights with Salesforce Einstein Analytics

Santosh Tukaram Chitalkar

BIRMINGHAM - MUMBAI

Learning Einstein Analytics 

Copyright © 2018 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Commissioning Editor: Richa TripathiAcquisition Editor: Karan SadawanaContent Development Editor: Zeeyan PinheiroTechnical Editor: Vibhuti GawdeCopy Editor: Safis EditingProject Coordinator: Vaidehi SawantProofreader: Safis EditingIndexer: Francy  PuthiryGraphics: Jason MonteiroProduction Coordinator: Arvindkumar Gupta

First published: January 2018

Production reference: 1250118

Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK.

ISBN 978-1-78847-576-1

www.packtpub.com

This is my first book and I want to dedicate my humble efforts to my family. Mom, Dad, and my wife Anuradha, who have never complained about my workaholic nature. I could write this book only because of their love and support. A special thanks to my mentor Rohit Arora, who believed in me, pushed me, and helped me find my passion for technology. Only he believed in my ability and to achieve success to this extent. I feel blessed to have such special people around me.   

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Contributors

About the author

Santosh Tukaram Chitalkar has been working on the Salesforce platform for over five years. He currently works for Capgemini as a Salesforce consultant. During his time at Capgemini, he has worked on various Salesforce projects, which include the implementation of sales SFO, inline Visualforce pages for sales and service assets, and renewal processes. 

He has also developed products for AppExchange such as FieldRecon. In his free time, he loves writing about Salesforce Einstein Analytics on his blog Pinakin Technology.

About the reviewer

Abhishek Tripathi has more than 5 years of experience with the Salesforce platform. He is a Salesforce certified application architect and has 16 Salesforce certifications. He is a technical blogger, posting tips and tricks for Salesforce to help others in the Salesforce community.

Abhishek has worked with some giants with Salesforce, such as PwC US, Coca-Cola, Tquila (acquired by Accenture), and Accenture.

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Table of Contents

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

Preface

Einstein Analytics, formally known as Wave Analytics, is a cloud-based platform that connects data from multiple sources and explores it to uncover insights. It empowers sales representatives, marketers, and analysts with insights to make customer interactions smarter; without building mathematical models. You will learn how to create applications, lenses, and dashboards, and how to share those dashboards with other users.

This book starts off by explaining the fundamental concepts, such as lenses, steps, and measures; it then sets you up with the Einstein Analytics platform. The book then moves on to creating an application—you will learn how to create datasets and dashboards, and the different ways of importing 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 the recent advancements in Einstein, which include machine learning constructs and getting predictions for events. By the end of this book, you will be proficient in Einstein Analytics, getting insights faster and understanding your customers in a better way.

Who this book is for

This book is for beginners who want to explore this AI-powered business intelligence software by Salesforce. Prior knowledge of the Salesforce platform is required.

What this book covers

Chapter 1, Getting Started with Einstein Analytics, gives an overview of Einstein Analytics. It also covers the concepts and terminologies used in Einstein Analytics. We will sign up to Salesforce special developer edition in this chapter.

Chapter 2, Setting Up Einstein Analytics, covers creating and understanding users and user types. We are going to learn how to create and assign permission sets.

Chapter 3, Say Hello to Einstein, covers building your first lenses and dashboards.

Chapter 4, Diving Deep into Einstein Analytics, covers creating a simple summary dashboard and understanding quota, dataflow, and dataflow scheduling. This chapter also explains Classic Designer Dashboard and Wave Designer Dashboard. In addition, it will cover faceting and declarative binding.

Chapter 5, Einstein for Sales, explains how to create an executive dashboard. While creating dashboards, you will learn about creating static steps, selection, and result binding.

Chapter 6, Einstein at Your Service, covers creating a service dashboard. While creating a dashboard, you will learn about the dashboard inspector and connecting your static step with dashboard components.

Chapter 7, Security and Sharing in Einstein Analytics, is an important chapter as it covers security and sharing in Einstein Analytics. This chapter covers Salesforce data access, data sharing, and data security, while also taking you through adding row-level security to a dataset.

Chapter 8, Recipe in Einstein, covers how to create a recipe. When working with data, there are times when we realize that we have added a lot of unnecessary fields and data, and we need to remove them. We also need to add new fields to the same dataset if we have missed a required field or, if we need to add a new one in the future. This is called data preparation and it is easier with Einstein Analytics.

Chapter 9, Embedding Einstein Dashboards, is all about Einstein Analytics providing the flexibility to embed dashboards within other Salesforce environments. It covers all the different methods of embedding dashboards and adding filters to embedded dashboards.

Chapter 10, Advanced Technologies in Einstein Analytics, covers advanced technologies or methods in Einstein Analytics. This chapter also covers the use of JSON, XMD, and SAQL for working on complex solutions.

Chapter 11, Machine Learning and Deep Learning, gives an overview of machine learning, deep learning, and NLP. You will also see the implementation of all these technologies in Einstein Analytics: Einstein Language and Einstein Sentiment.

To get the most out of this book

Learning Einstein Analytics is for all Salesforce CRM techies who wish to learn this platform. We have written this book keeping beginners in mind, but it is important that you are familiar with Salesforce CRM. Basic concepts and admin knowledge of Salesforce is required.

Einstein Analytics is a cloud-based platform; hence, you only need a system with a good internet connection to get started with this book. The first two chapters of this book explain the basic concepts and terminologies of Einstein Analytics and its setup. In Chapter 3, Say Hello to Einstein, Chapter 4, Diving deep into Einstein Analytics, Chapter 5, Einstein for Sales, and Chapter 6, Einstein at Your Service, the book explains the platform in detail and uses hands-on tutorials to explain how it works. We have taken a few business requirements from a hypothetical organization called Anutosh Infotech and we'll be building sales and service dashboards for that organization. While creating these dashboards, we will go through every relevant concept, feature, and implementation. The last five chapters explain how to build a complex solution in Einstein Analytics and give an overview of the advanced technologies and features provided by the Einstein platform.  

Download the example code files

You can download the example code files for this book from your account at www.packtpub.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

Log in or register at

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Select the

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Enter the name of the book in the

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The code bundle for the book is also hosted on GitHub athttps://github.com/PacktPublishing/Learning-Einstein-Analytics. We also have other code bundles from our rich catalog of books and videos available athttps://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: http://www.packtpub.com/sites/default/files/downloads/LearningEinsteinAnalytics_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Create a report on an account, export it to a CSV file named Account_data.csv, and save it to your local drive."

A block of code is set as follows:

[ "Account.BillingCountry",

"{{column(Static_Country_1.selection, [\"value\"]).asObject()}}",

"in"

],

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

[default]exten => s,1,Dial(Zap/1|30)exten => s,2,Voicemail(u100)

exten => s,102,Voicemail(b100)

exten => i,1,Voicemail(s0)

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Click on Enable Analytics, as shown in the following screenshot."

Warnings or important notes appear like this.

Tips and tricks appear like this.

Get in touch

Feedback from our readers is always welcome.

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Getting Started with Einstein Analytics

The evolution of technology has increased to a new level in the last five years and Customer Relationship Management (CRM) is an integral part of it. CRM has helped companies manage and analyze customer interactions and data throughout the customer life cycle, with the goal of improving business relationships with customers. But the analysis of data, managing it, and making business decisions based on that customer data is becoming more and more challenging because of the social media, internet, and technology.