Getting Started with Salesforce Einstein Analytics
A Beginner’s Guide to Building Interactive Dashboards
To my wife Novida Lunardi, who always inspired, supported, and encouraged me to make this book a reality.
In the contemporary enterprise, data now drives business. But data in itself is not of much use. You have to be able to use it to drive business improvements for it to actually matter. Data is just the raw material – you need tools and a strategy to get the most out of it. Additionally, in the age of AI, the dashboard is getting transformed into an intelligent experience. In such an experience, users aren’t spending all their time searching for the data they need. That equation is flipped: the relevant data finds them, and they then use it in a business process that has a narrative element to make important business decisions.
However, if you stocked a kitchen with every advanced cooking tool but then put someone who does not have the skills to even boil water in charge of making a four-course meal, you wouldn’t expect great results.
This book will help you become a master chef of the insights cuisine. This book gives everyone the power to build intelligent experiences.
For a generation, analytics dashboards were clumsy and monolithic and mostly told us what had already happened. Today, that’s no longer the case. With the help of this book, you will learn how to elevate it to a whole new level as a strategic tool and design intelligent experiences for the user such that the user walks away with the knowledge of what happened, why it happened, what will happen, and what they should do about it. In technical terms, this boils down to descriptive, diagnostic, predictive, and prescriptive analytics. The key here is complete. Answers to all the questions. Because the “what” and the “why” give context. Then “what will happen” and “what should I do about it” answers give guidance. “Context plus guidance, when delivered as narrative explanations infused in the business process such that data finds you, is equal to an intelligent experience.”
Johan Yu, Salesforce MVP in Asia, has a deep understanding and knowledge of Salesforce Einstein Analytics technology, but he is a trailblazer. Not just a master of the technology but a pioneer of new ideas, driving transformation. He is a leader in the Salesforce community, and beyond that, his ideas have also directly influenced numerous product capabilities in Einstein Analytics.
This book is aimed at Salesforce administrators, business users, and managers who use Salesforce for their daily work. However, Einstein Analytics is not just for Salesforce. So, any business or data analyst in the world will gain valuable skills that will empower them to drive a data-driven transformation in their organization.
Ketan Karkhanis
SVP Product and GM, Einstein Analytics at Salesforce
Salesforce is known as the most user-friendly enterprise application; over more than 20 years, it has been evolved from just a simple CRM on the cloud to comprehensive applications for Sales, Service, Marketing, and so on, including Analytics.
One of the features liked the most by Salesforce users is the report and dashboard; each user with permission enabled will be able to build and edit report and dashboard on their own. Furthermore, the result of the report is almost instant. Users will be able to sort, group, add subtotal, add bucket fields, and add summary fields and chart to the report. Salesforce dashboard is built on top of reports created, which serve as the data source for each dashboard component.
Salesforce report and dashboard serve well as a simple operation analytics tool, but it is not designed to work with large amounts of data, it is not designed as a data analysis and exploration tool, and it does not support connecting to the external data source. Therefore, Salesforce introduces Einstein Analytics.
Einstein Analytics is a cloud-based analytics tool; it is tightly connected to the Salesforce platform, but it is also able to get external data into the platform, including from multiple Salesforce org.
Einstein Analytics is built for data exploration, so performance is one of the key benefits offered by Einstein Analytics because the datasets are stored within Einstein Analytics, not in Salesforce platform. We can enable one-way data sync from Salesforce to Einstein Analytics, but this does not mean all data from Salesforce will sync into Einstein Analytics, but only objects and fields used in the dataflow.
As an Einstein Analytics dashboard builder , you need to prepare the dataset, and this dataset will be used as the data source for dashboards. You can use multiple datasets within a dashboard; then you can link the datasets with a common value.
To build datasets, normally you need to design a dataflow. In the dataflow, you architect how the data flows, from extracting data from Salesforce or from the existing dataset in Einstein Analytics, including dataset synced from the external system or from other Salesforce org. You are free to use your own creativity to transform the data in the dataflow, using transformation nodes provided to get data, augment data, filter, append, create new fields based on criteria, and store the transformed data into datasets. You can schedule dataflow to run every hour, daily, or weekly.
Einstein Analytics also offers recipe to enrich the existing dataset with other datasets. You also use a recipe to analyze data. Same as a dataflow, you can schedule recipe too.
Another option to get Salesforce data into Einstein Analytics is to use trend. Data will be pushed into Einstein Analytics periodically; this is most useful when you want to build trending, another use case to use trend because you need to get fields that exist in Salesforce reporting only.
To offer our users with more flexibility in exploring dashboard, we can implement binding , so the dashboard widget is no longer static, for example, using the same chart and giving options for users to change the grouping or showing a line in a chart based on other numbers.
Once the dashboard is built, another cool feature is the ability to facet and broadcast across widgets with the same dataset, or linked datasets. This feature is very helpful for the user in analyzing data. Users also will be able to explore widget to the lens and save it for future usage, annotate widget, and set notifications when widget reaches a number that the users set.
Security is always required in an analytics tool; Einstein Analytics offers capabilities to make the dashboard only visible to particular users. Dashboard builder is also able to set row-level security with security predicate, and also security inheritance to inherit records visibility from Salesforce rules.
To start learning Einstein Analytics, you need to have an org.; if your company has not purchased Einstein Analytics, you can register for a free Trailhead DE org.
Thank you for purchasing this book; if you read till the end of the book and follow the hands-on provided, you should have absorbed all features offered by Einstein Analytics and knowledge to build interactive dashboards for your company or your clients. Happy learning!
Chris Varr : My boss, without the wonderful opportunity given to learn Einstein Analytics, this book would never exist. Thank you for the support and belief in me #bestbossever.
My teammates: Eileen , Adrian , Swapna , Masako , Jesus , and Terry , you guys are the best; it is a pleasure to work with all of you.
Sayantani Mitra : One of the most knowledgeable #datatribe, thank you for your sharing, help, and input as a technical reviewer of this book.
Peter Lyons : You teach thousands of people learning Einstein Analytics with your YouTube videos; you are rad, truly an MVP!
Jennifer Shier : An amazing trailblazer and a very positive person, thank you for getting me into the #datatribe clan.
Rita Fernando and Susan McDermott : Thank you Rita and Susan, for every support provided in making this book become a reality.
Ketan Karkhanis : Thank you for the foreword and building such a great product, so we can build intelligence dashboards easily.
David Gibbons : Thank you for the support to Einstein Analytics trailblazers community, and yeah #AnalyticsChampion rocks!
Table of Contents
About the Author and About the Technical Reviewer
About the Author
has more than 20 years of experience working in the IT sector across MNCs and at a leading Salesforce consulting company in the Asia-Pacific region. He has spent more than 14 years working with Salesforce technology, starting his career as a developer, team leader, and technical manager, among many other challenging roles. Based in Singapore, Johan holds 13X Salesforce certifications, ranging from Administrator to Architect/Designer certifications, and Einstein Analytics and Discovery Consultant. In his spare time, he enjoys writing blogs and answering questions in the Salesforce Trailblazer Community. In May 2014, Johan became the first Salesforce MVP from Southeast Asia. He is also the leader of the Salesforce Singapore User Group and is keen to help members solve issues related to configuration, implementation, and adoption until more technical issues arrive.
About the Technical Reviewer
is a Salesforce Analytics Champion specializing in data-driven descriptive and predictive analytics for commercial real estate with actionable insights using Einstein Analytics and Discovery. She takes a keen interest in analyzing and deriving various insights from large datasets. She maintains a blog (on Einstein Analytics ( https://medium.com/einstein-analytics ) and is the current organizer of the Einstein Analytics Chicago User Group. Sayantani has a Masters in Applied Urban Science and Informatics from New York University and works as a Data Scientist and Einstein Analytics Specialist in Chicago.