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ANC301: Working with Salesforce Data and Dashboards in Wave Analytics

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  • 3 Days

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Course Description

In this 3-day instructor-led course, you will learn how to set up users in Wave, load and transform Salesforce and external data in Wave with JSON metadata files, and configure data security with apps and row-level security. You will also learn how to apply desktop and mobile layouts to dashboards using the Wave Dashboard Designer, modify dashboard queries by updating compact form and SAQL queries, and update metadata with an XML file.

Outline

Discovery and Planning

  • Discovery Meeting
  • Getting Logged In
  • Establishing Your Users and Development Process

 

Setting Up Users and Apps

  • Overview of User Access on the Wave Analytics Platform
  • Creating Wave Analytics Permission Sets
  • Assigning Permission Set Licenses and Permission Sets
  • Creating and Sharing Wave Analytics Apps

 

Connecting Data

  • Overview of Connecting Data
  • Data Mapping
  • Overview of the Dataflow Process
  • Designing a Dataflow
  • Loading External CSV Data into a Dataset
  • Creating and Running a Dataflow
  • Optimizing Dataflows
  • Preparing Data with Dataset Recipes
  • Additional Dataflow Transformations

 

Securing Your Data

  • Overview of Security in Wave Analytics
  • Determining Security Requirements
  • Overview of Using Predicate Filters with Salesforce Data
  • Implementing Ownership-Based Row-Level Security
  • Implementing Role-Based Row-Level Security
  • Implementing Team-Based Row-Level Security
  • Overriding Security for Implementation and Testing

 

Building Dashboards with Templates and Mobile Apps

  • Overview of Wave Analytics Dashboard Layout Templates
  • Overview of JSON for Dashboards
  • Building a Dashboard Using an Existing Layout
  • Translating Browser Dashboards to a Mobile Device
  • Creating/Updating Mobile Dashboard Layouts

 

Connecting Data Sources, Results and Selection Bindings

  • Limitations of Filters in Lenses and Dashboard in the UI
  • Creating a Dynamic Top-N Filter
  • Optimize a Multi-Dataset Dashboard by Connecting Data Sources
  • Creating a Dynamic Filter with Results Binding

 

Modifying Queries in Dashboards

  • Creating a YoY Growth Dashboard
  • Creating a Sales Delta Dashboard
  • Overview of Modifying Queries in a Dashboard
  • SAQL Overview
  • Add an External Salesforce Object to a Wave Dashboard

 

Using Extended Metadata in a Dataset

  • Overview of Extended Metadata (XMD)
  • Backing Up and Uploading a Dataset’s XMD File
  • Adding Quick Action Menus For Records in Wave
Audience

Working with data and dashboards in Wave Analytics is ideal for integration specialists who want to learn more about connecting and securing data in Wave. This course is also great for business analysts or developers interested in creating advanced dashboards.

Prerequisites

Salesforce knowledge, including: navigation, schema, security models, users, profiles, and permission sets. In addition, students should be proficient in Wave data exploration, building Wave dashboards with the UI, and basic JSON.

What You Will Learn

When you complete this course, you will be able to:

  • Determine your user, data, and security requirements, and establish a development process.
  • Set up apps and control what users can do in Wave Analytics by assigning them permission set licenses, permission sets, and app permissions.
  • Load an external CSV file to Wave, configure data replication schedules, and create and run JSON dataflow files to load Salesforce data and combine it with data from existing datasets.
  • Understand and implement data security in Wave and override security for implementation and testing.
  • Apply a Wave Analytics layout template to a dashboard and create a mobile dashboard layout.
  • Explain the limitations of filters in lenses and dashboards, and overcome these through UI settings and modifying the compact form query.
  • Explain the process of dashboard queries and modify a SAQL query to meet many analytic requirements.
  • Create and upload an XMD file to modify a dataset’s metadata.