Hi All, hope you all are enjoying the tutorial series of Einstein Analytics. In the previous tutorial, we learned how we can create Application, Dashboards, Datasets, Lenses, and Steps into Einstein Analytics. So, on Day 3 we will learn the below topics.

  • When to use which chart for analytics.
  • Create Dataset using CSV File.
  • Introduction to SAQL.

For those who have not gone through with the previous tutorials please visit the same so that you can come on the same track and understand the things in easy and better way. Here is the Link for the previous posts.

When to use which chart for analytics: – It’s very important to understand which chart is suitable whenever we wanted to analyze the data. Below are two images which illustrate when we should for which chart.

Create Dataset using CSV File: – In many cases,  Company has some legacy data that resides outside the Salesforce ORG and they do not want to import the old data into Salesforce. So, in this case, we can use. CSV file and import the same into Analytics to analyze the data.

Introduction to SAQL: – Salesforce Analytics Query Language Analytics Cloud uses SAQL behind the scenes in lenses, dashboards, and explorer to gather data for visualizations. Users don’t write SAQL statements, they use the UI and the app makes the queries. SAQL loads the dataset, perform the operations on it and generate the output dataset.

When to use SAQL: – 

Developers can write SAQL to directly access Analytics Cloud data via:

  • Wave REST API
  • Build your own app to access and analyze Analytics Cloud data or integrate data with existing apps.
  • Dashboard JSON
  • Create advanced dashboards. A dashboard is a curated set of charts, metrics, and tables.


q = load "0Fcc00000004DI1CAM/0Fd500000004F4sCAE";
q = group q by all;
q = foreach q generate count() as 'count', unique('OL.Helpful') as 'unique_OL.Helpful';
limit q 2000;

Basic SAQL Elements: – 

  • Statements: – Each SAQL is made of the statement and each statement is a combination of keywords(filter, group, offset and etc.), identifiers and literals.
    • load: – SAQL query always starts with the load statement which loads in the input dataset.
    • filter: – to filter out the records from the dataset. filter a by Year in [‘2017′,’2018’];
    • foreach
    • group and cogroup
    • union
    • order
    • limit
    • offset
  • Keywords: – Keywords are case-sensitive and must be lowercase. For Example, filter, group, offset and etc.
  • Identifiers: – SAQL identifiers are case-sensitive. They can be enclosed in single quotation marks (‘) or no quotation marks.
  • Literals: –
    • Number Literals
    • String Literals

Refer the video

Thanks for reading 🙂

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If you have any questions/query/suggestions please come up in the comment section or you can tweet me @cloudyamit

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