This document announces an Einstein Analytics presentation by Rikke Hovgaard on October 27, 2018 as part of the Farmington Hills Salesforce Developer User Group. The presentation will cover topics such as SAQL, comparing datasets, and time series data in Einstein Analytics. It provides details on the speaker, agenda, and how to access the Zoom meeting for the presentation.

1. Farmington Hills
Salesforce Developer User Group
Apex Hours
Einstein Analytics
#SalesforceApexHours #FarmingtonHillsSFDCDug
Speaker
Date
Venue/Link
Rikke Hovgaard, Amit Chaudhary
Saturday, OCT 27, 2018 10:00 AM EST ( 7:00 PM IST)
https://zoom.us/j/405325057

2. Who am I ?
Amit Chaudhary (Salesforce MVP)
• Active on Salesforce Developer Community
• Blogging at http://amitsalesforce.blogspot.in/
• Co-Organizer of – FarmingtonHillsSFDCDug
• Follow us @Amit_SFDC or @ApexHours
#SalesforceApexHours #FarmingtonHillsSFDCDug

3. Our Speaker
Rikke Hovgaard
Einstein Analytics Solution Architect with Salesforce
(ACE team)
User Group Leader
Blogging at www.salesforceblogger.com
Follow me on Twitter @HovsaRikke
#SalesforceApexHours #FarmingtonHillsSFDCDug

4. ▶ Data, Data, Data
▶ SAQL – Compare Table
▶ SAQL – 2 datasets
▶ SAQL Timeseries
▶ Other Steps
▶ Bindings
AGENDA
#SalesforceApexHours #FarmingtonHillsSFDCDug

5. #FarmingtonHillsSFDCdug #SalesforceApexHours
Apex Hours
This presentation may contain forward-looking statements that involve risks, uncertainties, and assumptions. If any such uncertainties materialize or if any of the assumptions
proves incorrect, the results of salesforce.com, inc. could differ materially from the results expressed or implied by the forward-looking statements we make. All statements other
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financial items and any statements regarding strategies or plans of management for future operations, statements of belief, any statements concerning new, planned, or
upgraded services or technology developments and customer contracts or use of our services.
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and services, our new business model, our past operating losses, possible fluctuations in our operating results and rate of growth, interruptions or delays in our Web hosting,
breach of our security measures, the outcome of any litigation, risks associated with completed and any possible mergers and acquisitions, the immature market in which we
operate, our relatively limited operating history, our ability to expand, retain, and motivate our employees and manage our growth, new releases of our service and successful
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Forward-Looking Statement

6. #FarmingtonHillsSFDCdug #SalesforceApexHours
Apex Hours
Data, Data, Data
Without Data Sync With Data Sync

7. #FarmingtonHillsSFDCdug #SalesforceApexHours
Apex HoursDataflow
At minimum has
these
plus
Combine/create
any based on these
SQL Oracle
External Data/ ETL
tools/APIs
Data
Lake
SFDC Objects
Data Landscape - With Connect
CSV
(gets added to Dataflow
dependent on DF)
External on it’s own schedule
Other SFDC
Orgs
Redshift, Other
Connectors
Marketing Cloud
CSV - Manual
Connect
Trend Report Data in Analytics
Dataset Builder
Data Recipes (not
part of Dataflow)
Start from or
combine from any
of these dataset
Recipes

8. Apex Hours
#FarmingtonHillsSFDCdug #SalesforceApexHours
Dataflow + Recipe
▶ What: tools to transform and register datasets
▶ Recipe very accessible and user friendly, dataflow more
powerful
▶ Example: create a compute expression
▶ Try it yourself:
▶ http://www.salesforceblogger.com/2018/04/24/my-most-used-computeexpression/

9. #FarmingtonHillsSFDCdug #SalesforceApexHours
Apex Hours
Let’s look at the
Data Manager

10. #FarmingtonHillsSFDCdug #SalesforceApexHours
Apex Hours
Technical Jargon - The Dashboard
Sales Wave App
Service Wave App
Event Monitoring App
Dataset
XMD
Dataset
XMD
Chart type/properties
+
Query
Chart type/properties
+
Custom Query (SAQL)
+
JSON
Dashboard
SFDC/
oData
SOQL/ApexSteps
Dbrd aka
asset XMD
*NEW (summer18) for
conditional formatting and
related - API accessible only

11. Apex Hours
#FarmingtonHillsSFDCdug #SalesforceApexHours
SAQL
▶ What: Salesforce Analytics Query Language – what is used at
run time.
▶ Use when you more complexity. Start out building as much as
possible in UI then switch to SAQL if needed.
▶ Example: YTD comparison, two datasets, timeseries
▶ Try it yourself:
▶ http://www.salesforceblogger.com/2017/11/20/ytd-comparison-with-compare-
tables/
▶ http://www.salesforceblogger.com/2018/10/16/a-look-to-the-future-with-timeseries/

12. #FarmingtonHillsSFDCdug #SalesforceApexHours
Apex Hours
Let’s do some SAQL

13. Apex Hours
#FarmingtonHillsSFDCdug #SalesforceApexHours
SOQL Steps
▶ What: A different step type that use data directly from
Salesforce
▶ Good for real time – but has an impact.
▶ Example: Logged in user
▶ Try it yourself:
▶ http://www.salesforceblogger.com/2017/06/27/how-to-filter-dashboard-by-logged-
in-user/

14. Apex Hours
#FarmingtonHillsSFDCdug #SalesforceApexHours
Bindings
▶ What: A way to link steps together or with widgets.
▶ Example: Dynamic Gauge, Dynamic Groupings etc.
▶ Try it yourself:
▶ http://www.salesforceblogger.com/2017/06/19/how-to-make-your-gauge-chart-
dynamic/
▶ http://www.salesforceblogger.com/2017/02/28/the-power-of-static-steps/
▶ http://www.salesforceblogger.com/2017/02/23/toggle-selector-for-map-types-in-a-
wave-dashboard/

15. #FarmingtonHillsSFDCdug #SalesforceApexHours
Apex Hours
Let’s do it

16. Apex Hours
#FarmingtonHillsSFDCdug #SalesforceApexHours
That’s all folks…
▶ https://trailblazercommunitygroups.com/events/details/salesfor
ce-farmington-mi-developers-group-presents-salesforce-apex-
hours-einstein-analytics-part-2#/
▶ Embarking on your EA journey?
http://www.salesforceblogger.com/2018/02/05/embarking-on-
your-einstein-analytics-journey-start-here/
▶ Remember to create the Learning Adventure App

17. Apex Hours
#FarmingtonHillsSFDCdug #SalesforceApexHours
Follow Farmington Hills SFDC Developer Group
Twitter Hashtag
#FarmingtonHillsSFDCDug #SalesforceApexHours
Meetup.com
https://trailblazercommunitygroups.com/farmington-mi-
developers-group/
YouTube