1.
Add Historical Analysis of
Operational Data with Fivetran
Automated Data Integration

2.
Introductions
Elesh Mistry
Fivetran, Senior Sales Engineer

3.
Agenda
● Fivetran introduction
● Easy setup of Fivetran
● The challenge with historical analysis
● Fivetran History Mode

4.
➔Automatic Data
Updates (DML)
➔Automatic Schema
Migrations (DDL)
➔Automated Recovery
from Failure
(Idempotent)
➔Micro-batched
architecture
➔Extensible Cloud
Functions
Fivetran: Automatic Data Integration

5.
The Modern Data Stack: Fivetran + Delta Lake

6.
Easy setup of Fivetran, for Databricks 7.1+
● Select Destination
- Databricks on AWS
or
- Databricks on Azure
● Easy configuration
- Auto-creates secure staging area

7.
Fivetran History Mode Intro: SCD Type 2
Analyze data from a
particular point in time
or how data has
changed over time.
Historical Analysis…
Activated per table at the
slide of a toggle.
…with Precision and Ease… of Changes…
Record every version of
each record in your
destination.

8.
Fivetran History Mode for Salesforce:
Example Use Cases
Track changes made to
opportunities over a period
of time to gain an in-depth
understanding of your sales
cycle.
Track changes to plans and
usage over time, so you
have information about
whether an account is
growing or reducing usage.
Opportunity Changes Account Growth
Gain an understanding of
bookings and cancelations.
Prior to history mode, you
would lose information
about the number of
bookings that were
canceled.
History of Growth

9.
1. Connect to Delta Lake on Databricks
2. Ingest data via Fivetran’s connector for Salesforce
3. Optional: Use a Fivetran dbt package to jump-start
your modeling process for aggregations
4. Click on History Mode within Fivetran
5. Set synchronization
Speeding time to insight with the modern stack

10.
Demo: Historical analysis for Salesforce data

11.
Feedback
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