Basics of Einstein Analytics

In this session we talk about Basics of Einstein Analytics. Einstein Analytics processes data using EtLT approach. Extraction, transformation, Loading in Analytics, Transformation in Analytics.

Agenda:-

1. What is Einstein Analytics
2. Terminology
3. Importing Dataset
4. Creating Lenses
5. Creating Dashboard
6.  Dashboard Tips and Tricks
7. Steps Cross-Dataset filter (Connect DataSet)
8. Dataflow Performance Improvement
9. View SAQL

Terminologies

1. App – Analog to a folder
2. DataSet – Formatted and Optimized data
3. Lenses – Saved exploration from the Dataset
4. Measure – Numeric fields (any field that can be measured)
5. Dimension – Group By
6. Filter – Condition
7. Grains – One row of denormalized data
8. SAQL – Salesforce Analytics Query Language based on Pigql
9. Pigql – Apache Pig Latin Query Language used in Hadoop as well
10. SFDCDigest – Deriving Data
11. Augment – Joint between the digestive system
12. Faceting – Updating filter to change dashboard content

How many ways to create a Dataset

1. DataFlow – Using Add Dataset in DF
2. Create Dataset Button
3. JSON
4. Recipe

Fun Facts

Can you restore DataFlow?  No. That’s why downloading and Backup JSON frequently.

Can you restore Dataset? Yes. Salesforce maintains a version of Dataset. Navigate to the Dataset dropdown; at the bottom of the page, there is a link to restore the dataset.

Data Replication

1. Decouples the extract of Salesforce data from your dataflows, letting you run it on a separate schedule
2. As it runs ahead of time, Dataflow performs faster
3. To make it faster, extraction done in incremental order
4. Few other connectors become available once we enable replication

Here is PPT of Session:-

Basics of Einstein Analytics Video