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Unraveling the Secrets of Elasticube Design Inbar Rodan

Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

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Page 1: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Unraveling the Secrets of Elasticube DesignInbar Rodan

Page 2: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

● How many product units did we sell in total?

● How many employees are there per region?

● How many units did we sell in each product category?

● What Percentage of whole food Category are grain products?

Foodies Goodies

Sales Dashboard Creation

Page 3: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Business Question

Identify NeedsWhat Percentage of whole food Ctegory

are grain products?

KPI KPI KPI

Fact Dim Fact Dim Fact Dim

Page 4: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Import Data ScopeFocus Only on whole food

Dim Table

Dim Table

Dim Table

Dim TableDim Table

Dim Table

Dim Table

Dim Table

Transactions

Dim Table

Dim Table

Dim Table

Dim Table

Page 5: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Transform to a Centralized StructureTransform into product categroies

Dim TableDim Table

Dim Table

Fact Table

Page 6: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Connect Unique DimensionsRepresente to each category

Dim Table

Dim Table

Dim Table

Dim Table Dim TableFact Table

Page 7: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Validate the DataSo.. What is the grain food % ?

Page 8: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Validate

Best Practices Overview

Identify Import Model Connect

Page 9: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Excellent MistakesAND SECRETS

Page 10: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

● How many product units did we sell in total?

● How many employees are there per region?

● How many units did we sell in each product category?

● What Percentage of whole food Category are grain products?

Foodies Goodies

Sales Dashboard Creation

Page 11: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Dim Table

Dim Table

Dim TableDim Table

Dim Table

Excellent Mistake #1“ Import all relationships and tables,

as in data warehouse “

Dim Table

Dim Table

Fact Table

Page 12: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Excellent Mistake #1Data Warehouse Implications

● Incorrect Results Query takes alternative path

● Long Import Times

1. Simpler Relationship2. Shorter Route3. Random

Path Preference

Page 13: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

● Include only relevant tables, fields, relationships

● Consolidate by subject

Excellent Secret #1Solving Cycles

Page 14: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Excellent Mistake #2“ Let the Many-to-Many be! ”

Dim Table

Dim Table

Dim Table

Fact Table

Page 15: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

● Incorrect Results How many units were sold per product?

● Performance Load Time Complexity of O(n2)

Excellent Mistake #2MtM Implications

Supplier Product ID

Pasta Buttini s.r.l. AA1

Tokyo Traders AA1

= 16Product ID Quantity

AA1 3

AA1 5

Product ID Quantity

AA1 3

AA1 5

Page 16: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Consolidate When tables data share granularity

Bridge When tables data does not share granularity, query from bridge table

Excellent Secret #2Solving MtM

OrdersSuppliers Per

Product

TableTable

Products

Suppliers/Orders

Page 17: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Excellent Secret #2Tracking MtM risks

1) MtM risk table in the Elasticube reflect the uniqueness of each table that has to be unique

2) MtM risk Widget

3) Add the KPI to Pulse

4) Let Pulse monitor your EC proactively

Page 18: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

● Incorrect Results something is just wrong

● Multiple Dim Fields same dim in different tables

● Unclear Naming Convention of cubes, tables, fields

Excellent Mistake #3“ Once I finished modeling the

elasticube, it is done ”

Page 19: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

● Verify Data

● Set duplicate fields as Invisible

● Pick Intuitive Naming Convention

Excellent Secret #3Solving Unfriendly Cube

Page 20: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Best Practices Summary

ValidateIdentify Import Model Connect

Page 21: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Questions?

Page 22: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Thank You!

Page 23: Analytics Databases: Unraveling the Secrets of Sisense Elasticube Design

Unraveling the Secrets of Elasticube DesignInbar Rodan