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1. 🔷 What is an OLAP Database?
OLAP stands for Online Analytical Processing.
An OLAP database is designed for complex analysis of large volumes of data, especially for business intelligence (BI) and decision-
making.
✅ Key Characteristics of OLAP Databases:
Optimized for read-heavy workloads (lots of queries, less frequent updates).
Supports complex queries like aggregations, trends, comparisons.
Works with multidimensional data (like sales by region, product, time).
Often used in data warehousing.
🔄 OLAP vs OLTP
Feature
OLTP (Online Transaction
Processing) OLAP (Online Analytical Processing)
Purpose Running daily operations Analyzing data for insights
Examples Banking, e-commerce apps Sales forecasting, dashboards
Data volume Smaller, real-time Large, historical
Operations Insert, update, delete Select, aggregate, group
Speed Fast for transactions Fast for complex reads
Structure Normalized (many related tables) Denormalized (star/snowflake
schema)
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2. 📊 OLAP Example
🔸 Scenario: Sales Analysis in a Retail Company
You run a chain of stores and want to analyze sales data to answer questions like:
"What were total sales last month by region?"
"Which products are selling best over the past year?"
"How do sales compare across quarters and years?"
💽 How Data is Stored in OLAP:
Your data might be organized in a data warehouse like this (denormalized format):
Fact Table: Sales
Date Product_ID Store_ID Units_Sold Revenue
2025-08-01 101 1 10 $200
2025-08-02 102 2 5 $150
Dimension Tables:
Product (Product_ID, Category, Brand)
Store (Store_ID, Region, City)
Date (Date, Month, Quarter, Year)
📈 What OLAP Lets You Do:
You can easily perform multidimensional analysis, such as:
Slice: View sales only for August 2025.
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3. Dice: View sales for "Electronics" in "West Region" during Q2.
Drill Down: Go from yearly to monthly to daily sales.
Roll Up: Aggregate sales from days to months to years.
🔧 Tools/Databases That Support OLAP
Microsoft SQL Server Analysis Services (SSAS)
Oracle OLAP
SAP BW
Snowflake (modern cloud-based OLAP)
Google BigQuery
Amazon Redshift
Apache Druid
🧠 Summary:
Feature OLAP Database
Use Case Business intelligence & reporting
Strength Complex analytical queries
Data Shape Multidimensional (facts + dimensions)
Best For Trends, comparisons, aggregations
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