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100

What is a Data Warehouse?

store historical business data

100

What is Extract?

first step in ETL where data is collected from different sources.

100

What is OLTP?

used by banks and ATMs for daily transactions.

100

What is Load?

I am the "L" in ETL.

100

What is MOLAP?

faster because my summaries are already calculated in cubes.

200

What is ROLAP?

handle huge datasets because I use relational databases.

200

What is HOLAP?

combine cubes with relational tables.

200

What is Data Mining?

discover hidden patterns from warehouse data.

200

What is a Star Schema?

a schema with one fact table connected to several dimension tables.

200

What is a Snowflake Schema?

the centralized fact table is connected to multiple dimensions. In the snowflake schema, dimensions are present in a normalized form in multiple related tables.

300

What is Roll-up?

Aggregating data to a higher level

300

What is Drill-down?

Moving down in the concept hierarchy

300

What is Slice?

In a slice method, one dimension is chosen, and a subcube is generated.

300

What is Dice?

A dice operation selects two or more dimensions, and subcubes are generated

300

What is Data Integration?

reports from multiple departments cannot be combined properly.

400

What is HOLAP?

Combines ROLAP + MOLAP.  

400

What is Pivot

rotate the data cube to provide a different view.

400

What is MOLAP?

stored in multidimensional cubes for very fast queries.

400

What is ROLAP?

use SQL to answer analytical queries.

400

What is a Data Lake?

A data lake is a centralized repository designed to hold vast volumes of data in its native, raw format — be it structured, semi-structured, or unstructured.

500

What is Transformation?

convert different date formats into one standard format.

500

What is Data Cleansing?

improve data quality before analysis.

500

What is Time-Variant?

represent historical information.

500

What is a Multidimensional Data Model?

organize data into facts and dimensions.

500

Difference between ETL and ELT

ETL (Extract, Transform, Load) 

1. Data is transformed before loading into the warehouse 

2. Only cleaned and transformed data is stored 

ELT (Extract, Load, Transform) 

1. Data is transformed after loading into the warehouse 

2. Raw data is stored first, then transformed when needed  

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