Describe characteristics of analytical data processing solutions

Question 1

Describe the analytical data processing steps.

Answer 1

1. Operational data is extracted, transformed, and loaded (ETL) into a data lake for analysis.
2. Data is loaded into a **schema of tables **- typically in a Spark-based lake-house with tabular abstractions over files in the data lake, or data warehouse, with a fully relation SQL engine.
3. Data in the data warehouse may be aggregated and loaded into an online analytical processing (OLAP) model or cube. Aggregated numeric values (measures) from fact tables are calculated for intersection of dimensions from dimensions tables.
4. The data in the data lake, data warehouse, and analytical model can be queried to produce report, visualizations, and dashboards.

Question 2

What is an OLAP model?

Answer 2

OLAP model is an aggregated type of data storage that is optimized for analytical workloads. Data aggregation are across dimension at different levels, enabling drill up/down to view aggregations at multiple hierarchal levels.