Analytical Objects

Analytical Objects

An Analytical Object in Intellicus defines a cube comprising related dimensions and measure groups. It enables multi-dimensional data analysis and accelerates time-to-insights.

To design and save an Analytical Object in a specific category, you must have Read, Write, and Execute permissions for Analytical Objects in that category.

This topic outlines the prerequisites and steps to design and build cubes using Analytical Objects.

Prerequisites

License

Ensure the Intellicus system is licensed for:

  • Designing Analytical Objects

  • Using High Speed View

Note
These are add-on features available in Professional and Enterprise editions of Intellicus.

Disk Space

Each cube can occupy from a few kilobytes (KB) to several gigabytes (GB) of disk space depending on:

  • Cube design complexity

  • Volume of source data

  • Number of dimensions and measures

Ensure sufficient disk space is available to accommodate all planned cubes.

Memory

Intellicus uses an optimized streaming-in and disk-swapping mechanism to manage memory efficiently during cube building.

Recommendation:
Allocate at least 1 GB of RAM per cube during build time for optimal performance when processing 5–10 million transactional records (approx. 2–3 GB cube size).
Memory requirements will vary based on data volume and complexity.

Cube Terminology

Term

Description

Term

Description

Dimension

Group data into natural categories. Each dimension can contain one or more levels. For example, the Time dimension may include Year, Month, and Day levels.

Level

A sub-category within a dimension.

Attribute

A specific type of information in a dimension (e.g., Year is an attribute in the Time dimension).

Hierarchy

A parent-child relationship among elements in a dimension. Parent values summarize their children.

Measure

Represents numeric, aggregatable data. Examples: Revenue, Cost, Inventory, Employee Count, etc.

Cube Design Concepts

Intellicus supports two primary cube structures:

  • Hierarchical model (pre-computed)

  • Tabular model (on-demand computation)

For example, you can create a cube that aggregates sales data by:

  • Time: Month, Week

  • Personnel: Salesperson, Client

  • Geography: Region

  • Product: Model

You can then run queries such as:

  • Total sales by Month, Salesperson, Region

  • Maximum sales by Product Model and Region

Data Sources for Cubes

To design a cube, you can source:

  • Fact Data (measures)

  • Dimension Data

These can be fetched using Intellicus Query Objects, which support:

  • Relational databases (RDBMS)

  • File-based sources (e.g., CSV, Excel)

For more information, refer to the Query Objects section under Data Preparation.

Cube Browsing

Once the cube is designed and built, you can browse and analyze it using High Speed View for interactive and high-performance data exploration.

Refer to the chapters below to access and design Analytical Objects.

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