Top-Down vs Bottom-Up Approach in Data Warehouse Design: Quiz and Flashcards

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Questions and Answers

What does data granularity in a data warehouse refer to?

The number of columns in a table

The level of detail (correct)

The amount of data stored

The speed of data retrieval

Which approach involves building bite-size departmental data marts?

Top-down approach

Bottom-up approach (correct)

Centralized data warehouse approach

Independent data marts approach

Should you look at the big picture of your organization and build a mammoth data warehouse?

Yes, always (correct)

No, never

Depends on the size of the organization

Only for small organizations

Which data warehouse design approach involves creating dependent data marts?

Data mart bus approach Signup and view all the answers

Should you start by building a pilot or go directly with a full-fledged implementation when developing a data warehouse?

Depends on the organization's budget Signup and view all the answers

What is a key advantage of the Top-Down Approach?

A truly corporate effort, an enterprise view of data Signup and view all the answers

Which characteristic is a disadvantage of the Top-Down Approach?

Takes longer to build even with an iterative method Signup and view all the answers

What is a key advantage of the Bottom-Up Approach?

Permeates redundant data in every data mart Signup and view all the answers

Which characteristic is a disadvantage of the Bottom-Up Approach?

Proliferates unmanageable interfaces Signup and view all the answers

Why is a top-down approach considered more centralized compared to a bottom-up approach?

Single, central storage of data about the content Signup and view all the answers

Which approach is more likely to lead to inconsistent and irreconcilable data?

Perpetuates redundant data in every data mart Signup and view all the answers

What is the relationship between data marts and the enterprise data warehouse?

Data marts depend on the enterprise data warehouse for data feed. Signup and view all the answers

In the data-mart bus approach, what is the principal notion behind conforming dimensions among data marts?

To integrate data marts into logically integrated supermarts. Signup and view all the answers

What is the main idea behind the top-down approach in building a data warehouse?

Beginning with a centralized data warehouse and then creating dependent data marts. Signup and view all the answers

What defines the bottom-up approach to building a data warehouse?

Creating data marts first and then integrating them into a centralized warehouse. Signup and view all the answers

Why is conforming dimensions among various data marts important in the context of the data-mart bus approach?

To have logically integrated supermarts providing an enterprise view of the data. Signup and view all the answers

How are 'data warehouses' and 'data marts' related in terms of different architectures?

'Data warehouses' and 'data marts' can have different integration methods in different architectures. Signup and view all the answers

Study Notes

Data Warehouse Approaches and Architectures

There are two approaches to building a data warehouse: top-down and bottom-up.
Top-down approach:
- Advantages: truly corporate effort, enterprise view of data, inherently architected, and single central storage of data.
- Disadvantages: takes longer to build, high exposure to failure, high outlay without proof of concept, and needs high level of cross-functional skills.
Bottom-up approach:
- Advantages: faster and easier implementation, favourable return on investment, less risk of failure, and allows project team to learn and grow.
- Disadvantages: each data mart has its own narrow view of data, perpetuates inconsistent and irreconcilable data, and proliferates unmanageable interfaces.

A Practical Approach

Ralph Kimball's practical approach consists of four steps:
- Plan and define requirements at the overall corporate level.
- Create a surrounding architecture for a complete warehouse.
- Conform and standardize the data content.

Data Granularity

In an operational system, data is usually kept at the lowest level of detail.
In a data warehouse, data is summarized at different levels, and the level of detail is referred to as data granularity.
The lower the level of detail, the finer is the data granularity.

Data Warehouses and Data Marts

Before building a data warehouse, consider the following questions:
- Top-down or bottom-up approach?
- Enterprise-wide or departmental?
- Which first—data warehouse or data mart?
- Build pilot or go with a full-fledged implementation?
- Dependent or independent data marts?

Data-Mart Bus

The data marts depend on the enterprise data warehouse for data feed.
The centralized data warehouse forms the hub to feed data to the data marts on the spokes.
Information delivery can be both from the centralized data warehouse and the dependent data marts.

Data Warehousing Architecture

The five major types of data warehouse architectures differ in how data is integrated and stored, and how "data warehouses" and "data marts" are related.

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Description

Learn about the advantages and disadvantages of top-down and bottom-up approaches in data warehouse design. Explore the differences in corporate effort, architecture, centralized storage, skills required, exposure to risk, and speed of implementation.

Top-Down vs Bottom-Up Data Warehouse Design

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