When deciding whether or not to create a data warehouse prototype before putting together a full-scale version, it is up to the data warehousing project team. Project participants are especially anxious about learning data warehousing skills before beginning work on the data warehouse. You can read my mind. Spell out your recommendations enterprise-wide in further detail.

When deciding whether or not to create a data warehouse prototype before putting together a full-scale version, it is up to the data warehousing project team. Project participants are especially anxious about learning data warehousing skills before beginning work on the data warehouse. You can read my mind. Spell out your recommendations enterprise-wide in further detail.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Concept explainers

Fundamentals of Datawarehouse

A data warehouse is a data repository which is used to store large quantities of historical data that are mostly used for creating reports that help businesses to identify their weaknesses and strengths. For example, demographics data about people of a region can help businesses identify the needs and preferences of the region’s population. A data warehouse acts as a central storage for storing data that comes from one or more heterogenous sources. It also consists of data which can be old and of historical value. One of the most important applications of this type of system is that it is used for supporting business intelligence and data analytics applications.

Question

When deciding whether or not to create a data warehouse prototype before putting together
a full-scale version, it is up to the data warehousing project team. Project participants are
especially anxious about learning data warehousing skills before beginning work on the
enterprise-wide data warehouse. You can read my mind. Spell out your recommendations
in further detail.

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Your data warehousing project team may be discussing whether to construct a prototype. Learn data warehousing essentials to prepare for the enterprise-wide data warehouse. What's your point? Your thoughts?
The team working on your data warehouse project should decide whether a prototype is necessary before releasing the final product. The data warehousing capabilities of the project team are prioritised before the enterprise-wide data warehouse is implemented. You are aware of my feelings. Justify your stance.
Your data warehousing project team should determine whether to prototype before launching it. Before installing the enterprise-wide data warehouse, the project group prioritizes data warehousing abilities. You know my thoughts. Explain your views.
When deciding whether or not to create a data warehouse prototype before putting together a full-scale version, it is up to the data warehousing project team. Project participants are especially anxious about learning data warehousing skills before beginning work on the enterprise-wide data warehouse. You can read my mind. Spell out your recommendations in further detail.
Your data warehouse project team is now arguing whether or not they should first construct a data warehouse prototype. You will be prepared for the data warehouse that serves the whole organization if you get specific expertise in data warehousing. What are your ideas and opinions? What are your ideas and opinions?
Your data warehouse prototype is now being discussed by the team constructing it. Concerns about how long it would take to acquire data warehousing skills have plagued the project team as they prepare to launch an enterprise-wide data warehouse. Is it fair to suppose that... Make sure that your meaning is clear.