University of Central Missouri Data Warehouse Architecture Research Paper

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University of Central Missouri

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This week's written activity is a three- part activity. You will respond to three separate prompts but prepare your paper as one research paper. Be sure to include at least one UC library source per prompt, in addition to your textbook (which means you'll have at least 4 sources cited).

Start your paper with an introductory paragraph.

Prompt 1 "Data Warehouse Architecture" (2-3 pages): Explain the major components of a data warehouse architecture, including the various forms of data transformations needed to prepare data for a data warehouse. Also, describe in your own words current key trends in data warehousing.

Prompt 2 "Big Data" (2-3 pages): Describe your understanding of big data and give an example of how you’ve seen big data used either personally or professionally. In your view, what demands is big data placing on organizations and data management technology?

Prompt 3 “Green Computing” (2-3 pages): One of our topics in Chapter 13 surrounds IT Green Computing. The need for green computing is becoming more obvious considering the amount of power needed to drive our computers, servers, routers, switches, and data centers. Discuss ways in which organizations can make their data centers “green”. In your discussion, find an example of an organization that has already implemented IT green computing strategies successfully. Discuss that organization and share your link. You can find examples in the UC Library.

Conclude your paper with a detailed conclusion section.

The paper needs to be approximately 7-10 pages long, including both a title page and a references page (for a total of 9-12 pages). Be sure to use proper APA formatting and citations to avoid plagiarism.

Your paper should meet the following requirements:

• Be approximately seven to ten pages in length, not including the required cover page and reference page.

• Follow APA6 guidelines. Your paper should include an introduction, a body with fully developed content, and a conclusion.

• Support your answers with the readings from the course, the course textbook, and at least three scholarly journal articles to support your positions, claims, and observations, in addition to your textbook. The UC Library is a great place to find supplemental resources.

• Be clearly and well-written, concise, and logical, using excellent grammar and style techniques. You are being graded in part on the quality of your writing.

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Explanation & Answer

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Running head: DATA WAREHOUSE ARCHITECTURE

Your name
Instructor’s name
Course
Date of submission

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DATA WAREHOUSE ARCHITECTURE

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Introduction:
Data architecture implies the various provisions which are used to describe the current
state, the requirements of data, helping to guide the integrations of data as well as data assets
control based on stipulations of data strategy. Its main purpose is in bridging the business
strategy and technical execution. Strategically, data architecture helps to prepare business in
quickly evolving and benefiting from the advancing technology (Blažić, Poščić & Jakšić, 2017).
For agility and the functional transformation for change, data architecture enhances the
management of complex information delivery as well as data within the company. In this case, it
is of importance to consider the various forms of data analytics which are applicable in
organizations such as green data, data warehouse as well as big data analytics.
Prompt 1 "Data Warehouse Architecture" (2-3 pages): Explain the major components of
data warehouse architecture, including the various forms of data transformations needed
to prepare data for a data warehouse. Also, describe in your own words current key trends
in data warehousing.
The idea of data collection representing historical data within various organizational
operations is referred to as a data warehouse. Such data is stored in various structures that are
optimized to analyze data as a warehouse of the data. Systems that are involved in data
warehousing include home designs having different architecture options. Some of the systems
have operational data stores while others are deployed with data amounts (Blažić, Poščić &
Jakšić, 2017). Additionally, some of the data warehouses consider data sources inclusive of the
internal and external sources of data.

DATA WAREHOUSE ARCHITECTURE

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Data warehousing seeks to determine some specific ways through which information
from raw data can be got for usability to aid in more knowledge. Thus, it is composed of data
collection which is mainly used for intelligence in business as well as decision making. More so,
data architecture is subject-oriented, time-variant as well it is not updatable when constructing a
data warehouses for use in the business, of much consideration s the various layers in the
warehouse architecture. Among the various components of data warehousing is;
Source data component: this implies the source data arriving into the data warehouse that
can as well be grouped into the categories of internal data, archived data, production data as well
as external data.
Data staging component: is the one occurring when the extract data in its various sources
needs to be transformed to become ready in such a format that is appropriate for querying and
analysis. Among the various basic functions within the staging areas are the transformations of
data, data extraction as well as loading of the data (Ahmed, et al. 2017). The repositories of data
in the operational systems comprise of the current data requiring the structuring of data
efficiently and in a faster processing manner.
Metadata component: This is similar to the data catalog or dictionary within the database
management system. It is u...


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