Explore a data warehouse for business intelligence

Assignment Help Database Management System

Reference no: EM131469861 , Length: 20

Data Warehousing and Business Intelligence Project

Task: Architect, Populate and Explore a Data Warehouse for Business Intelligence

This CA will assess your ability to apply the theories, methodologies and strategies tackled in the course to successfully implement a data warehouse to support business intelligence queries.

CA Deliverables

For the project, there are 2 deliverables: 1) a 20 page report, and 2) a pre-recorded video demonstration with voice commentary of up to 5 mins.

The paper should be structured as follows:

1. Introduction: description of the setting of your data warehouse. This section should document: the sources of data, motivation for these sources of data, and describe how the data sets have been curated as well as coerced to work together. If you have fabricated your own data for this project, describe how this has been done, and what assumptions and/or data artefacts are interwoven in this process.

2. Architecture and Implementation: a high-level overview of how the data warehouse is built, i.e. have you followed in an Inmon, Kimball, or alternate approach. Detail why you have designed the data warehouse in this manner. Use supporting argumentation and (where appropriate) substantiating literature with respect to the architectural, methodological and design choices made. Include any details of staging in this section.

3. Data Warehouse Data Model: description of the schema(s) built. What dimensions do you have, and why? Also include a discussion on why they are composed in this manner. Noteworthy, also is how the data model has been prepared for the BI queries.

4. ETL strategy: how has the data been extracted, transformed, cleaned, and loaded into the data warehouse? Document precisely how the data goes from the sources to data warehouse, ideally as a logical data map. Document all transformations and steps taken to clean the data sources. Note which parts of your approach are automated.

5. Application of Data Warehouse: Execute three non-trivial queries that highlight the business value of your data warehouse. For each query, note the sources of data contributing to the answer of the query. Each BI query should be articulated as a question that is answered using the data warehouse. You may use visualisation tools to execute the queries, e.g. Power Pivot, Tableau, Power BI etc. However, the video MUST illustrate how these tools have been integrated into your overall solution - at least how the cube has been imported/exported.

The report should detail the sources of data, how they were generated or extracted, and the steps taken to load and transform the data for storage in the warehouse.

Some example sources of data include:

- Social Media and Blogs

- Corporate documents, reports and white papers

- Patents

- (Dummy) CRM, ERP, Customer transaction records

- Accounting documents

- News articles (e.g. via feedzilla)

- Stock tickers (e.g. quandl.com)

- Web Pages

Attachment:- Data Warehousing Project.rar

Reference no: EM131469861

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Reviews

len1469861

4/22/2017 1:02:41 AM

Assignment Work with following details. Subject: Data Ware House. Data warehouse project description. I need the 20 page report as well as the 5 minute demo video. The final report should not be more than 20 pages including all figures and references. The setting and architecture are coherently documented. Appropriate academic literature substantiates wellargued design choices and methodological considerations.

4/22/2017 1:02:31 AM

The presented schema is coherently documented and engineered with key design choices are justified. All data sets have a well conceived place in the data model. The model evidences multidimensional drill down. A solution set that addresses complex issues, and performs complex ETL processes using advanced methods. May include or exploit new or emerging technologies to facilitate complex ETL methods. Loading, Extraction, Transformation and Cleaning are automated. The ETL methodology is well documented and discussed.

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