1. Develop a proof of concept data warehouse with more than one fact table by capturing data from North wind, or some other source(s). Document your reasons for selecting the subject area(s), identify key stakeholders, formalise the vision and goals of the data warehouse. Also list the requirements for developing the data warehouse.
2. Develop and present a suitable schema for the data warehouse. Discuss your reasons for the design.
3. Using Microsoft SQL Server, implement your tables and extract, transform and load data from the operational source(s) into the data warehouse. This can be done using any available tool or by writing SQL statements.
4. Produce minimum four reports in support of the requirements outlined in section 1 using SSDT. Also produce four visualisations using R programming language and analyse them.
5. “A good data warehousing professional is always scouting for new sources of data that can be applied to business intelligence”. In this spirit, develop a DTD/XML Schema based on a data warehouse cube and apply it to develop an XML document.
6. Discuss the limitations of the relational E-R and star schema dimensional models. Demonstrate the use of graph using Neo4j technologies.
Presentation slides in PPT
Visual Appeal No errors in spelling, grammar and punctuation. Clear and concise information on each slide.
Visually appealing/engaging.
Content Concise summary of the topic with all questions answered. Comprehensive and complete coverage of information.
Deliverables:
• Report (Microsoft Word) including visualisations and R code.
• Data warehouse Design (produced in Visio or in a similar system)
• Data Warehouse (scripts)
• Reports (pdf)
• SSDT Project
• XML DTD /Schema and document
• Neo4j document
• Presentation slides Read Less
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I am Microsoft Certified Data Scientist and MCSE in Data Analytics with experience in Predictive Analytics, Descriptive Analytics and Business Intelligence (BI). Total 12 years of experience in Data management and Data analytics and worked with Microsoft for 5 years and IBM for 2 years .
Currently started a Data Analytical Company called MSR Data Analytics Limited. I can build the data-warehouse model with below techniques
1. SSAS Multi-Dimensional model
2. SSAS Tabular Model
3. SSAS Slowly Changing Dimensions.