Option 2 is a work plan with a strategy for migrating a working prototype database from a source production OLTP environment, into a Data Mart star schema design. The plan will include steps to migrate non-volatile subject-oriented records into a read-only OLAP environment. Objective is to Develop a action plan for migrating historical data from an operational source into a Business Intelligence (BI) data mart to become historical records for decision making.
Signature Writing Assignment (due in Week 4):
A 500+ word plan that demonstrates results from technical research conducted about implementing a working prototype design of a database into a production environment. Assume that a working prototype has been built as a vehicle for demonstrating the design. After the work plan is accepted, scheduling the deployment will be a milestone for certifying a fully operational database (using an alternative to having any front end application) after clear test acceptance by both technical and business end users. Yes, the design may be for the final outcome for ITM450 project. The plan must contain at least 3 references composed in APA style, with cross reference to cited quotations or paraphrased content from source. Using Owl of Purdue for proper formatting of references is suggested. Citing a professional’s expert opinion is accepted.
After composing your plan, remove all instructions on this page.
Week Three Learning Outcomes
- Define Business Intelligence (BI)
- Explain the benefit of BI
- Describe the significance of Data Warehouses
- List the four main characteristics of Online Analytical Processing (OLAP)
Reading: Ch. 13 – Business Intelligence and Data Warehouses
The text book describes Business Intelligence (BI) outcomes for data mart. A simplifying structure for this plan is suggested by these five topics for a Wk4 Prototype Migration Activity. The bold words may be keywords for a plan sections.
- Describe the tables in an operational environment, such as a functional application, assuming it to be running in an online transactions processing (OLTP) architecture.
- Define your Business Intelligence (BI) Strategy for migrating history into a designed data mart to be compatible with potential OLAP usage by decision makers
- Explain the future benefit of BI summary information to lead to improved business outcomes and profitability
- Describe the significance of starting with a single Data Mart for building toward a repository of historical records
- State some business rules for extracting relevant data from one or more sources, transformations for migrating historical facts into a BI environment and loading
An optional plan framework is included on the next page as a starting place.
Table of Contents
[A] Operational environment: 2
[E] Business Rule Statements: 4
Figure 1. Operational Application Database Design. 2
Figure 2. Business Intelligence Star Schema. 3
Figure 3. Business Intelligence Star Schema. 3
Figure 4. Data Mart outcome report or dashboard images. 4
Title: <Name of Solution>
Submitted by <your name> on Date: __/__/__
[A] Operational environment:
Describe the nature of your prototype database design (which started in Week 1 of this course, or coming forward from previous work.)
- Who are the users?
- What product or service is being processed?
- Who is(are) the customers?
- What tables exist to represent the daily transactional activity of the business?
- What tables are descriptive of the transactions?
- When does time relevance (dates) play are part?
- What database constraints exist (on which tables)?
- What value has achieved by placing Referential Integrity into the is prototype?
| A prototype operational database design, an ERD (perhaps for the selected project scenario)
|
Figure 1. Operational Application Database Design
[B] Data Mart:
The starting place for a first data mart is the Star Schema, including a fact and some number of dimension tables, one being a Time dimension (perhaps called a Calendar). The plan may involve adding some more test data into the operational tables, then creating queries that will extract those records, transform the records to fit the design of a fact and dimension tables. Here is a list of possible statistics to report about your solution. Remove those that do not apply. After providing answers remove the questions.
- Describe the nature of your Star schema
- Star fact contains ___<kind of data> __ Is this table contain any rows?
- Does this data match up with the source table used for initializing it?
- Earliest date in the imported and refined time dimension table? __ / ___ / ___. Latest? ___ / ___ / ___
- Earliest date for a fact records joined to a date on the time? __ / ___ / ___. Latest? ___ / ___ / ___
- Dimension tables for: <name & row count for each dimension>
- Who? (the people or the organizational units)
- Where? (locations in which OLTP operations takes place)
- What? (descriptions of content in terms of products/services created or sold)
- When? (time frame for recording business dates)
- Does each dimension table have an integer Primary Key? ___
- Does fact table have a simple or compound primary key? ____
| Insert a star schema design diagram here
|
Figure 2. Business Intelligence Star Schema
[C] Future Benefits:
Explain the future benefit of BI summary information to lead to improvements in business outcomes and profitability
[D] First Data Mart:
Describe the significance of starting with a single Data Mart for building toward a repository of historical records
| An original star schema design… either here in [D] or above in [C]…. Keep one and discard the other, then regenerated the table of figures
|
Figure 3. Business Intelligence Star Schema
[E] Business Rule Statements:
State some business rules for extracting relevant data from sources, transformations for migrating historical facts into a BI environment. Which dimension table may be stable after first load, and which may change?
[F] BI Outcomes:
Describe come BI outcomes for data mart. Define the future outcome for the prototype database after it will go into production.
| Perhaps an artifact that represents the possible outcome of your scenario. This might be found by a google images search and an image or two of results that vendors show, or training scenario outcomes, or perhaps an example of a real outcome.
Citation URL: |
Figure 4. Data Mart outcome report or dashboard images
References: (Include a minimum of 3 sources in APA format)
Coronel, C. & Morris, S. (2017). Database systems: Design, implementation, and management (12th ed.). [Instructor Manual for Ch13_Database_Warehouse_Ed12_Review]. Retrieved from ITM450 Blackboard course Week Three Learning Activity with permission by the instructor.
