MicroStrategy Terminology

Source systems
Source system refers to any system or file that captures or holds data of interest
This data is eventually analyzed in report format to determine answers to business-related questions
The source system is the originating point of the data

ETL process
The extraction, transformation, and loading (ETL) process represents all of the steps necessary to move data from disparate source systems to an integrated data warehouse

Data warehouse
The data warehouse is a large database populated with data that is stored in tables
These databases have many tables, tracking many different pieces of information
Data warehouses are generally based on some form of relational database and can be queried with Structured Query Language(SQL) to pull information from the warehouse into a report format
The data stored in the data warehouse originates from the source systems
Data warehouses are designed and optimized for analytical processing
Analytical processing involves manipulating the data in the warehouse to calculate sales trends, growth patterns, trend reporting, profit analysis, and so on

Logical data model
The logical data model graphically represents the flow and structure of data in a business environment
It comprises facts, attributes, and hierarchies.

Physical warehouse schema
The physical warehouse schema is based on the logical data model
It is a detailed graphic representation of your business data
It organizes the logical model in a method that makes sense from a database perspective

Metadata database
The metadata contains information that facilitates the transfer of data between the data warehouse and the MicroStrategy application
It stores the object definitions and the information about the data warehouse, including its structure
MicroStrategy uses the metadata to translate user requests into SQL queries and to translate the SQL queries back into MicroStrategy objects, such as reports
The three types of objects that are stored in the metadata are:
* schema objects
Schema objects are created usually by a project designer
Schema objects relate the information in the logical data model and physical warehouse schema to the MicroStrategy environment
Facts, attributes, and hierarchies are examples of schema objects
These objects are developed in MicroStrategy Architect, which can be accessed from MicroStrategy Desktop

* application objects
The report designer creates the application objects necessary to run reports
Application objects, which are developed in MicroStrategy Desktop and Web, are the building blocks for reports and documents
These application objects include reports, report templates, filters, metrics, prompts, and so on

* configuration objects
Administrative and connectivity-related objects, also called configuration objects, are managed in MicroStrategy Server Administrator by an administrator role
Examples of configuration objects include users, groups, server definitions, and so on

Facts
A fact has two characteristics: it is numerical and aggregatable
Examples of facts include revenue, inventory, and account balances
Facts are stored in the data warehouse in fact tables
These fact tables comprise different columns, each cell representing a specific piece of information
SQL aggregations, such as SUM and AVG, are performed on the facts in the database tables

Attributes
Attributes act as holders of information, allowing you to add context to your facts in a report
For example, if you had $10,000 in revenue, that number does not mean anything in a business sense unless you know the context, such as which region, the designated time frame for the sales, and what was the labor involved
Simply put, attributes provide categories for the summarization of data

* Attribute elements
Attribute elements are the data shown on the report
Think of them as a sub-level of the attribute
For example, City might be the attribute, whereas London, Milan, and New York are the attribute elements
In the data warehouse, attributes are usually represented by columns in a table, and attribute elements are represented by the rows

* Attribute relationships
Attribute relationships give meaning to the data in a logical data model by associating attributes based on business rules
The types of attribute relationships are:

# one-to-one
# one-to-many
# many-to-many

Metrics
Metrics are analytical calculations performed against stored data (facts) to produce results that can then either be read as status material or analyzed for decision-making purposes
A metric can be defined within a report to specify the data to be displayed in the report

Reports
A report is a request for specific formatted data from the data warehouse
Reports can contain attributes and facts from the data warehouse, filters to determine how much data is used to generate the report, and metrics to perform calculations on the facts
More sophisticated functions, such as report limits, metric qualifications, dynamic aggregation, and shortcuts to reports and filters, allow you to create more functional and informative reports

Report Objects
Report Objects are objects associated with a given report
At any time, a user can choose to view only a particular set of those objects
For example, you choose to show Metric1 and Metric2 but not Metric3 on the template
Report Objects also indicate the lowest level of detail available in a report