Group items tagged

Fact tables are the foundation of the data warehouse. They contain the fundamental measurements of the enterprise, and they are the ultimate target of most data warehouse queries.

The grain is the business definition of what a single fact table record represents.

the grain is the description of the measurement event in the physical world that gives rise to a measurement.

Each nominal ledger account is unique to allow its ledger to be located

A chart of accounts (COA) is a created list of the accounts used by an organization to define each class of items for which money or the equivalent is spent or received. It is used to organize the finances of the entity and to segregate expenditures, revenue, assets and liabilities in order to give interested parties a better understanding of the financial health of the entity.

Types of accounts[edit] Asset accounts: represent the different types of economic resources owned or controlled by business, common examples of Asset accounts are cash, cash in bank, building, inventory, prepaid rent, goodwill, accounts receivable[1] Liability accounts: represent the different types of economic obligations by a business, such as accounts payable, bank loan, bonds payable, accrued interest.[citation needed] Equity accounts: represent the residual equity of a business (after deducting from Assets all the liabilities) including Retained Earnings and Appropriations.[citation needed] Revenue accounts or income: represent the company's gross earnings and common examples include Sales, Service revenue and Interest Income.[citation needed] Expense accounts: represent the company's expenditures to enable itself to operate. Common examples are electricity and water, rentals, depreciation, doubtful accounts, interest, insurance.[citation needed] Contra-accounts: Some balance sheet items have corresponding contra accounts, with negative balances, that offset them. Examples are accumulated depreciation against equipment, and allowance for bad debts against long-term notes receivable.

racle SQL Developer Data Modeler provides a model driven approach for database design and generation, implemented by integrated set of models – Logical, Data types, Dimensional, Relational, Data Flow diagrams and Physical models for supported Oracle Databases, Microsoft SQL Server 2000 and 2005

Cube Views metadata

Dimensional Models   Dedicated full featured Dimensional model – star and snowflake schema easily can be built and expressed on detailed and compact diagrams   Dimensions – support for merging (level can belongs to more than one dimension), shared, fact and role playing dimensions   Hierarchies – value based hierarchies (parent-child), and regular and ragged level based hierarchies   Measures – fully, semi and none additive; different aggregation functions on different dimensions ; fact dimension; calculated measures   Query wizard allows Select statements to be generated from the dimensional model   Support for Oracle OLAP. This includes specifics like cube partitioning, sparse dimensions, and compressed measures   Built-in wizards help to define all required object types and view definitions that enable SQL access to dimensional data in Oracle AW (using the OLAP_TABLE interface)   Bidirectional integration with Oracle physical model - Dimensional model can be created using SQL dimension definitions in physical model or the definitions can be created from the dimensional model

“Master Data is your business critical data that is stored in disparate systems spread across your Enterprise.”

Parties: represents all parties the enterprise conducts business with such as customers, prospects, individuals, suppliers, partners, etc. Places: represents the physical places and their segmentations such as geographies, locations, subsidiaries, sites, areas, zones, etc. Things: usually represents what the enterprise actually sells such as products, services, packages, items, financial services, etc. Financial and Organizational: represents all roll-up hierarchies used in many places for reporting and accounting purposes such as organization structures, sales territories, chart of accounts, cost centers, business units, profit centers, price lists, etc.

Transactional Data such as purchase orders, invoices or financial statements, is not usually considered master data since it actually registers a “fact” that happened at a certain point in time.

A conformed dimension is a set of data attributes that have been physically referenced in multiple database tables using the same key value to refer to the same structure, attributes, domain values, definitions and concepts. A conformed dimension cuts across many facts.

Dimensions are often recycled for multiple applications within the same database. For instance, a "Date" dimension can be used for "Date of Sale", as well as "Date of Delivery", or "Date of Hire". This is often referred to as a "role-playing dimension".