Data Warehouse Developer

A load manager extracts data from the source system. Fast load the extracted data into temporary data store. Perform simple transformations into structure similar to the one in the data warehouse.

A data warehouse contains historical information that is made available for analysis of the business whereas an operational database contains current information that is required to run the business.

Metadata is simply defined as data about data. In other words, we can say that metadata is the summarized data that leads us to the detailed data.

Subject oriented signifies that the data warehouse stores the information around a particular subject such as product, customer, sales, etc.

☛ XMLA is XML for Analysis which can be considered as a standard for accessing data in OLAP, data mining or data sources on the internet. It is Simple Object Access Protocol.XMLA uses ‘discover’ and ‘Execute’ methods. Discover fetches information from the internet while Execute allows the applications to execute against the data sources.

☛ XMLA is an industry standard for accessing data in analytical systems, such as OLAP. It is based on XML, SOAP and HTTP.

☛ XMLA specifies MDXML as the query language. In the XMLA 1.1 version, the only construct in MDXML is an MDX statement enclosed in the tag

View:

☛ Tail raid data representation is provided by a view to access data from its table.

☛ It has logical structure that does not occupy space.

☛ Changes get affected in corresponding tables.

Materialized view:

☛ Pre-calculated data persists in materialized view.

☛ It has physical data space occupation.

☛ Changes will not get affected in corresponding tables.

The warehouse manager performs consistency and referential integrity checks, creates the indexes, business views, partition views against the base data, transforms and merge the source data into the temporary store into the published data warehouse, backs up the data in the data warehouse, and archives the data that has reached the end of its captured life.

Metadata respiratory contains definition of data warehouse, business metadata, operational metadata, data for mapping from operational environment to data warehouse, and the algorithms for summarization.

The functions performed by Data warehouse tool and utilities are Data Extraction, Data Cleaning, Data Transformation, Data Loading and Refreshing.

A load manager performs the operations required to extract and load the process. The size and complexity of load manager varies between specific solutions from data warehouse to data warehouse.

Time dimensions are usually loaded by a program that loops through all possible dates appearing in the data. It is not unusual for 100 years to be represented in a time dimension, with one row per day.

Some applications include financial services, banking services, customer goods, retail sectors, controlled manufacturing.

Data warehouse is a subject oriented, integrated, time-variant, and nonvolatile collection of data that supports management's decision-making process.

The stages are IT strategy, Education, Business Case Analysis, technical Blueprint, Build the version, History Load, Ad hoc query, Requirement Evolution, Automation, and Extending Scope.