What is Data warehousing?
Answer form: Texan Software Solutions (.texansoft.com):-
In any line of business, information is a very vital element. This information can be in various formats such as documents or data. As organizations expand so does the volume of information and it becomes highly difficult to store it as it is spread in different locations. Because managers are busy in important decision making processes, they are unable to devote such a huge amount of time organizing information.
In such a scenario, information management system becomes inevitable. Information management involves gathering and managing information from various sources and unifying then into a single format so that it becomes easily accessible to the right people at the right time.
Since the early 1990s, data warehouses have been at the forefront of information technology applications as a way for organizations to effectively use digital information for business planning and decision making. As information professionals, it is necessary for us to understand the data warehouse system architecture.
The term Data Warehouse was coined by Bill Inmon in 1990, which he defined in the following way: "A warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process".
About Data warehousing
Data warehouse is a repository of an organizations electronically stored data. Data warehouses are designed to facilitate reporting and analysis.
A Data Warehouse houses a standardized, consistent, clean and integrated form of data sourced from various operational systems in use in the organization, structured in a way to specifically address the reporting and analytic requirements.
This definition of data warehouse focuses on data storage. However, the means to retrieve and analyze data, to extract, transform and load data, and to manage the data dictionary are also considered essential components of a data warehousing system. Many references to data warehousing use this broader context. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform, and load data into the repository, and tools to manage and retrieve metadata.
Texansoft.com offers a comprehensive portfolio of training on a various Data Warehouse solutions. With our expertise in the field of Data warehouse training and our world-class Virtual Learning Solution, Texansoft.com offer you training customized to your specific needs.
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Classifications in Data Warehousing:
1.ETL Tools.
2. BI Reporting Tools.
What is ETL, Extract Transform and Load?
ETL is an abbreviation of the three words Extract, Transform and Load. It is a process in database usage and especially in data warehousing that involves:
Extracting data from different types of systems/sources
Transforming it to a structure that fits operational needs (which can include quality levels) and is appropriate for reporting and analysis
Loading it into the end target (database or data warehouse)
The figure below displays these ETL steps.
ETL Architecture and Steps
Popular ETL Tools
Informatica
Data Stage
Ab Initio
BO DI
Informatica course content of Texansoft.com
Informatica
Introduction and Architecture
"Introduction to Informatica
"Architecture of Informatica "" Power Center 8.1
"Informatica Design Process
"Informatica Client Tool "" Designer
"Source Analyzer and Warehouse Designer
Mapping Designer
"Create a Simple Mapping
"Overview of Transformations
"Types of Transformations "" Active and Passive
"Expression Transformation
"Source Qualifier Transformation
"Introduction to Workflow Manager
"Control Flow Statements
"Task Developer
"Workflow Designer
"Creating Connections
Flat Files Handling
"Create Simple Mappings
"Flat File Analysis
Architecture Review
"Architecture 8.1 Review
"Differences between Power Mart and Power Center
"Connecting to SAP
"FTP Process
"Command Task
"Create a Mapping
"Joiner Transformation
Transformations
"Create a Mapping
"Using Join in a Source Qualifier Transformation
"Expression Transformation
"Filter Transformation
Transformations Contd
"Multiple Targets Loading
"Router Transformation
"Diff between Filter and Router Transformations
"Create a Mapping
"Master Outer Join
Transformations Contd
"Create a Mapping
"Reusable Transformation
"Lookup Transformation
"Debugger
"Handling Multiple Files as Source
Mapplets
"Create Mappings
"Sequence Generator Transformation
"Multiple Pipelines in a Single Mapping
"Target Load Plan
"Mapplets
Update Strategy
"SCD Type 1 mapping Implementation
"Update Strategy Transformation
SCD Type 2
"SCD Type 2 mapping Implementation
Loading Strategy
"Sequential and Parallel Loading
"Union Transformation
"Dynamic Lookup Cache
"Introduction to Fact Loading
"Create a Mapping
Transformations Contd
"Create a Mapping
"Date Dimension Loading
"Lookup Transformation "" Persistent Cache
"Aggregator Transformation
"Sorter Transformation
"Creating Stored Procedure
Transformations Contd
"Normalizer Transformation
"Stored Procedure Transformation
"Active Vs Passive Transformations
"Connected Vs Unconnected Transformations
Implementing Incremental Loading
"Create a Mapping
"Importance of Mapping Variable
Implementing Incremental Aggregation
"Create a Mapping
"Incremental Aggregation
Transaction and Variable Port
"Transaction Control Transformation
"Variable Ports
Workflow Tasks
"Scheduling
"Task Link Properties
"Event Raise Task
"Event Wait Task
"Work let
Others
"Parameter Files
"Removing Duplicate Rows
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