Vaporware

Vaporware is a word used to describe products, usually computer hardware or software, that were not released on the date announced by their developer, or that were announced months or years before their release. Application of the word usually implies a negative opinion of a product, and uncertainty that it will eventually be released. The word has been applied to a growing range of products including consumer electronics, automobiles, and some stock trading practices.

Paper Launch

A paper launch is the situation in which a product is compared or tested against other products, despite the fact that it is not available to the public at the time. Generally the term is applied to the computer and gaming industry, although it is not limited to that.

Software Release Life Cycle

For more information please visit SRLC

What is a staging area?

The staging area is:-
1. One or more database schema(s) or file stores used to “stage” data extracted from the source OLTP systems prior to being published to the “warehouse” where it is visible to end users.
2. Data in the staging area is NOT visible to end users for queries, reports or analysis of any kind. It does not hold completed data ready for querying.
3. It may hold intermediate results, (if data is pipelined through a process)
4. Equally it may hold “state” data – the keys of the data held on the warehouse, and used to detect whether incoming data includes New or Updated rows. (Or deleted for that matter).
5. It is likely to be equal in size (or maybe larger) than the “presentation area” itself.
6. Although the “state” data – eg. Last sequence loaded may be backed up, much of the staging area data is automatically replaced during the ETL load processes, and can with care avoid adding to the backup effort. The presentation area however, may need backup in many cases.
7. It may include some metadata, which may be used by analysts or operators monitoring the state of the previous loads (eg. audit information, summary totals of rows loaded etc).
8. It’s likely to hold details of “rejected” entries – data which has failed quality tests, and may need correction and re-submission to the ETL process.
9. It’s likely to have few indexes (compared to the “presentation area”), and hold data in a quite normalised form. The presentation area (the bit the end users see), is by comparison likely to be more highly indexed (mainly bitmap indexes), with highly denormalised tables (the Dimension tables anyway).

The staging area exists to be a separate “back room“ or “engine room” of the warehouse where the data can be transformed, corrected and prepared for the warehouse.

It should ONLY be accessible to the ETL processes working on the data, or administrators monitoring or managing the ETL process.

In summary. A typical warehouse generally has three distinct areas:-
1. Several source systems which provide data. This can include databases (Oracle, SQL Server, Sybase etc) or files or spreadsheets
2. A single “staging area” which may use one or more database schemas or file stores (depending upon warehouse load volumes).
3. One or more “visible” data marts or a single “warehouse presentation area” where data is made visible to end user queries. This is what many people think of as the warehouse – although the entire system is the warehouse – it depends upon your perspective.

The “staging area” is the middle bit.

Staging area is place where you hold temporary tables on data warehouse server. Staging tables are connected to work area or fact tables. We basically need staging area to hold the data and perform data cleansing and merging before loading the data into warehouse.

What is the methodology and process followed for ETL testing in Data warehouse environment?

Like ETL SPEC they create a document containing the source table (Schema name) and a target table (another schema name) with the logic used in transforming source to target. We have to write database query with the logic contained in the document using source schema and take its output. Now write a simple select statement in the target schema and take its output. Compare the two outputs if they are same well and fine else it's a bug.

Database knowledge is a must for ETL testing.

What are the things to consider while testing ETL ?

The process of Testing the web based application and ETL application is quit diffrent.the major difference is in web based application we test the GUI part of the applicaytion as well as the main functional tesitng.but as it in ETL first

We have to understand the source structure like how many records are comming from source and how many records are loaded in to the target this is the basic motivation for testing the ETL. then how many records are rejecting and waht is the reason for rejecting.

Second we have to test the Back-end data driven test.

We have to test ETL components by execuitng SQL PL/SQL queyries.

We have to test the mapping naming convertion is done with respect to SRS.


Things to be considered :
1.Check we can get the existing data
2.Check we can clean up the data
3.Check we can add new data
4.Check we can merge data
5.Check for the limitation of the data
6.Check for the security purpose of using data
7.Check whether it is overlimited how much time we needed to get from the extraction

ETL CHANNEL

Extract, transform and load (ETL) is the core process of data integration and is typically associated with data warehousing. ETL tools extract data from a chosen source(s), transform it into new formats according to business rules, and then load it into target data structure(s). Managing rules and processes for the increasing diversity of data sources and high volumes of data processed that ETL must accommodate, make management, performance and cost the primary and challenges for users. The traditional ETL approach requires users to map each physical data item with a unique metadata description; newer ETL tools allow the user to create an abstraction layer of common business definitions and map all similar data items to the same definition before applying target-specific business rules, isolating business rules from data and allowing easier ETL management.

ETL Testing

Extract, Transform and Load (ETL)

General goals of testing an ETL application:
1. Data completeness. Ensures that all expected data is loaded.

2. Data transformation. Ensures that all data is transformed correctly according to business rules and/or design specifications.

3. Data quality. Ensures that the ETL application correctly rejects, substitutes default values, corrects or ignores and reports invalid data.

4. Performance and scalability. Ensures that data loads and queries perform within expected time frames and that the technical architecture is scalable.

5. Integration testing. Ensures that the ETL process functions well with other upstream and downstream processes.

6. User-acceptance testing. Ensures the solution meets users' current expectations and anticipates their future expectations.

7. Regression testing. Ensures existing functionality remains intact each time a new release of code is completed.

For more details please visit ETL Testing

Infrastructure as a Service (IaaS)

IaaS provides and mantains the underlying hardware, operating system and network Infrastructure resources and provides it in a virtualiced, easy to manage comoditized way. IaaS doesn’t care about the application at all.

IaaS is the base of the Cloud Computing paradigm, many people confuse CC with IaaS, thers just use the term Cloud Computing when they are in fact talking about IaaS. IaaS has also been referred to as "Everything as a Service" and "Hardware as a Service".

IaaS offers CPU, memory, storage, networking and security as a package. IaaS is the virtual machine in the sky.
With IaaS, you can choose from a range of predefined virtual machines and load packaged operating system images to it.
Well known and whidely trusted IaaS providers that offer services to the general public are: Amazon, Joyent, GoGrid and FlexiScale and Rackspace Cloud.

Amazon is probably the best known of the providers, Joyent is also huge and hosts some Facebook applications and the the social network LinkedIn, among others.

By moving your infrastructure to "the cloud", you have the ability to scale as if you owned your own hardware and data center (which is not realistic with a traditional hosting provider) but you keep the upfront costs to a minimum.


Benefits of IaaS:
1. Ability to scale on demand, instantly.
2. Per Hour billing, you only pay for what you use.
3. Ideal for startup business, where one of the most difficult things to do is keep capital expenditures under control.

Database as a Service (DaaS)

A new emerging option called database-as-a-service (DaaS) hosts databases in the cloud and is a good fit for some new apps. Amazon, Google, IBM, Microsoft, Oracle, and Saleforce.com as well as small innovators such as EnterpriseDB, LongJump, and Elastra are all targeting the DaaS market. Although most of today's DaaS solutions are very simple, in the next two to three years, more sophisticated offerings will evolve to support larger and more complex apps.

What Is DaaS?
DaaS provides traditional database features, typically data definition, storage and retrieval, on a subscription basis over the web. To subscribers DaaS appears as a black box supporting logical data operations, and logical data stores where customers can only see their organization's data. Physical access is seen as a security risk and thus it is not available. As with SaaS, DaaS vendors build and manage data centers incorporating best practices in security, back-up, recovery and customer support. Data services typically are provided as SOAP or REST APIs allowing users to define data structures, perform CRUD operations, manage entitlements and query the database using a subset of standard SQL.

Software as a service (SaaS)

Software as a service (SaaS, typically pronounced [sæs]), sometimes referred to as "software on demand," is software that is deployed over the internet and/or is deployed to run behind a firewall on a local area network or personal computer. With SaaS, a provider licenses an application to customers as a service on demand, through a subscription or a "pay-as-you-go" model.

SaaS was initially widely deployed for sales force automation and Customer Relationship Management (CRM). Now, it has become commonplace for many business tasks, including computerized billing, invoicing, human resource management, financials, content management, collaboration, document management, and service desk management.

Cloud Computing

Cloud computing conceptual diagram

Upcoming Technology

Following are the few upcoming technologies -

1)Cloud computing,
2)SaaS(Software as a Service),
3)DaaS(Database as a Service),
4)Platform as-a-Service (PaaS),
5)IaaS(Infrastructure as a Service (IaaS)),
6)IDM(Identity Management)

Types of Cloud Testing

The following testing types are applicable in general for Cloud testing.

Cloud testing: attracting demand

Cloud Testing is a form of software testing wherein testing is done using resources, machines or servers from the cloud infrastructure. Besides, the entire testing environments can be obtained from the cloud on-demand at a cost that is practical and reasonable due to the pay-for-use nature of cloud computing and with a lead-time that is near impossible within a company’s own data center.

Initially, this concept took shape when companies started using numerous machines booted up in the cloud in order to simulate web traffic and carry out performance tests on Web sites. Now remote machines in the cloud are used to provide a common ground for testers to test and developers to isolate and resolve the observed software defects.

Apparently, cloud testing has traditionally been used to refer to load and performance testing of Web sites. However, with increasing maturity of technology, all kinds of enterprise software can be tested for functional and performance issues before going in for full fledged enterprise deployment.

For more information please visit : Cloud testing: attracting demand

What Cloud Testing offers

Cloud Testing offers services that allow developers, testers and website managers to test their websites using industry standard frameworks and real browsers. Cloud Testing provides this using a SaaS (Software as a Service) model. There’s no need to invest in any hardware, software or consultancy.



For more information please visit below link :
What Cloud Testing offers

Cloud Testing

Cloud Testing is a form of software testing in which Web applications that leverage Cloud computing environments (“cloud”) seek to simulate real-world user traffic as a means of load testing and stress testing web sites

Testing in the cloud is often discussed in the context of performance or load tests against cloud-based applications. However, all types of software application tests, be they performance, functionality, usability, etc., are eligible to be referred to as 'cloud testing'

'The testing entity is targeting an application which resides on a third-party computing platform and is accessing that platform across the internet.'

Leading cloud computing service providers include, among others, Amazon, 3-terra, Skytap, and SOASTA. Some keys to successful testing in the cloud include
1. understanding a platform provider's elasticity model/dynamic configuration method,
2. staying abreast of the provider's evolving monitoring services and Service Level Agreements (SLAs),
3. potentially engaging the service provider as an on-going operations partner if producing commercial off-the-shelf (COTS) software, and
4. being willing to be used as a case study by the cloud service provider. The latter may lead to cost reductions.