11/14/16

DB TESTING, ETL TESTING & BI TESTING

What is database testing?

Testing the backend databases like comparing   the actual results   with expected results.
Data base testing basically include the following.
1) Data validity testing.
2) Data Integrity testing
3) Performances related to database.
4) Testing of Procedure, triggers and functions.
       For doing data validity testing you should be good in SQL queries
       For data integrity testing you should know about referential integrity and different constraint.
       For performance related things you should have idea about the table structure and design.
       For testing Procedure triggers and functions you should be able to understand the same.

*******************************************************************************What is ETL TESTING?

ETL basically stands for Extract Transform Load - which simply implies the process where you extract data from Source Tables, transform them in to the desired format based on certain rules and finally load them onto Target tables. There are numerous tools that help you with ETL process - Informatica, Control-M being a few notable ones.

So ETL Testing implies - Testing this entire process using a tool or at table level with the help of test cases and Rules Mapping document. 

In ETL Testing, the following are validated -
1) Data File loads from Source system on to Source Tables.
2) The ETL Job that is designed to extract data from Source tables and then move them to staging tables. (Transform process)
3) Data validation within the Staging tables to check all Mapping Rules / Transformation Rules are followed.
4) Data Validation within Target tables to ensure data is present in required format and there is no data loss from Source to Target tables.

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What is Business Intelligence?

Business intelligence, or BI for short, is an umbrella term that refers to competencies, processes, technologies, applications and practices used to support evidence-based decision making in organizations. In the widest sense it can be defined as a collection of approaches for gathering, storing, analyzing and providing access to data that helps users to gain insights and make better fact-based business decisions.

BI used for?
Organizations use Business Intelligence to gain data-driven insights on anything related to business performance. It is used to understand and improve performance and to cut costs and identify new business opportunities, this can include, among many other things:

Ø  Analyzing customer behaviors, buying patterns and sales trends.
Ø  Measuring, tracking and predicting sales and financial performance
Ø  Budgeting and financial planning and forecasting
Ø  Tracking the performance of marketing campaigns
Ø  Optimizing processes and operational performance
Ø  Improving delivery and supply chain effectiveness
Ø  Web and e-commerce analytics
Ø  Customer relationship management
Ø  Risk analysis
Ø  Strategic value driver analysis
  
  
 

Basics of Business Intelligence

Gathering Data
Gathering data is concerned with collecting or accessing data which can then be used to inform decision making. Gathering data can come in many formats and basically refers to the automated measurement and collection of performance data. For example, these can come from transactional systems that keep logs of past transactions, point-of-sale systems, web site software, production systems that measure and track quality, etc. A major challenge of gathering data is making sure that the relevant data is collected in the right way at the right time. If the data quality is not controlled at the data gathering stage then it can harm the entire BI efforts that might follow – always remember the old adage - garbage in garbage out

Storing Data
Storing Data is concerned with making sure the data is filed and stored in appropriate ways to ensure it can be found and used for analysis and reporting. When storing data the same basic principles apply that you would use to store physical goods – say books in a library – you are trying to find the most logical structure that will allow you to easily find and use the data. The advantages of modern data-bases (often called data warehouses because of the large volumes of data) is that they allow multi-dimensional formats so you can store the same data under different categories – also called data marts or data-warehouse access layers. Like in the physical world, good data storage starts with the needs and requirements of the end users and a clear understanding of what they want to use the data for.

Analyzing Data
The next component of BI is analysing the data. Here we take the data that has been gathered and inspect, transform or model it in order to gain new insights that will support our business decision making. Data analysis comes in many different formats and approaches, both quantitative and qualitative. Analysis techniques includes the use of statistical tools, data mining approaches as well as visual analytics or even analysis of unstructured data such as text or pictures.

Providing Access
In order to support decision making the decision makers need to have access to the data. Access is needed to perform analysis or to view the results of the analysis. The former is provided by the latest software tools that allow end-users to perform data analysis while the latter is provided through reporting, dashboard and scorecard applications.


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