ETL Testing and Informatica Training

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ETL Testing and Informatica Training
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Online Trainings
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Pune
- Monday to Friday
                                         -  Vishrantwadi, Pune,Maharashtra - 411 015

Pune
- Weekends
                                         -  Hinjewadi, Pune,Maharashtra - 411 057

Bangalore

- Weekends
                                         -  Kasturi Nagar,Nr Tin Factory,Bangalore - 43

Hyderabad
- Weekends
                                         -  Ameerpet,Hyderabad

Data Transformation Test

Data transformation test:

1.It’s a process of converting,cleansing,scrubbing,merging the data into required business format.

2.Validating that the data is transformed correctly or not,based on the business rules/business requirements,

Business rules/requirements validating can be the most complex and important part of ETL testing. 

3.An ETL application(i.e.Informatica,Datastage..etc) with significant transformation logic between source and target,where test should be make sure that the datatype of each column of each table is as per the functional and mapping specifications,If no specific details are mentioned in functional and mapping specifications about the tables/schema's then test should be make sure on the below concerns:

a)The datatype of source column and destination column(Target column) are same or not.

b)The destination column length is equal to or greater than the source column length.

c)Validation should be done that all the data specified gets extracted.

d)Test should include the check to see that the transformation and cleansing process are working correctly.

e)Make sure that all the types of data transformations are working and meeting the FS/MS and Business requirements/rules.

The following types of data transformation makes place in staging

1. Data Cleansing 

2. Data Scrubbing  

3. Data Aggregation  

4. Data Merging 

Data Completeness Test

1.Data completeness test are designed to verify that all the expected data loads into the DWH.

2.It includes running detailed tests to verify that all records,all fields and full contents of each field are loaded correctly or not.

3.Strategies to consider includes:

a)Record counts must compared between source and the target data.

b)Comparing record counts between source and data loaded to the warehouse (Target) and also rejected records in warehouse (Target).

c)Comparing unique values of key fields between source data and data loaded to the warehouse (Target) column mapping from the source or stage.

4.Populating the full contents of each field to validate that have no truncation occurs at any step in the process for example if the source data fields is having string(30) and make sure that to test it with 30 characters.

Test Strategy for ETL Testing / Standard Tests for ETL Testing

There will be some standard tests for DWH that should be carried out as part of testing for every DWH Project.

These are Strategies for testing ETL Applications are Identified as below:

1)      Data Completeness Testing

2)      Data Transformation Testing

3)      Data Quality Testing

4)      Initial Load / Full Load Testing

5)      Incremental Load Testing

6)      Presentation Layer Testing /  BI Testing / Report Testing

7)      Integration Testing / System Integration Testing / SIT

8)      Load and Performance Testing

9)      UAT Testing / User Acceptance Testing

10)   Regression Testing

                     High Level Description

    Data Completeness Testing             -  

Ensures that all expected data is loaded

       Data Transformation Testing            - 

 Ensures that all data is transformed correctly according to business rules

Data Quality Testing -

Ensure that the etl applications correctly rejects,substitutes the default values and reports invalid data

 Initial Load / Full Load Testing -

       Ensures that all the very first time data loaded correctly and als ensure the truncating process

Incremental Load Testing -

       Ensures that after first load all data is getting updating maintaining versioning and inserting new records  properly

  Presentation Layer Testing /  BI Testing / Report Testing  -

Testing BI Reports in DWH testing and comparing data correctness from DWH data and Reports

Integration Testing / System Integration Testing / SIT  -

Ensure that the ETL process functions with other upstream and downstream process

 Load and Performance Testing -

Ensure that the data loads and queries perform within expected Timeframes

 UAT Testing / User Acceptance Testing  -

Ensure that solution  and current expectations and anticipates full expectations

Regression Testing -

Ensures the new data updates have not broken any existing functionality or process.

ETL Testing Online Training & Course Content

ETL Testing Course Content by

Sandeep Manem  @ +91-9885320101, +91-8237320101

DataWare Housing Concepts:

·           What is Data Ware House?

·           Difference between OLTP and DataWare Housing

Data Acquisition

·           Data Extraction

·           Data Transformation

·           Data Loading

Data Marts

·           Dependent Data Mart

·           Independent Data Mart

Data Base Design

·           Star Schema

·           Snow Flake Schema

·           Fact constellation Schema

SCD(slowly changing dimension)

·           Type-1 SCD

·           Type-2 SCD

·           Type-3 SCD

Basic Concepts in SQL

·         Overview of ETL Tool Architecture

·         White Box and Black BOX Testing Functionality on Different Transformation Rules

Data Ware House Life Cycle

Different Types of Testing Techniques in ETL

·           Minus Queing

·           Count  Queing

  ETL Testing Concepts

1.Introduction

·            What is use of testing

·            What is quality & standards

·            Responsibilities of a ETL Tester

2.Software development life cycle

·            Waterfall model

·            V-model

·            Agile model & methodology

·            Prototype model

·            Spiral model

3.Testing methodologies

·            White box testing

·            Black box testing

·            Grey box testing

·            ETL Testing Work Flow Process

·            How to Prepare the  ETL Test Plan

·            How to design the Test cases in ETL Testing.

·            How to reporting the Bugs in ETL Testing ?

·            ETL Testing Responsibilities in DataStage, Informatica, Abinitio etc;

·            How to detect the bugs through database queries

·            ETL Performing Testing & Performing Tuning

Projects

Projects on Different Domains(Banking , Health Care, Telecom , Insurance)

OR

ETL Testing Course Content by

Sandeep Manem  @ +91-9885320101, +91-8237320101

Oracle Basics & Concepts

1. DBMS

2. RDBMS

3. DBMS vs RDBMS

4. Why Database Required

5. Different types of databases and difference

6. ASCII vs UNICODE

7. PL/SQL Basics

8. Oracle Architecture

9. Diff B/W Database & Files

10. OLTP

11. OLAP, ROLAP, MOLAP

12. METADATA

13. DDL,DML,DCL

14. BASIC ADMIN ACTIVITIES

15. DATATYPES

16. TABLES

17. SQL ,SUB QUERIES,CORELATED SUB QUERY

18. INNER QUERY,OUTER QUERY

19. FUNCTIONS AND TYPES AND IMPORTANCE

20. JOINS AND DIFFERENT TYPES

21. VIEWS n MATERIALIZED VIEWS

22. INDEX

23. CONSTRAINTS

24. REFERENTIAL INTEGRITY

25. PARTITIONING

26. PERFORMANCE TUNING

27. DIFFERENT TYPES OF TECHNIQES

28. DATABASE SCHEMA

DWH Concepts

1. WHAT IS DWH ?WHY WE REQUIRE THAT ?

2. DWH ARCHITECTURE

3. DATA MART and TYPES

4. DM vs DWH

5. DATA CLEANZING

6. DATA SCRUBING

7. DATA MASKING

8. NORMALIZATION

9. ODS

10. STG AREA

11. DSS

12. Diff B/w OLTP vs ODS,OLAP vs DSS

13. DIMENTION MODELING

14. DIMENSIONS

15. FACTS

16. AGGREGATES

17. DWH SCHEMA designing

18. STAR SCHEMA,SNOWFLAKE SCHEMA,GALAXY SCHEMA,FCS

19. SLOWLY CHANGING DIMENSIONS

20. SCD TYPE1,TYPE2,TYPE3

21. INITIAL LOAD

22. INCREMENTAL LOAD

23. FULL LOAD

24. CDC- change data capture

25. FAQ’S

ETL Testing Concepts

1. Introduction of ETL-Extract,Transform,Load

2. ETL TOOLS and Diff Types of ETL Tools

3. ETL ARCHITECTURE

4. ETL TESTING AND WHY WE REQUIRE

5. DIFFERENT ETL TOOLS ARCHITECTURES

6. SDLC and Methods/Models

7. STLC and Methods/Models

8. SDLC vs STLC

9. Reverse Engineering

10. QC(Quality Center and BugZilla)

11. Roles and Responsibilities

12. Minus,Duplicate,Count,Intersection,etc…

13. Detect Defects

14. Defects Logging and Reporting

15. How to prepare Queries very quickly with the help of mapping

16. Performance Tuning and Performance Testing,Report Testing,UI Testing

17. Quality and different standards that tester should follow,Why?

18. Testplan Preparation

19. Testcases Preparation

20. Preparation of Test data

21. Process Of ETL Testing

Testing Concepts

1. Whitebox Testing

2. Blackbox Testing

3. Gray Box Testing

4. Regression Testing

5. Smoke Testing vs Sanity Testing

6. User Testing

7. Unit testing

8. Intigration testing

9. Module testing

10. System testing

11. UAT

ETL Tool and Testing

1. Data Extract

2. Data Transform

3. Data Load

4. Import Source

5. Import Target

6. Mappings,Maplets

7. Workflows,Worklets

8. Transformations,Functionalities,Rules and Techniques

9. Import and Export

10. Coping and Rules

11. Queries Preparation based on Transformations

12. Importance of ETL Testing

13. Creating of Mappings,Sessions,Workflows

14. Running of Mappings,Sessions,Workflows

15. Analyzing of Mappings,Sessions,Workflows

16. Tasks and Types

Practice:

a. Testing scenarios, creation of test cases and scripts

b. Test case execution and defect tracking and reporting

c. Preparation of Test data

d. Practice ETL Testing with Real Time Scenarios and FAQ’s

e. Resume preparation.

ETL Testing Use Cases & Benefits

ETL Testing

ETL Testing in Less Time, With Greater Coverage, to Deliver Trusted Data

Much ETL testing today is done by SQL scripting or “eyeballing” of data on spreadsheets. These approaches to ETL testing are very time-consuming, error-prone, and seldom provide complete test coverage. Informatica Data Validation Option provides an ETL testing tool that can accelerate and automate ETL testing in both production environments and development & test. This means that you can deliver complete, repeatable and auditable test coverage in less time with no programming skills required. 

ETL Testing Use Cases

• Production Validation Testing (testing data before moving into production). Sometimes called “table balancing” or “production reconciliation,” this type of ETL testing is done on data as it is being moved into production systems. The data in your production systems has to be right in order to support your business decision making.  Informatica Data Validation Option provides the ETL testing automation and management capabilities to ensure that your production systems are not compromised by the data update process.
• Source to Target Testing (data is transformed). This type of ETL testing validates that the data values after a transformation are the expected data values. The Informatica Data Validation Option has a large set of pre-built operators to build this type of ETL testing with no programming skills required.
• Application Upgrades (same-to-same ETL testing). This type of ETL testing validates that the data coming from an older application or repository is exactly the same as the data in the new application or repository. Must of this type of ETL testing can be automatically generated, saving substantial test development time.

Benefits of ETL Testing with Data Validation Option

• Production Reconciliation. Informatica Data Validation Option provides automation and visibility for ETL testing, to ensure that you deliver trusted data in your production system updates.
• IT Developer Productivity.  50% to 90% less time and resources required to do ETL testing
• Data Integrity.  Comprehensive ETL testing coverage means lower business risk and greater confidence in the data.