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Important ETL Testing Interview Questions and Answers

ELT Testing Interview Questions

1. What is ETL?

In data warehousing architecture, ETL is an important component, which manages the data for any business process. ETL stands for Extract, Transform and Load. Extract does the process of reading data from a database. Transform does the converting of data into a format that could be appropriate for reporting and analysis. While, load does the process of writing the data into the target database.

2. Explain what are the ETL testing operations includes?

ETL testing includes:
  • Verify whether the data is transforming correctly according to business requirements.
  • Verify that the projected data is loaded into the data warehouse without any truncation and data loss.
  • Make sure that ETL application reports invalid data and replaces with default values.
  • Make sure that data loads at expected time frame to improve scalability and performance.

    3. Mention what are the types of data warehouse applications and what is the difference between data mining and data warehousing?

    The types of data warehouse applications are:
  • Info Processing.
  • Analytical Processing.
  • Data Mining. Data Mining: Data mining can be define as the process of remove hidden predictive information from large databases and interpret the data while data warehousing may make use of a data mine for analytical processing of the data in a faster way. Data warehousing: Data warehousing is the process of collecting data from multiple sources into one common repository

    4. What are the various tools used in ETL?

  • Cognos Decision Stream.
  • Oracle Warehouse Builder.
  • Business Objects XI.
  • SAS business warehouse.
  • SAS Enterprise ETL server.

    5. What is fact? What are the types of facts?

    It is a central component of a multi-dimensional model which contains the measures to be analysed. Facts are related to dimensions. Types of facts are:
  • Additive Facts.
  • Semi-additive Facts.
  • Non-additive Facts.

    6. Explain what are Cubes and OLAP Cubes?

    Cubes are data managing units comprised of fact tables and dimensions from the data warehouse. It produces multi-dimensional analysis.
    OLAP stands for Online Analytics Processing, and OLAP cube stores large data in muti-dimensional form for reporting purposes. It consists of facts called as measures categorized by dimensions.

    7. What is tracing level and what are the types?

  • Tracing level is the amount of data saved in the log files.
  • Tracing level are of two types. They are: Normal and Verbose.
  • Normal level explains the tracing level in a detailed manner while verbose explains the tracing levels at each and every row.

    8. What is Grain of Fact?

    Grain fact is the level at which the fact information is stored. It is also known as Fact Granularity

    9. What is transformation?

    A transformation is a repository object which generates, modifies or passes data. Transformation are of two types Active and Passive

    10. Explain the use of Lookup Transformation?

    The Lookup Transformation is useful for:
  • Getting a related value from a table using a column value.
  • Update slowly changing dimension table.
  • Verify whether records already exist in the table.

    11. Mention what are the advantage of using DataReader Destination Adapter?

    The advantage of using the DataReader Destination Adapter is that it populates an ADO recordset (consist of records and columns) in memory and exposes the data from the DataFlow task by implementing the DataReader interface, so that other application can consume the data.

    12. In case you have non-OLEDB (Object Linking and Embedding Database) source for the lookup what would you do?

    In case if you have non-OLEBD source for the lookup then you have to use Cache to load data and use it as source.

    13. In what case do you use dynamic cache and static cache in connected and unconnected transformations?

    We use dynamic cache and static cache in, Dynamic cache is used when you have to update master table and slowly changing dimensions (SCD) type 1 For flat files Static cache is used

    14. What is data source view?

    A data source view allows to define the relational schema which will be used in the analysis services databases. Rather than directly from data source objects, dimensions and cubes are created from data source views.

    15. How you can extract SAP data using Informatica?

    By the following ways you can extract SAP data using Informatica,
  • With the power connect option you extract SAP data using informatica.
  • Install and configure the PowerConnect tool.
  • Import the source into the Source Analyzer. Between Informatica and SAP Powerconnect act as a gateaway. The next step is to generate the ABAP code for the mapping then only informatica can pull data from SAP.
  • To connect and import sources from external systems Power Connect is used.

    16. Explain what staging area is and what is the purpose of a staging area?

    Data staging is an area where we hold the data for short-period on data warehouse server. Data staging includes following steps
  • Source data extraction and data transformation ( restructuring ).
  • Data transformation (data cleansing, value transformation ).
  • Surrogate key assignments.

    17. What is Bus Schema?

    For the various business process to identify the common dimensions, BUS schema is used. It comes with a conformed dimensions along with a standardized definition of information

    18. What is data purging?

    Data purging is a process of deleting data from data warehouse. It deletes junk data's like rows with null values or extra spaces.

    19. What are Schema Objects?

    Schema objects are the logical structure that directly refer to the databases data. Schema objects includes tables, views, sequence synonyms, indexes, clusters, functions packages and database links.

    20. Explain these terms Session, Worklet, Mapplet and Workflow?

    Mapplet : It creates sets of transformation.
    Worklet: It represents a specific set of tasks given.
    Workflow: It's a set of instructions that tell the server how to execute tasks.
    Session: it helps the server to shift data from sources to target with set of instruction.