If you're looking for Pentaho BI Interview Questions for Experienced or Freshers, you are in right place. There are a lot of opportunities from many reputed companies in the world. According to research, Pentaho BI has a market share of about 3.7%. So, You still have the opportunity to move ahead in your career in Pentaho BI Development. Mindmajix offers Advanced Pentaho BI Interview Questions 2021 that help you in cracking your interview & acquire a dream career as Pentaho BI Developer.
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Below mentioned are the Top Frequently asked Pentaho Interview Questions and Answers that will help you to prepare for the Pentaho interview. Let's have a look at them.
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It addresses the blockades that block the organization’s ability to get value from all our data. Pentaho is discovered to ensure that each member of our team from developers to business users can easily convert data into value.
|Related Article: What is Pentaho|
The Pentaho BI Project is a current effort by the Open Source communal to provide groups with best-in-class solutions for their initiative Business Intelligence (BI) needs.
The Pentaho BI Project encompasses the following major application areas:
Yes, Pentaho is a trademark.
Pentaho Metadata is a piece of the Pentaho BI Platform designed to make it easier for users to access information in business terms.
With the help of Pentaho’s open-source metadata capabilities, administrators can outline a layer of abstraction that presents database information to business users in familiar business terms.
Pentaho Reporting Evaluation is a particular package of a subset of the Pentaho Reporting capabilities, designed for typical first-phase evaluation activities such as accessing sample data, creating and editing reports, and viewing and interacting with reports.
Multidimensional Expressions (MDX) is a query language for OLAP databases, much like SQL is a query language for relational databases. It is also a calculation language, with syntax similar to spreadsheet formulas.
A finite ordered list of elements is called a tuple.
The Cube will contain the following data:
It is not possible as in PDI transformations all of the steps run in parallel. So we can’t sequential them.
We can create a new conversion or close and re-open the ones we have loaded in Spoon.
There is a simple workaround available: change the data type with a Select Values step to “Integer” in the metadata tab. This converts it to 1 for “true” and 0 for “false”, just like MySQL expects.
This is not possible as in PDI transformations all the steps run in parallel. So we can’t sequential them. This would require architectural changes to PDI and sequential processing also result in very slow processing.
We can’t. if we have duplicate field names. Before PDI v2.5.0 we were able to force duplicate fields, but also only the first value of the duplicate fields could ever be used.
2. All build under the Java platform
Pentaho Dashboards give business users the critical information they need to understand and improve organizational performance.
Pentaho Reporting allows organizations to easily access, format, and deliver information to employees, customers, and partners.
Pentaho Schema Workbench offers a graphical edge for designing OLAP cubes for Pentaho Analysis.
Pentaho Data Mining used the Waikato Environment for Information Analysis to search for data for patterns. It has functions for data processing, regression analysis, classification methods, etc.
It is a visual, banded report writer. It has various features like using subreports, charts, and graphs, etc.
It is an entry-level tool for data manipulation.
A hierarchical navigation menu allows the user to come directly to a section of the site several levels below the top.
It is the technology that enables files to be transparently encrypted to secure personal data from attackers with physical access to the computer.
A repository is a storage location where we can store the data safely without any harmless.
ETL Tool is used to getting data from many source systems like RDBMS, SAP, etc., and convert them based on the user requirement. It is required when data float across many systems.
ETL is an extraction, transforming, loading process the steps are :
The metadata stored in the repository by associating the information with individual objects in the repository.
Snapshots are read-only copies of a master table located on a remote node that can be periodically refreshed to reflect changes made to the master table.
Data staging is actually a group of procedures used to prepare source system data for loading a data warehouse.
Data flow from source to target is called mapping.
It is a set of instruction which tells when and how to move data from respective source to target.
It is a set of instruction which tells the Informatica server how to execute the task.
It creates and configures the set of transformations.
A data warehouse is said to be a three-tier system where a middle system provides usable data in a secure way to end-users. Both sides of this middle system are the end-users and the back-end data stores.
ODS is an Operational Data Store that comes in between data warehouse and staging.
ETL Tool is used for extracting data from the legacy system and load it into the specified database with some processing of cleansing data.
OLAP Tool is used for the reporting process. Here data is available in the multidimensional model hence we can write a simple query to extract data from the database.
XML is an extensible markup language which defines a set of rule for encoding documents in both formats which is human-readable and machine-readable.
Informatica Powercenter 4.1, Informatica Powercenter 5.1, Powercenter Informatica 6.1.2, Informatica Powercenter 7.1.2, etc.
Abinitio, DataStage, Informatica, Cognos Decision Stream, etc
MDX is a multidimensional expression that is the main query language implemented by Mondrian.
It is a cube to view data where we can slice and dice the data. It has a time dimension, locations, and figures.
Several solutions exist:
It will look as follows:
Use a calculator step and use e.g. The NLV(A, B) operation as follows:
You can’t. PDI will complain in most cases if you have duplicate field names. Before PDI v2.5.0 you were able to force duplicate fields, but also only the first value of the duplicate fields could ever be used.
The catch is to specifically restrict the file list to the files inside the compressed collection. Some examples:
You have a file with the following structure:
To read each of these files in a File Input step:
You have a simpler file, fat-access.log.gz. You could use the Compression option of the File Input step to deal with this simple case, but if you wanted to use VFS instead, you would use the following specification:
Note: If you only wanted certain files in the tarball, you could certainly use a wildcard like access.log..* or something. .+ is the magic if you don’t want to specify the children's filenames. .* will not work because it will include the folder (i.e. tar:gz:/path/to/access.logs.tar.gz!/access.logs.tar!/ )
Finally, if you have a zip file with the following structure:
access.logs.zip/ a-root-access.log subdirectory1/ subdirectory-access.log.1 subdirectory-access.log.2 subdirectory2/ subdirectory-access.log.1 subdirectory-access.log.2
You might want to access all the files, in which case you’d use:
Note: For some reason, the .+ doesn’t work in the subdirectories, they still show the directory entries. :/
The spoon is the design interface for building ETL jobs and transformations. Spoon provides a drag-and-drop interface that allows you to graphically describe what you want to take place in your transformations. Transformations can then be executed locally within Spoon, on a dedicated Data Integration Server, or a cluster of servers.
The Data Integration Server is a dedicated ETL server whose primary functions are:
|Execution||Executes ETL jobs and transformations using the Pentaho Data Integration engine|
|Security||Allows you to manage users and roles (default security) or integrate security to your existing security providers such as LDAP or Active Directory|
|Content Management||Provides a centralized repository that allows you to manage your ETL jobs and transformations. This includes full revision history on content and features such as sharing and locking for collaborative development environments.|
|Scheduling||Provides the services allowing you to schedule and monitor activities on the Data Integration Server from within the Spoon design environment|
Pentaho Data Integration is composed of the following primary components:
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Ravindra Savaram is a Content Lead at Mindmajix.com. His passion lies in writing articles on the most popular IT platforms including Machine learning, DevOps, Data Science, Artificial Intelligence, RPA, Deep Learning, and so on. You can stay up to date on all these technologies by following him on LinkedIn and Twitter.
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