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Matillion Interview Questions for 2024: What’s New and What’s Important
Are you about to start your career in Matillion as a Cloud ETL developer and looking for the right material to prepare for your interview? Alright, you have come to the exact place! We have gathered a list of frequently asked Matillion Interview questions and answers based on the suggestion of ETL industry experts. Preparing all these interview questions would surely help you in acquiring knowledge to clear Matillion interviews in the very first attempt.
Frequently asked Matillion Interview questions and answers
1) Why do we need ETL tools?
Every single day organizations create lots of data in all areas of their businesses. This data holds valuable insights that help organizations in reducing inefficiencies, increasing revenue, reduce cost, find new opportunities, and much more. In order to achieve these benefits, the data should be manipulated and transformed to support modern analytics.
ETL tools play an essential role in bringing the right insights to the table. Organizations use ETL tools to collect, read, and transform huge volumes of raw data from different business sources. After transformation, the data gets loaded into a single data store, database, or data warehouse for easy access.
2) What is Matillion?
Matillion is an advanced ETL/ELT tool natively built for supporting cloud database platforms which include Snowflake, Google BigQuery, Amazon Redshift, and Azure Synapse. It comes with an innovative browser-based UI and offers powerful ETL/ELT functionality.
Matillion software comes with 20+ components to execute various tasks such as Data read, write and join. You can build powerful and simplified ETL systems and schedule ETL jobs using this advanced Matillion ETL tool. Matillion supports processing millions of rows in seconds with real-time feedback.
If you wish to learn real-time Matillion ETL skills and get into your dream job
with great placement assistance,then check out our expert’s designed
Matillion Training.
3) What is Cloud ELT?
The word ELT is abbreviated as Extract, Load and Transform and it is a bit different from traditional ETL. Cloud ELT has been designed to match the cloud data warehouse requirements. It’s capabilities allow it to transform large volumes of data in minutes instead of weeks or months.
The Cloud ELT utilizes the cloud environment capabilities to transform data. The modern capabilities of Cloud ELT support organizations with real-time data and help them in making data-driven decisions.
4) What are the key features of Matillion?
Following are the features of Matillion features:
- Advanced drag-and-drop user interface.
- Push-down ELT technology uses cloud environment power to process millions of rows in seconds.
- Supports organizations with options like Live feedback, data preview, and validation.
- Offers advanced collaboration capabilities
- Comes with 25 admin menu options to simplify administration.
- Streamlines your way to connect with other data sources with 50 plus connectors.
- In-clint support
- Simple UI and basic functions allow you to build jobs in minutes.
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5) What are the data objects in Matillion?
Data objects in a database are used for storing reference data. As a part of the ETL process, Matillion often interacts with the database objects. Following are the various database objects Matillion works with:
- Tables
- Views
- Indexes
- Clusters
- Sequences
- Synonyms
6) What is JSON?
JSON stands for JavaScript Object Notation and it is designed to hold the structured data to be used in JavaScript. Examples of structured data include names, addresses, dates, location, etc. JSON is a popular way of sending data for Web APIs.
7) What is XML?
XML stands for eXtensible Markup Language. It stores the structured data. XML uses tags that work similar to HTML and the tag name must only be numbers, letters, and underscores. XML was designed in such a way to understand by humans and machines. JSON and XML are open standard file formats and available publicly.
8) How does Matillion work with JSON and XML files?
Matillion comes with an advanced component to handle JSON and XML files. Matillion’s Extract Nested Data component flattens XML and JSON files into rows. It extracts and loads data from many XML and JSON-based REST APIs.
9) How does data loading work using Matillion?
Data loading is one of the major tasks performed by Matillion. It is often used to load data into the target data warehouse platform. Matillion ETL streamlines the data loading process by offering a wide range of data connector components. Connectors eliminate the hard work associated with the data movement process from the data origin to destination.
10) Explain about Matillion connectors?
Matillion is highly flexible and comes with a wide array of pre-built data source connectors. You can also build customized connectors in Matillion. Using these connectors in Matillion you can seamlessly connect to any REST API source system and ingest data into your targeted cloud data warehouse.
11) How does Matillion load data into different cloud data warehouse platforms?
Matillion is an advanced cloud ETL tool that seamlessly connects with a wide range of data sources which include databases, cloud storage services, and many other services across the internet of things. It connects with a wide range of sources and passes the data into targeted cloud data warehouse platforms such as Snowflake, Google BigQuery, Amazon Redshift, or Microsoft Synapse.
12) What are the different data load types in Matillion?
Following are the two different data loading types in Matillion:
- Historical or Initial load
- Incremental load
Let’s understand each in detail:
Historial or Initial Load:
This process helps users to extract the data from a predefined point of time. You can use this process to extract historical data based on your requirement or use case. Historical data is typically used for trend analysis. For example: to analyze the sales across multiple years.
Incremental data Load:
This is the process where targeted data warehouse platforms are added with the latest information from the sources and refreshed to provide the latest info to the users. This process largely depends on the ability to identify changes in data sources. Incremental columns are being used to identify the latest record loaded. The Incremental ETL process can be scheduled based on your requirement. It may be daily, weekly, or monthly.
13) What are the different databases supported by Matillion?
A database is defined as a group of relevant data stored and accessed from a computer system. A database management system is a type of software that allows the users to access and manipulate data stored in a database. Matillion supports a wide range of databases and supports the users in loading data from connectors and transforms data.
Databases are broadly categorized into two segments which are SQL and NoSQL but there are many other databases that are unique in performing certain activities.
Following are the different types of databases supported by Matillion:
- Relational databases
- NoSQL databases
- Graph databases
- Hierarchical databases
- Object-oriented databases
14) What are the cloud data warehouse platforms supported by Matillion?
Matillion supports data migration to five data warehouse platforms which are as follows:
- Snowflake
- Amazon Redshift
- Synapse
- Google BigQuery
- Delta Lake
15) What is Audit log in Matillion?
The Audit log is defined as a list of significant activities within a Matillion Instance.
16) Name a few variables supported by Matillion?
Following are the different variables supported by Matillion:
- Environment variables
- Job variables
- Automatic variables
- Grid variables
17) What are the different Transform components in Matillion?
Following are the list of transform components one can use to transform data in Matillion:
- Aggregate Component
- Calculator Component
- Assert View Component
- Construct Struct Component
- Convert Type Component
- Construct Variant
- Delete Rows Component
- Distinct Component
- Detect Changes Component
- Extract Nested Data
- First-Last Component
- Filter Component
- Flatten Variant Component
- Map Values Component
- Lead-Lag Component
- Pivot component
- Rename Component
- Rank Component
- Replicate Component
- SQL Component
- Split Field Component
- Transpose Columns Component
- Window Calculation Component
- Transpose Rows Component
- Unpivot Component
18) What are the join components in Matillion?
Following are the join components available in Matillion:
- Join Component
- Intersect Component
- Unite Component
19) What are Read components available in Matillion?
Following are the different read components available in Matillion:
- Fixed Flow Component
- Multi-Table Input Component
- Generate Sequence Component
- Table Input Component
- Stream Input
- Wildcard Table Input
20) What are the Matillion Read components?
Following are the Matillion Read Components:
- Fixed Flow Component
- Generate Sequence Component
- Multi-Table Input Component
- Stream Input
- Table Input Component
- Wildcard Table Input
21) What is the use of Matillion ETL API?
The Matillion ETL API has been designed to streamline tasks such as simplify interactions, improve functionality performance, handle high volume data transfers, and interacting with Matillion programmatically. One can access the API service using the Uniform Resource Identifier.
22) What is cURL?
A cURL is a command-line tool used in Matillion to transfer data via URLs or endpoints. In the word cURL, the letter ‘C’ stands for Client.
Conclusion:
Hope you have enjoyed reading these Matillion ETL interview questions and answers. These are some of the commonly asked questions in any Matillion interview, preparing these questions will help you clear any interview. We are going to add more questions in the near future, so stay tuned to this blog for the latest questions. Happy reading!
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