Here are some top 20 Dataiku DSS interview questions along with their answers:
1. What is Dataiku DSS?
Ans: Dataiku Data Science Studio (DSS) is an advanced analytics and collaborative data science platform that allows users to build, deploy, and manage data pipelines, machine learning models, and data applications.
2. What are the main components of Dataiku DSS?
Ans: The main components of Dataiku DSS include:
- Visual Data Preparation: Allows users to explore, clean, and transform data visually.
- Visual Machine Learning: Enables the building and training of machine learning models using a drag-and-drop interface.
- Collaboration: Provides a collaborative environment for teams to work together on data projects.
- Deployment: Facilitates the deployment of models into production environments.
- Monitoring and Governance: Offers tools for monitoring and managing data and models.
3. What programming languages are supported in Dataiku DSS?
Ans: Dataiku DSS supports multiple programming languages, including Python, R, SQL, Hive, Pig, and Spark.
4. How can you integrate Dataiku DSS with external systems or tools?
Ans: Dataiku DSS provides various integration capabilities, such as APIs, connectors, and plugins, to connect with external systems or tools like databases, data warehouses, cloud platforms, and visualization tools.
5. How does Dataiku DSS handle version control and collaboration?
Ans: Dataiku DSS has built-in version control and collaboration features. It allows multiple users to work on the same project simultaneously, tracks changes made to workflows and models, and provides tools for merging changes and resolving conflicts.
6. What is the role of Dataiku DSS in data preparation?
Ans: Dataiku DSS offers visual data preparation capabilities, allowing users to perform tasks like data cleansing, transformation, feature engineering, and data enrichment using a user-friendly interface, without writing code.
7. How does Dataiku DSS support machine learning?
Ans: Dataiku DSS provides a visual machine-learning interface where users can build and train machine-learning models using a drag-and-drop approach. It supports a wide range of algorithms, feature selection techniques, and model evaluation methods.
8. Can you schedule and automate workflows in Dataiku DSS?
Ans: Yes, Dataiku DSS allows users to schedule and automate workflows using its built-in scheduler. Workflows can be triggered based on specific events, time intervals, or data availability.
9. Does Dataiku DSS support big data processing?
Ans: Yes, Dataiku DSS supports big data processing by integrating with distributed processing frameworks like Apache Spark. It can handle large datasets and perform distributed computations for efficient data processing.
10. How does Dataiku DSS facilitate model deployment?
Ans: Dataiku DSS provides deployment capabilities for models, allowing users to deploy models as REST APIs, batch-scoring jobs, or real-time predictions within applications or services.
11. How does Dataiku DSS ensure data governance and security?
Ans: Dataiku DSS offers features for data governance and security, such as role-based access control, data lineage tracking, auditing, and encryption of sensitive data. It helps organizations comply with data privacy and security regulations.
12. Can Dataiku DSS integrate with cloud platforms?
Ans: Yes, Dataiku DSS can integrate with major cloud platforms like AWS, Azure, and GCP, enabling users to leverage cloud services for storage, processing, and scalability.
13. What is a core plugin in the context of Dataiku?
Ans: A core plugin is a plugin that is bundled with the Dataiku installation and is maintained by the Dataiku team. Core plugins provide essential functionality for working with data in Dataiku, such as connecting to data sources, performing data preparation tasks, and creating visualizations.
14. What is the difference between an API client and a web server plug-in?
Ans: An API client is a piece of software that makes it easy for developers to access a particular API. A web server plug-in is a piece of software that allows a web server to interact with a particular API.
15. How would you go about converting a Python notebook into a Dataiku workflow?
Ans: You can convert a Python notebook into a Dataiku workflow by going to the ‘Workflows’ tab, clicking on the ‘+’ icon, and selecting ‘Notebook to Workflow’.
16. How can a user save their work in Dataiku?
Ans: A user can save their work in Dataiku by clicking on the “Save” button in the top right corner of the screen.
17. What is the purpose of custom recipes in Dataiku?
Ans: Custom recipes allow you to create your own specific recipe that is not available in the standard library. This is useful if you want to create a recipe that is not available in Dataiku or if you want to modify an existing recipe to better suit your needs.
18. For how long do Dataiku customers need to commit to Dataiku’s services? Is it flexible or fixed?
Ans: Dataiku’s services are offered on a subscription basis, so customers can commit for as long as they need the services. There is some flexibility in the subscription terms, so customers can cancel or change their subscription at any time.
19. Does Dataiku provide free trials?
Ans: Yes, Dataiku provides free trials for its software.
20. What are some additional features available when using Dataiku on a cloud platform?
Ans: When using Dataiku on a cloud platform, you have access to additional features such as scalability, high availability, and disaster recovery. You also have the ability to take advantage of cloud-specific features such as storage and networking.