20 Dataiku Interview Questions and Answers

Prepare for the types of questions you are likely to be asked when interviewing for a position where Dataiku will be used.

Dataiku is a data analysis and machine learning platform that allows users to develop predictive models and applications. As a result, it is a valuable skill for data scientists and software developers who want to work with data. If you are interviewing for a position that requires Dataiku, it is important to be prepared to answer questions about your experience and knowledge. In this article, we review some common Dataiku interview questions and provide tips on how to answer them.

Dataiku Interview Questions and Answers

Here are 20 commonly asked Dataiku interview questions and answers to prepare you for your interview:

1. What is Dataiku?

Dataiku is a data analysis and machine learning platform that enables users to build and share data applications without coding. Dataiku provides a visual interface for data preparation, machine learning, and predictive modeling.

2. Can you explain what a data flow is in context of Dataiku?

A data flow is a directed graph that represents the transformation of data from one format or structure to another. Data flows can be used to represent simple data pipelines, as well as more complex data processing workflows. In Dataiku, data flows are used to visually design and execute data transformation recipes.

3. How does Dataiku ensure that the code used for preparing datasets is robust, scalable, and secure?

Dataiku has a few different features to ensure that code is robust, scalable, and secure. First, Dataiku provides code review capabilities so that code can be peer reviewed before it is used in production. Second, Dataiku provides a platform for unit testing code so that code can be tested before it is deployed. Finally, Dataiku provides a secure environment for storing and sharing code so that only authorized users can access it.

4. Do you need to have any prior programming knowledge before using Dataiku? If yes, which ones do you recommend?

No, you don’t need to have any prior programming knowledge to use Dataiku. However, if you want to get the most out of the platform, then it would be helpful to know at least one programming language. The most popular programming languages used with Dataiku are Python and R.

5. Does Dataiku support Spark or Hadoop? What about other big data technologies like Hive, Sqoop, etc.?

Yes, Dataiku supports Spark and Hadoop. Dataiku also supports Hive, Sqoop, and other big data technologies.

6. What are some use cases of Dataiku?

Dataiku is a data analysis and machine learning platform that can be used for a variety of tasks such as data wrangling, predictive modeling, and data visualization. It can be used by data scientists, analysts, and business users alike. Some common use cases for Dataiku include:

– Performing exploratory data analysis to gain insights into data
– Building predictive models to forecast future events or trends
– Creating data visualizations to communicate findings to others
– Automating data-driven processes or workflows

7. What is your understanding of Machine Learning as it relates to Dataiku?

Machine learning is a process of teaching computers to make predictions or recommendations based on data. In the context of Dataiku, machine learning can be used to automatically analyze and process data in order to find patterns or trends. This can be used to make predictions about future data, or to recommend actions to take based on the data.

8. Why do you think Dataiku is better than other analytics tools available on the market? Especially those offered by Microsoft, IBM, and SAS?

Dataiku is better because it is more user-friendly and offers more flexibility when it comes to data analysis. With Dataiku, you don’t need to be a coding expert to be able to get insights from your data – which is not the case with most of the other tools on the market. Additionally, Dataiku integrates well with a wide range of technologies, which makes it easy to use in a variety of different environments.

9. Is there any way to import my existing models into Dataiku?

Yes, you can import your existing models into Dataiku by using the “Import” button in the “Models” tab.

10. Are there any limitations on the number of people who can collaborate on a project at once with Dataiku?

There are no limitations on the number of people who can collaborate on a project at once with Dataiku.

11. What is the process to schedule automation tasks with Dataiku?

The process to schedule automation tasks with Dataiku is to first create a task in the Task Manager. Then, you will need to specify the schedule for the task and finally, you will need to add the task to the Automation Scheduler.

12. Is it possible to integrate Python scripts with Dataiku projects?

Yes, it is possible to integrate Python scripts with Dataiku projects. This can be done through the use of the Python recipe, which is available in the recipe library.

13. What is a core plugin in the context of Dataiku?

A core plugin is a plugin that is bundled with the Dataiku installation and that 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?

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?

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?

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?

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?

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?

Yes, Dataiku provides free trials for its software.

20. What are some additional features available when using Dataiku on a cloud platform?

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.


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