Analysts spend the majority of their time on data preparation tasks, and it’s often the most tedious part of analysis. Whether you’re in the camp that loves data prep or would prefer to never have to cleanse another dataset again, Dataiku’s data preparation software features were designed to make data prep more efficient (and more bearable). Here are some of the most loved features within the platform.
1. Visual Flow to Make It Easier to Collaborate With Business Stakeholders and Data Science Teams
After providing analysis to business stakeholders or data teams, you’ll often receive questions on how you achieved your results. However, it can be difficult to explain all the different actions you took when wrangling, transforming, and cleansing a dataset while using spreadsheets and other data prep tools. With Dataiku, a visual flow is generated that shows each step of the data pipeline and can be used to easily explain transformations to stakeholders. This helps them better understand the steps behind your analysis so that they can gain more confidence in the output.
In this example of a visual flow in Dataiku, you can see each step in the data pipeline tagged by contributors, to more easily understand and explain what has been done to stakeholders.
2. Data Transformations to Speed Up Data Wrangling, Cleansing, and Transformation, No Matter Your Data Source or Language Used
Take complex spreadsheet functions and make them easier to perform on large datasets with the right data preparation software. Dataiku features 100+ built-in data transformers in the form of visual tools to help you quickly cleanse, join, aggregate, reshape, filter, geocode, and more. You can also see previews of each transformation before committing to functions. Additionally, each transformation is listed separately and can be grouped and labeled so that you (and others) can gain full visibility into everything that’s occurred.
You also have the option to write custom formulas in a spreadsheet-like language you’re familiar with and code (using SQL and beyond) for bespoke transformations if needed or desired. Use visual tools for maximum speed or write custom code for maximum flexibility — the choice is up to you.
An example of a prepare recipe in Dataiku in which you can apply native or custom transformations to a dataset, while organizing those transformations for better understanding.
3. Built-In Data Connectors to Easily Connect to Needed Data Sources
Easily access the data you need with dozens of data connectors to cloud storage technologies, on-premises databases, and enterprise applications to get the most out of data preparation software with Dataiku. No matter where it’s pulled from, data is uniformly presented in a familiar tabular view, perfect for analysts accustomed to spreadsheet data preparation tools. See a list oof supported connectors here.
4. Native Data Visualizations and Statistical Analysis
At any step in your data preparation, leverage 25+ types of built-in charts and visual statistical analyses to quickly explore data and identify patterns, without the need to export data into other tools. Then, easily shift to creating and deploying ML models or creating automated reporting dashboards for stakeholders — all from a single interface.
An example of native geospatial visualizations in Dataiku.
Dataiku can suggest statistical analysis that could be useful based on your data.
5. Share and Reuse Work to Save Time
Data prep software features in Dataiku like reusable and shareable project assets make it easy to find relevant past work and transfer knowledge. You’re able to copy/paste recipes, package workflows as reusable visual components, and publish curated reference data to a central feature store — saving time and building best practices for your team.
Dataiku's feature store where you can save and reuse features for data science or analytics projects.
6. Automation to Minimize Repetitive Data Preparation Software Tasks
Often you’ll find yourself working on recurring reports for stakeholders which have the same data prep steps each time. With Dataiku, you can automate the bulk of these common reporting tasks using scenarios.
Example of a Scenario which can be used to automate recurring data prep tasks.
Generative AI Data Preparation Assistants
With Dataiku’s Generative AI assistants, you can accelerate work and create transformations with simple instructions. Using features like AI Prepare, you can automatically generate steps in a prepare recipe with a prompt. AI Code assistant speeds up data prep tasks involving code, by allowing you to both generate code and ask questions about what existing code does, all without leaving Dataiku. Finally, AI Explain helps you summarize data transformations in flows so that you can easily understand what’s going on in a project, and quickly share this with others in the project description.
AI Prepare in the prepare recipe helps you quickly transform data with Generative AI.
Validating Data Quality
When preparing data, you want to be able to ensure your data is of high quality and that it fits the parameters of your use case. With visual indicators showing data issues in datasets, one-click summaries of column details, and robust data quality rules, you can ensure your insights are built on a solid foundation.
Easily validate data with data quality rules.