Exploratory Data Analysis
Dataiku saves time with quick visual analysis of columns, including the
distribution of values, top values, outliers, invalids, and overall statistics.
For categorical data, the visual analysis includes the distribution by value,
including the count and % of values for each value.
Charts and Graphs
With Dataiku, all users (technical or not) can create effective visualizations
to understand or share data insights across the team or organization.
Charting options include bar charts, lines, curves, stacked area layouts,
pie charts, donut layouts, boxplots, 2D-distribution, lift charts, tables,
scatter plots, and more.
Dataiku includes special handling for geospatial data, including specific
formats for data analysis and presentation.
Visual geocoding and decoding make it easy to create geo points or
extract location information like latitude and longitude for mapping. Geo-
join allows users to connect datasets based on geographic information.
Map-based analysis enables users to put geo data onto maps for analysis
Dataiku facilitates robust statistical analysis, including univariate and
bivariate analysis, with multiple available charts per column.
Statistical tests include fit distributions, fit curve, correlation matrix, PCA,
student t-test, Shapiro-Wilk normality test, two-sample Mood test, Two-
sample Kolmogorov-Smirnov test, One-way Anova test, Chi-square
independence test, and more.
Dashboards in Dataiku allow project owners to share information about
their projects with stakeholders across the company, including charts,
analysis, discussions, wikis, and more.
Dashboards are easy to build and view in Dataiku — they can be shared
with users across the organization in just a few clicks.
Integrations with Tableau, Qlik, and PowerBI
In addition to the native visualization and dashboarding functionality that
Dataiku provides out-of-the box, the platform also supports the use of
existing BI tools.
Dataiku integrates with leading BI platforms like Tableau, Qlik, and
PowerBI to ensure critical stakeholders and business users have the
information they need to create value from AI projects developed in