Visual analytics have become critical to the way that most of us do business. Reports and dashboards are used to review metrics, summaries, and forecasts, as well as to track trends. During the 2021 Product Days, Dataiku COO Romain Fouache outlined three of the many significant capabilities that Dataiku offers to help businesses support and deliver strong analytics. Read over these carefully, as one (or multiple!) of them could be the key(s) to your next successful data science project.
DataOps: Building a Strong Foundation
Data analytics is only as relevant as the data coming in, thus it is extremely important to efficiently clean and prepare data before sending it through processes and modeling. Data can be plain wrong, irrelevant, missing, or just stale. Data pipelines are the plumbing that take in the raw data and transform it into valuable outputs. This could mean combining data sources, cleaning up the data, or even transforming the data. Each time you want to get a new insight, a data pipeline runs in the background. 
Another aspect of DataOps is capturing when something goes wrong. Having automatic data quality checks on quality in place, like Dataiku offers, helps ensure that your data pipelines are creating high quality datasets that you can trust. DataOps is ultimately the foundation of any successful use of data at scale.
Dashboards: Ensuring Relevance and Quality of Data
Once you have data that you can trust, you want to put that data to work either in a descriptive or a predictive analytics mode. Data visualization dashboards take descriptive analytics to the next level by enabling ad hoc, interactive exploration of patterns and providing business context to drive a more complete understanding of data insights. Additionally, data visualization dashboards are regularly updated according to dataset modifications, ensuring the relevance and quality of data-driven insights. 
- It allows you to directly explore and understand your data while you are working on it.
- It is an instant way to share insights with your teams and encourage alignment across users from different areas.
- It enables you to build trust with business stakeholders by helping them understand your analyses and showing them what is going on.
- All of this is done in only a matter of minutes!
Plus, Dataiku facilitates interactive statistics via a dedicated interface for performing exploratory data analysis (EDA) on datasets, including univariate and bivariate analysis, hypothesis testing, and dimensionality reduction. Statistics cards can then be published to dashboards so others can validate the analysis.
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 (e.g., Tableau, Qlik, and PowerBI).
Applications: Further Increasing Data Democratization
For many people, the end of an analytics project consists of a dashboard or a model. How can organizations take this a bit further and use their dashboards and/or models in their day to day activities?
Business users need a no-code or low-code way to leverage the work that has been done. That is ultimately what applications do: They give business users a way not just to interact with a dashboard, but to actually interact with the way the data is processed.