Dataiku vs. ThoughtSpot

Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.

Incentivized

It is well suited when the same data is consumed by many different people with different analytics and visualization requirements because, if you have the data available in ThoughtSpot, every user can prepare different views. Also, it is a good reporting tool, you can get rid of slides if you have a good dashboard prepared, gaining flexibility and agility.

Incentivized

• The intuitiveness of this tool is very good.
• Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visuals
• The way you can control things, the set of APIs gives a lot of flexibility to a developer.

Incentivized

• Beautiful visualizations. The visuals are distinct, clean, and easy to discern from one another.
• Intelligent querying functionality. When looking to manipulate the data, the search function makes it easy to manipulate the features in the data, along with aggregating them in the way you'd like.
• Embedding! It has been a smooth process thus far for our product & technical teams to work with ThoughtSpot and bring it into our product.

Incentivized

• End product deployment.

Incentivized

• It would be great if ThoughtSpot can add the feature to filter by clicking on visualizations. i.e if I click on a particular data point in the chart if the full dashboard can filter just for that particular data point.
• Color coding the heatmap with different colors like green to orange to red.

Incentivized

I give it just waiting because passport is brilliant and it has helped our organisation In advancing to the next stage in the age of AI. It has allowed or non-tech people to better service and clients in a cost-effective way. George port has allowed us to create new products for us and for our clients increasing our revenue streams and reducing clients churn

Incentivized

As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.

Incentivized

The rating is because of the ease of use of the interface as it has a no code interface that makes it easy to setup data pipelines without extensive programming. Cloud native integration: It integrates seamlessly with cloud based data warehouses. Automated data loading, Scalability, Cost Effective, Transformations, Data Governance and security.

Incentivized

it's available unless there is a server or system update etc. sometimes the timing of this is bad (for example during a month end close)

Incentivized

It does what it is supposed to. Would be nice to have a bit more insights

Incentivized

The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.

Incentivized

I give it this meeting because the team is not only help able to help us in the current solutions but also amazing and taking feedback and feeding it back to their development team which includes more products and features into ThoughtSpot

Incentivized

inhouse in-person training. Took a bit to long to get the basics.

Incentivized

poor instructions

Incentivized

Understand use case and model and design accordingly

Incentivized

Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.

Incentivized

We also explored Tableau Ask Data. Tableau is our standard for BI in our organization. We want to use the smallest amount of tools in our company to have the best adaption. ThoughSpot will fill a few gaps that we have with our current set up and will also enhance out offering for our employees in the transition of being more data driven within in near future

Incentivized

Because it is very reliable, inside the situation, we need strong internet connection to access a lot of data but easily never had any downtime except during the upgrades

Incentivized

• Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.
• Platform also ease tracking of data processing workflow, unlike Excel.
• Build-in data visualizations covers many use cases with minimal customization; time saver.

Incentivized

• Time to market ROI is massive vs hiring the full-time dedicated team to build and maintain a frontend multi-tenant SaaS data viz product.
• It will be interesting to see over time how the advanced features play out in terms of usability and end value, such as Natural Search, which we are very excited about, and the machine learning tools.

Incentivized