We performed a comparison between Google Cloud Datalab and Tableau based on real PeerSpot user reviews.
Find out in this report how the two Data Visualization solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."All of the features of this product are quite good."
"Google Cloud Datalab is very customizable."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The initial setup is simple."
"The product has the best features for analytical views and filters."
"There is a lot of APIs available, which means that Tableau can be customized to a large extent."
"I have found many of the self-service features valuable."
"The solution helps users create dashboards and analyze data without relying on IT or product teams."
"Tableau is very good in the front-end visualization compared to Power BI."
"The best use case for us is the solution's integration with Salesforce because we are also partners of Salesforce."
"Scheduled extract and the multiple connectors are fantastic!"
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"The product must be made more user-friendly."
"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
"The interface should be more user-friendly."
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"With Tableau, there is a gap in its ability to handle very large-scale data."
"There's no mature ETL tool in Tableau, which is quite a negative for them."
"They need to improve the icons and the filters, because they look too old, resembling Excel from 1997."
"The solution’s pricing could be improved."
"The integration with other program languages, like Python, needs to be better."
"The tool's OpenAI integration was announced last year. However, it is late. Tableau is a good solution for end customers. However, there are some concerns regarding the stability and performance of its server architecture, including SaaS services. The server side appears unstable, and performance issues are noticeable, often accompanied by unclear error messages."
"An advanced type of visualization is a bit tricky to create. It has something called a Calculated field, and that sometimes gets a bit difficult to use when you want to create an advanced type of visualization."
"It would be nice if we could export more raw data. Currently, there is a limit as to how much data you can export."
Google Cloud Datalab is ranked 20th in Data Visualization with 5 reviews while Tableau is ranked 1st in Data Visualization with 293 reviews. Google Cloud Datalab is rated 7.6, while Tableau is rated 8.4. The top reviewer of Google Cloud Datalab writes "Easy to setup, stable and easy to design data pipelines". On the other hand, the top reviewer of Tableau writes "Provides fast data access with in-memory extracts, makes it easy to create visualizations, and saves time". Google Cloud Datalab is most compared with Databricks, IBM SPSS Statistics, Cloudera Data Science Workbench, KNIME and Qlik Sense, whereas Tableau is most compared with Microsoft Power BI, Domo, Amazon QuickSight, SAS Visual Analytics and Databricks. See our Google Cloud Datalab vs. Tableau report.
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