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."The infrastructure is highly reliable and efficient, contributing to a positive experience."
"Google Cloud Datalab is very customizable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The APIs are valuable."
"All of the features of this product are quite good."
"Data Interpreter: Which can identify issues or potential errors with your imported data."
"Our customers love the visual capabilities on top of it and the ability to explain and get the required data. There is no other product like Tableau in the business intelligence and analytics space."
"The most valuable feature is the drag and drop, then the simplicity to build dashboards which allows us to provide more usable data to our customers."
"Tableau is a fantastic tool that provides impressive dashboards and customized reports."
"The data visualization piece is most valuable. We do ad-hoc analysis or one-time shot things, but there are things that we have to track every single day. When our management and our customers want to see how things are changing, the dashboarding provides that information. Tableau is key in providing that data on a refresh basis. We use a data blending tool that pumps the data into Tableau, and we just schedule it to run every single day. So, the automation of the data and being able to present it to people who are interested are the most valuable features."
"Tableau is easy to use."
"The initial setup is simple."
"Tableau's most valuable features are user-friendliness and have a connection between multiple source systems. You can publish a report by using Tableau Public and there you can make your data online, not only batches of data, you can use it as an online analytical tool."
"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."
"The interface should be more user-friendly."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"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 product must be made more user-friendly."
"What is happening, with so many tools coming up in the market, is that people have to continuously get educated in order to use some of the more advanced features."
"It is not so great when it comes to data exchange/integration, data mining, etc."
"Its price should be improved. Its price is much higher than Power BI and QlikView. Programming is not easy on Tableau. For programming, you have to have a separate model. They should include programming directly on the web portion of the Tableau desktop so that people can write Python or JavaScript code for customizations instead of using a different model. Currently, Tableau Data Prep is a separate application that you have to purchase. It would be helpful if they can include Tableau Data Prep and programming languages such as R, Python in the next version. Tableau Public, which is a community version, doesn't allow you to save your work on your desktop. They should allow it. Currently, you can only upload it in the community."
"The development part should be better. We are putting a lot of effort in during development, so if we face any struggles, we have to find workaround solutions on the internet."
"Requires a lot of user training."
"SAP BusinessObjects has some semantic layer designs that give the flexibility to do ad hoc reporting or dashboard designing. If that can be brought into Tableau, it would be great. We have the data in the database, but we should also be able to bring something between the database and the dashboard and do some semantic layer modeling for ad hoc reporting requirements."
"Navigating through activities like cleansing, reshaping, and wrangling extensive or complicated datasets could prove challenging within the Tableau environment."
"More integration with Python or something related to machine learning would be a good improvement."
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, Amazon QuickSight, Domo, SAS Visual Analytics and Databricks. See our Google Cloud Datalab vs. Tableau report.
See our list of best Data Visualization vendors.
We monitor all Data Visualization reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
