We performed a comparison between Google Cloud Datalab and Qlik Sense 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."
"The overall ability to build quick wins with simple data to drive insights."
"The integration with R & Python for predictive modeling, and possibly machine learning in the future, is very valuable."
"Faster time to delivery utilizing useful charts and graphs, which allows for on-demand generation of analytical data in tables, graphs, and charts."
"Quick reporting."
"From siloed reports, we went to a centralized knowledge hub, combining cross-functional data, and helping decision-makers see the data as a whole, therefore making more informed decisions."
"Some of the valuable areas of this solution include producing individual reports and closing the gap."
"The product has many great features like easy and fast implementation, flexible data loading, and in-memory processing, but the Set Analysis is what I think is the most valuable. It makes the product very powerful."
"Qlik Sense is essentially a web-based tool even though it's on-prem – you're working off an HTML page – so it's pretty quick. Your processing speed does not matter because you're using a lot of stuff through the web. That's great because it brings down the cost in regards to hardware."
"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."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"The interface should be 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 product must be made more user-friendly."
"The management console appearance needs improvement to its look."
"Areas for improvement include user-friendliness, self-service, and some of the visualization options for generating reports."
"There is room for improvement in the learning curve when getting started, but training resources have been growing."
"More pivot table options, like the ability to have the totals row at the bottom of the table, would be helpful."
"There is an inability to effectively manage (pre)caching (scheduling, assigning for respective user groups, etc), especially without community extensions or uour own development."
"It would be nice to have more native features from QlikView built into Qlik Sense."
"Right now, it is complex and you have to understand the data model prior to analyzing it, so basically I would like to see an integration with Excel in the future."
"Qlik Sense is working very well on going to low code and development. They are trying to make their environment more user-friendly. However, the training is not free. When you want to learn more about the tool, sometimes you need to pay for the training. This does not make sense to me because training should be free because the more you learn about the tool the more you use it and the more you are loyal to the company and want to continue usage."
Google Cloud Datalab is ranked 20th in Data Visualization with 5 reviews while Qlik Sense is ranked 2nd in Data Visualization with 112 reviews. Google Cloud Datalab is rated 7.6, while Qlik Sense is rated 8.6. 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 Qlik Sense writes "Customizable with good ROI and a quick learning curve". Google Cloud Datalab is most compared with Databricks, IBM SPSS Statistics, Cloudera Data Science Workbench, IBM SPSS Modeler and Microsoft Azure Machine Learning Studio, whereas Qlik Sense is most compared with Tableau, Amazon QuickSight, Microsoft Power BI, Apache Superset and Alteryx. See our Google Cloud Datalab vs. Qlik Sense report.
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