We performed a comparison between Alteryx and Google Cloud Datalab based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."One-stop shop for data preparation, blending, prediction, and optimization in a single workflow."
"My primary focus is creating numerous data pulls, and Alteryx Server handles the automation well."
"Geo features have made spatial mapping large retail universes possible."
"It's super easy to learn how to use it — the learning curve is very small."
"Alteryx's connectivity is essential. We like the ability to connect the solution to multiple sources. It's easier than other data modeling and extraction solutions. It's built on a self-service concept, so it's easy for anyone to open the tool and directly import or export data from it."
"Automation is the most valuable aspect for us. The ability to wrap business logic around the data is very helpful."
"It saves time on a lot projects. "
"I like the fact that you can easily blend data from different platforms."
"All of the features of this product are quite good."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"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 solution can be made more affordable."
"I think sometimes the solution doesn't load properly or takes so much time for the workflows. Though the workflow runs and completes the file in Excel, if you use the same formula, it's a bit slow. Also, the image processing is not so good because I tried to do some image processing and they were like, sometimes they put two to eight. In the document, it was two, but the OCR predicted it as eight."
"If there is any way to make the learning curve less steep, that would be ideal."
"The event handling, such that the file system watcher, is in need of improvement."
"The formula we currently use in Alteryx can be automated."
"There are no ready models to use in analytics."
"There are a few hiccups with specific data sets and languages or formats that the data comes in. That may be a minor problem, but we can work through it. We had some issues looking at XML format in added data, but it wasn't significant."
"Alteryx can improve the model management and deployment processing of large workloads."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"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."
"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."
"The product must be made more user-friendly."
Alteryx is ranked 3rd in Data Science Platforms with 74 reviews while Google Cloud Datalab is ranked 16th in Data Science Platforms with 5 reviews. Alteryx is rated 8.4, while Google Cloud Datalab is rated 7.6. The top reviewer of Alteryx writes "Feature-rich ETL that condenses a number of functions into one tool". On the other hand, the top reviewer of Google Cloud Datalab writes "Easy to setup, stable and easy to design data pipelines". Alteryx is most compared with KNIME, Dataiku, Databricks, RapidMiner and Tableau, whereas Google Cloud Datalab is most compared with Databricks, IBM SPSS Statistics, Cloudera Data Science Workbench, KNIME and Qlik Sense. See our Alteryx vs. Google Cloud Datalab report.
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