

Find out what your peers are saying about SAP, Alteryx, Red Hat and others in Predictive Analytics.
Tasks that earlier took hours in Excel or SQL are now completed in minutes.
From a time-saving perspective, we saved 60 to 75 percent of the human workforce needed and eliminated other disparate ETL tools, ultimately saving us over 600,000 dollars.
Alteryx helps familiarize managers with artificial intelligence-driven possibilities.
The number of employees has reduced to half, and time is saved by nearly two to three hours a day because of automated reports.
Customer support from Alteryx has been amazing.
they do have a website for resolving doubts and accessing helpful resources, including various tools and filters.
I contacted customer support once or twice, and they were quick to respond.
Anyone with minimal knowledge of Looker can easily go through the documentation and understand the steps and the UI.
Alteryx is scalable for most enterprise analytics and data preparation workloads.
Suggestions for improvements in Alteryx include areas for increasing efficiency, particularly in processing telemetry data, which involves dealing with large volumes of unstructured data.
Alteryx is scalable, and I would give it eight out of ten.
I rate Looker's scalability a nine because of how easily we can scale by simply combining tables.
I didn't need to reach out to Alteryx for support because available documents usually provide enough information to resolve issues.
I have not encountered any lagging, crashing, or instability in the system during these three months of usage.
Alteryx is a reliable tool, but it is also very heavy, requiring good laptop configurations, a minimum of 8GB RAM, and a recent processor such as i10.
The tool could include more native connectors, such as for global ERPs, instead of requiring additional fees for these connections.
The support structure changed; initially, we received great support, however, it later became less reliable due to licensing issues and a tiered support system.
The additional features that Alteryx needs to work on to make it more competitive include better collaboration and easier integration through API.
The performance is not optimal on large data sets.
The biggest friction point or frustration I have encountered with Google Data Studio is the lack of automatic integrations.
The price is very high, with licensing typically starting around five thousand dollars plus user per year.
We found excellent use cases for automation through Alteryx, which provided the means to reduce operational costs and streamline the build of ETL pipelines without extensive coding.
Alteryx is more cost-effective compared to Informatica licenses, offering savings.
Alteryx not only represents data but also supports decision-making by suggesting the next steps.
Analysts who do not have any coding experience can still work on the transformation and preparation of data, which is quite useful.
Alteryx includes built-in tools such as drive time analysis and linear regression, which are much harder to achieve in standard BI tools such as Power BI or Tableau.
For a business user to understand data from free form or Essbase, it usually takes thirty minutes to an hour to go through the previous day's trend. However, with the visualization tools in Looker, they can easily understand the data and compare it to the previous one or two years using a bar graph, pie chart, or other graphs.
In terms of time saved, my team probably saves close to 40 hours per week due to using Google Data Studio instead of the old manual process.
| Product | Mindshare (%) |
|---|---|
| Alteryx | 7.9% |
| DataRobot | 6.2% |
| Red Hat Lightspeed | 6.0% |
| Other | 79.9% |
| Product | Mindshare (%) |
|---|---|
| Google Data Studio | 5.0% |
| Tableau Enterprise | 17.3% |
| Qlik Sense | 7.1% |
| Other | 70.6% |


| Company Size | Count |
|---|---|
| Small Business | 46 |
| Midsize Enterprise | 20 |
| Large Enterprise | 73 |
| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 8 |
| Large Enterprise | 7 |
Alteryx enhances efficiency by automating data preparation and transformation through a user-friendly drag-and-drop interface, catering to non-technical users and business professionals. It supports data blending, predictive analytics, and diverse data integration capabilities.
Alteryx streamlines data manipulation and complex transformations, benefiting industries such as finance and marketing with its ability to connect to multiple data sources and automate workflows. The platform supports analytics and machine learning model building, reducing manual efforts in ETL processes. Despite its capabilities, improvements are needed in database connectivity, pricing flexibility, and cloud service integration. Users desire enhancements in reporting features, visualization, and technical support to optimize its full potential. Machine learning and predictive analytics features require advancements to improve user experience and broaden accessibility through better connectors and reduced licensing costs.
What are Alteryx's key features?
What benefits and ROI should be looked for in reviews?
In finance and marketing, organizations leverage Alteryx to automate data tasks, connect diverse sources, and generate analytics models and dashboards efficiently. Its no-code approach aids in rapid data preparation, cleansing, and analysis, empowering business users to engage in predictive and prescriptive analytics effectively.
Google Data Studio enables seamless integration with Google's ecosystem, enhancing data visualization with Looker's capabilities. Its semantic layer and real-time insights support efficient dashboard creation and sharing.
Google Data Studio offers comprehensive data management through LookML, allowing custom data modeling with minimal training. Its centralized data management facilitates dashboard creation for non-technical employees. Users benefit from real-time insights and advanced analytics, along with automated reporting that reduces workload. Although it offers customization and data-level security, areas like visualization flexibility and large dataset performance need improvement. Challenges include handling complex filters, limited chart types, and the absence of multi-sheet options.
What are the key features of Google Data Studio?Google Data Studio is implemented in industries like real estate, sales, and marketing for creating operational reports and understanding trends. It helps organizations visualize data for customer behavior analytics, supporting developers in managing integrations and data governance efficiently.
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