


Find out what your peers are saying about Alteryx, SAP, Anaplan 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.
This reduction in both time and money resulted in real-time impact and significant cost savings.
For a lot of different tasks, including machine learning, it is a nice solution.
When it comes to big data processing, I prefer Databricks over other solutions.
In a world surrounded by data, tools that allow navigation of large data volumes ensure decisions are data-driven.
Because of integration with Microsoft Power BI, its interactive dashboards, and how easily it integrates with other SQL data sources, business decisions from business users have become much faster.
Power BI is easy to deploy within an hour, providing robust security against data leaks.
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.
Whenever we reach out, they respond promptly.
As of now, we are raising issues and they are providing solutions without any problems.
I would give Databricks customer support a rating of ten.
The significant drawback I notice is that Microsoft's size makes it hard to get specific change requests addressed unless they involve a bug.
We have a partnership with Microsoft, involving multiple weekly calls with dedicated personnel to ensure our satisfaction.
The support is good because there is also a community available.
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.
The sky's the limit with Databricks.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Databricks is an easily scalable platform.
You expect only a small percentage of users concurrently, but beyond a thousand concurrent users, it becomes difficult to manage.
With increasing AI capabilities, architectural developments within Microsoft, and tools like Fabric, I expect Power BI to scale accordingly.
As more data is processed, performance issues may arise.
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.
They release patches that sometimes break our code.
Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.
Databricks is definitely a very stable product and reliable.
In terms of stability, there's no data loss or leakage, and precautions are well-managed by Microsoft.
We typically do not have problems with end-user tools like Excel and Power BI.
It is very stable for small data, but with big data, there are performance challenges.
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.
Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.
We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
This makes Power BI difficult to manage as loading times can reach one or two minutes, which is problematic today.
Access was more logical in how it distinguished between data and its formatting.
Microsoft updates Power BI monthly based on user community feedback.
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.
It is not a cheap solution.
I believe that in terms of credits for Databricks, we're spending between £15,000 and £20,000 a month.
My experience with pricing, implementation costs, and licensing is that it is very efficient and very fast.
I found the setup cost to be expensive
Power BI isn't very cheap, however, it is economical compared to other solutions available.
The pricing for Microsoft Power BI is low, which is a good selling point.
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.
Databricks' capability to process data in parallel enhances data processing speed.
The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.
The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.
In today's data-driven environment, these tools are of substantial value, particularly for large enterprises with numerous processes that require extensive data analysis.
Within the organization, Microsoft Power BI is used to create dashboards and gain insights into data, enhancing data-driven decision-making.
To reduce the need for highly skilled personnel, we can engage someone who is just familiar and has a basic understanding of Microsoft Power BI, while AI can handle the major tasks through either agent AI or requirement analysis.
| Product | Mindshare (%) |
|---|---|
| Alteryx | 7.6% |
| Red Hat Lightspeed | 5.8% |
| Altair RapidMiner | 5.7% |
| Other | 80.9% |
| Product | Mindshare (%) |
|---|---|
| Databricks | 9.7% |
| Snowflake | 15.1% |
| Teradata | 8.8% |
| Other | 66.4% |
| Product | Mindshare (%) |
|---|---|
| Microsoft Power BI | 7.5% |
| Tableau Enterprise | 5.8% |
| Amazon QuickSight | 3.2% |
| Other | 83.5% |



| Company Size | Count |
|---|---|
| Small Business | 33 |
| Midsize Enterprise | 16 |
| Large Enterprise | 56 |
| Company Size | Count |
|---|---|
| Small Business | 27 |
| Midsize Enterprise | 12 |
| Large Enterprise | 57 |
| Company Size | Count |
|---|---|
| Small Business | 136 |
| Midsize Enterprise | 59 |
| Large Enterprise | 171 |
Alteryx provides user-friendly, no-code tools for data blending, preparation, and analysis. Its drag-and-drop interface and in-database capabilities simplify integration with data sources while maintaining data integrity.
Alteryx offers a comprehensive suite for automation of data workflows, reducing manual tasks and enhancing processing efficiency. Known for robust predictive and spatial analytics, it effectively handles large datasets. The platform's flexibility allows for custom script deployments, supported by a strong community. However, Alteryx faces challenges with high pricing, lack of cloud support, and limited data visualization tools. Users express a need for more in-built data science functionalities, improved API integration, and a smoother learning curve. Connectivity and documentation gaps, along with complex workflows, are noted concerns, suggesting areas for enhancement. Alteryx is widely used for tasks like ETL processes, data preparation, predictive modeling, and report generation, supporting functions like financial projections and spatial analysis.
What features define Alteryx?Alteryx is implemented across industries for diverse needs such as anomaly detection in finance, customer segmentation in marketing, and tax automation in auditing. Teams leverage its capabilities for data blending and predictive modeling to enhance operational efficiency and address specific business needs effectively.
Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.
Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.
What features make Databricks unique?
What benefits can users expect from Databricks?
In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.
Microsoft Power BI is a powerful tool for data analysis and visualization. This tool stands out for its ability to merge and analyze data from various sources. Widely adopted across different industries and departments, Power BI is instrumental in creating visually appealing dashboards and generating insightful business intelligence reports. Its intuitive interface, robust visualization capabilities, and seamless integration with other Microsoft applications empower users to easily create interactive reports and gain valuable insights.