Find out what your peers are saying about Alteryx, SAP, Altair and others in Predictive Analytics.
Alteryx helps familiarize managers with artificial intelligence-driven possibilities.
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.
Using ThoughtSpot has resulted in significant time savings and improved business sales by allowing us to identify sellers and buyers across regions, facilitating targeted marketing.
Based on our implementation in one project, we are trying to raise more funding to expand its use.
ThoughtSpot saves a significant amount of time compared to other tools and is very user-friendly.
I contacted customer support once or twice, and they were quick to respond.
The customer service was not good because we weren't premium support users.
Customer support is good since I've had no issues and can easily contact representatives who respond promptly.
Whenever we reach out, they respond promptly.
As of now, we are raising issues and they are providing solutions without any problems.
I rate the technical support as fine because they have levels of technical support available, especially partners who get really good support from Databricks on new features.
I stopped opening tickets due to insufficient and untimely responses.
ThoughtSpot provides a dedicated customer success person and the ability to submit tickets online, with a response time of no more than a day.
The knowledge base for ThoughtSpot is less robust compared to others.
Alteryx is scalable, and I would give it eight out of ten.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Databricks is an easily scalable platform.
I would rate the scalability of this solution as very high, about nine out of ten.
Tableau, Power BI, or Looker have separate tools for preparation, customization, and storytelling.
The platform does not have technical problems with scaling data or connections.
As our data has grown, I have validated huge datasets and complex models without significant issues.
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.
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.
I use it primarily for large datasets, and it performs faster than regular data visualization tools such as Power BI, which has limits on dataset size.
The upgrades are smooth with no downtime, which is super important.
The responsiveness of accessing live data is exceptional and faster than most other BI tools.
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.
Currently, it is not as customizable as the options available on Power BI or Tableau.
Handling governance when there are many models and dashboards is complex.
Enhancing integration capabilities with other tools like DBT would also be beneficial as it would make our lives easier.
Alteryx is more cost-effective compared to Informatica licenses, offering savings.
It has a fair price when considering a larger-scale implementation.
Alteryx is expensive.
It is not a cheap solution.
HubSpot is expensive.
ThoughtSpot's pricing is reasonable and in line with other BI tools.
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 is user-friendly and allows easy creation of workflows compared to Informatica PowerCenter.
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.
Its compatibility with most databases, including the latest from FlexMovely and Redshift, allows users to create joins and worksheets easily.
This alerting feature is very beneficial for our company at the moment, and we use it extensively.
When I upload a data dump, AI analytics suggest possible data visualizations and insights, which I can pin to dashboards or live boards for modification.
| Product | Market Share (%) |
|---|---|
| Alteryx | 14.0% |
| Anaplan | 13.8% |
| SAP Analytics Cloud | 12.7% |
| Other | 59.5% |
| Product | Market Share (%) |
|---|---|
| Databricks | 8.3% |
| Snowflake | 17.7% |
| Dremio | 8.9% |
| Other | 65.1% |
| Product | Market Share (%) |
|---|---|
| ThoughtSpot | 1.5% |
| Microsoft Power BI | 14.1% |
| Tableau Enterprise | 10.3% |
| Other | 74.1% |
| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 15 |
| Large Enterprise | 51 |
| Company Size | Count |
|---|---|
| Small Business | 25 |
| Midsize Enterprise | 12 |
| Large Enterprise | 56 |
| Company Size | Count |
|---|---|
| Small Business | 3 |
| Large Enterprise | 12 |
Alteryx can be used to speed up or automate your business processes and enables geospatial and predictive solutions. Its platform helps organizations answer business questions quickly and efficiently, and can be used as a major building block in a digital transformation or automation initiative. With Alteryx, you can build processes in a more efficient, repeatable, and less error-prone way. Unlike other tools, Alteryx is easy to use without an IT background. The platform is very robust and can be used in virtually any industry or functional area.
With Alteryx You Can:
Alteryx Features Include:
Some of the most valuable Alteryx features include:
Scalability, stability, flexibility, fast performance, no-code analytics, data processing, business logic wrapping, scheduling, ease of use, data blending from different platforms, geo-referencing, good customization capabilities, drag and drop functionality, intuitive user interface, connectors, machine learning, macros, simple GUI, integration with Python, good data transformation, good documentation, multiple database merging, and easy deployment.
Alteryx Can Be Used For:
Alteryx Benefits
Some of the benefits of using Alteryx include
:
Reviews from Real Users
"Automation is the most valuable aspect for us. The ability to wrap business logic around the data is very helpful." - Theresa M., Senior Capacity Planner at a financial services firm
"Alteryx has made us more agile and increased the speed and effectiveness of decision making." - Richard F., Director, Digital Experience & Media at Qdoba Restaurant Corporation
"The scheduling feature for the automation is excellent." - Data Analytics Engineer at a tech services company
"The product is very stable and super fast, five-star. It's significantly more stable than its nearest competitor." - Director at a non-tech company
“A complete solution with very good user experience and a nice user interface.” - Solutions Consultant at a tech services company
"There are a lot of good customization capabilities." - Advance Analytics PO at a pharma/biotech company
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?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.
ThoughtSpot is a powerful business intelligence tool that allows easy searching and drilling into data. Its ad hoc exploration and query-based search features are highly valued, and it is easy to set up, stable, and scalable.
The solution is used for reporting purposes, self-service BI, and embedding into other applications for customers to do self-service analytics. It helps businesses with metrics, KPIs, and important insights by sourcing data from various sources into one golden source and visualizing it in an easy way for the business to consume. The pricing model is ideal, charging for data rather than the number of users.
