Azure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…
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SAS Enterprise Miner
Score 9.0 out of 10
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SAS Enterprise Miner is a data science and statistical modeling solution enabling the creation of predictive and descriptive models on very large data sources across the organization.
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Pricing
Azure Databricks
SAS Enterprise Miner
Editions & Modules
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No answers on this topic
Offerings
Pricing Offerings
Azure Databricks
SAS Enterprise Miner
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Azure Databricks
SAS Enterprise Miner
Features
Azure Databricks
SAS Enterprise Miner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Databricks
7.0
3 Ratings
17% below category average
SAS Enterprise Miner
8.8
4 Ratings
6% above category average
Connect to Multiple Data Sources
6.73 Ratings
8.14 Ratings
Extend Existing Data Sources
7.33 Ratings
9.04 Ratings
Automatic Data Format Detection
6.73 Ratings
9.34 Ratings
MDM Integration
7.42 Ratings
9.02 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Databricks
7.3
3 Ratings
14% below category average
SAS Enterprise Miner
8.1
4 Ratings
4% below category average
Visualization
7.13 Ratings
7.14 Ratings
Interactive Data Analysis
7.53 Ratings
9.14 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Databricks
8.0
3 Ratings
2% below category average
SAS Enterprise Miner
8.0
4 Ratings
2% below category average
Interactive Data Cleaning and Enrichment
7.03 Ratings
7.84 Ratings
Data Transformations
8.43 Ratings
8.24 Ratings
Data Encryption
9.63 Ratings
8.12 Ratings
Built-in Processors
7.13 Ratings
8.12 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Databricks
7.4
3 Ratings
12% below category average
SAS Enterprise Miner
8.8
4 Ratings
5% above category average
Multiple Model Development Languages and Tools
5.23 Ratings
7.54 Ratings
Automated Machine Learning
8.43 Ratings
9.82 Ratings
Single platform for multiple model development
8.03 Ratings
8.54 Ratings
Self-Service Model Delivery
8.03 Ratings
9.23 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Centralised notebooks are out directly into production. This can lead to poorly engineered code. It is very good for fast queries and our data team are always able to provide what we ask for. It is a big cost to our business so it is important it runs efficiently and returns on our investment.
SAS Enterprise Miner is world-class software for individuals interested in developing reproducible models in a reasonable amount of time. Perhaps the most useful part of SAS Enterprise Miner is the ability to compare models with other models without writing code. The ensemble modeling capabilities is the easiest way to do ensemble modeling I have come across. SAS Enterprise Miner is well-suited for beginning to advanced analysts who know something about advanced analytics. The software is not well-suited for analysts or companies that have little interest in advanced modeling.
Enterprise Miner is really visual and lets you do a whole lot without actually going into the detailed options. For decent results, you should really explore the different advanced options though.
The recent versions of Miner allow users to use R code in Miner. You can then compare several models and approach to get the best performing model.
The resulting data is really well displayed and easy to understand (ex: the lift graph, score ranking, etc.)
Miner has the ability to integrate custom SAS code which allows the user to add functionalities that are specific to the project.
Great for what we use day to day and does what we need it to do. Cost management is not fully developed across the UX and gets expensive very quickly for developing projects. Integrated very well with our Microsoft stack and can be worked on collaboratively which works well for us.
SAS' customer support used to be non-existent many years ago. Today, contacting SAS customer support is great. They are responsible, knowledgable, and seem to have an interest in getting the results right the first time. With that said, Enterprise Miner's online support is weak, probably because the user base is much smaller than other tools.
Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!" Far ahead of the competition, the delta lakehouse platform also fares better than it counterparts of Iceberg implementation or a loosely bound Delta Lake implementation of Synapse
SAS EM has a very great set of machine learning and predictive analytics toolsets, which helped our organization achieve its goals. We used other tools, but for us, SAS EM was the most intuitive and easy to learn the tool and it provides greater data exploration and data preparation capabilities compared to the other tools we used.
In our organization, users were using SAS already so the learning curve was really low. Within a few weeks after the implementation, the users were already delivering models developed with SAS Enterprise Miner. It is difficult to talk about ROI as models were already being developed before. It was mostly a change of technology and it was a smooth transition.
Going with Enterprise Miner came with migration from desktop use of SAS to a server use of SAS. This created a new role of SAS administrator. This was obviously a cost but as the use of SAS increased greatly, it was expected.
From a methodology standpoint, Enterprise Miner helped greatly in the documentation of the model development which was a requirement in a few groups such as the risk groups. Having a visual "GUI-like" approach to development, the flowchart or diagram of the project in Miner was able to give users a good understanding of the approach the analyst took to develop the model.