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Buyer's Guide
Data Science Platforms
September 2022
Get our free report covering Amazon, Microsoft, Databricks, and other competitors of Anaconda. Updated: September 2022.
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Alexis Bustamante - PeerSpot reviewer
STI Data Leader at grupo gtd
Real User
Top 5Leaderboard
Easy to use with a free community version and helpful documentation
Pros and Cons
  • "The solution offers a free community version."
  • "We'd like a more visual dashboard for analysis It needs better UI."

What is most valuable?

I like the simplicity and ease of use. 

You can deploy the solution to many clouds easily. 

The initial setup is straightforward.

The solution offers a free community version.

What needs improvement?

The auto models can be improved. 

We can create auto models like Microsoft Azure Machine Learning. In Azure Machine Learning, they have these features, for example, for auto models or code, or by code. They need this in Databricks. 

We need more connectors between on-premises and the cloud. 

We'd like a more visual dashboard for analysis It needs better UI. 

For how long have I used the solution?

I've used the solution for one and a half months. 

What do I think about the stability of the solution?

The solution is very stable. There are no bugs or glitches. It doesn't crash or freeze. 

What do I think about the scalability of the solution?

Scalability is no problem. At the beginning, we created a cluster, for example, and if we need more performance in the future, for example, or to accelerate the training, we can change the cluster. It's quite straightforward. 

We have five people using the solution. 

In one or two years, we'd like to promote the solution to clients and increase usage. Right now, the way it is used is limited. I know that some banks and aeronautics companies use it.

How are customer service and support?

In terms of technical support, for now, we use the community. 

Which solution did I use previously and why did I switch?

We are also aware of KNIME, Azure Machine Learning, and Anaconda. In Anaconda, we use many frameworks, for example.

We started with other platforms, like Azure Machine Learning due to the fact that, with AutoML, it's easy to use. However, now that we have more skills, we need other tools or platforms like Databricks. It's a good platform to deploy and develop machine learning in employees.

How was the initial setup?

The implementation is quite easy. It's not complex or difficult. The first time, I did it using a tutorial which was quite helpful. Later, I took a course. I know it quite well. 

The deployment only takes a few days. 

You only need to deploy or maintain the solution. 

What about the implementation team?

We did not need any outside assistance in terms of setting up the solution. 

What's my experience with pricing, setup cost, and licensing?

For us, this product is free. We use the community version.

I am interested in using the enterprise version, however. Whether we use it or not depends on the projects and customers we get.

What other advice do I have?

I work with a solution provider. We are a Databrick customer.

We are not partners of Databricks. Only we are partnered with Microsoft Azure and Amazon AWS.

We are using the latest version of the solution. However, I do not know the exact version number. 

I still need time with the solution before providing advice to others. I need to prepare the capacity internally. So far, it's been great.

I'd rate the solution eight out of ten. 

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Senior Systems Engineer at a financial services firm with 10,001+ employees
Real User
Top 10
Good technical support but too complex and not open-source
Pros and Cons
  • "The technical support is very good."
  • "The solution is much more complex than other options."

What is our primary use case?

We primarily just use the analytical tool section of the solution.

What is most valuable?

The stability is okay.

The technical support is very good.

What needs improvement?

We really don't like the protocols the solution offers. 

The solution is much more complex than other options.

For how long have I used the solution?

We've been using the solution for three or four years, however, it may have been a bit longer.

What do I think about the stability of the solution?

I don't recall having issues with stability. I can't recall if there are bugs or glitches.

What do I think about the scalability of the solution?

I don't really know to much about the scalability of the solution. It's not something I generally dealt with.

How are customer service and technical support?

I've contacted technical support in the past. I'd say they offer enough of a level of service to us. We're pretty satisfied with their level of service. SAS internal support is very qualified and if we have any issues, we contact them and trust that they can help. 

Which solution did I use previously and why did I switch?

We are thinking to replace SAS with something like Anaconda. Actually, we are using Anaconda with Jupyter NET, however, we need to collect more details about Anaconda and other open-source analytic tools that could replace SAS.

How was the initial setup?

I don't have too much information on the initial setup, however, it's my understanding that it's quite complex.

What's my experience with pricing, setup cost, and licensing?

We'd prefer it if the solution was open source. That would make it less expensive.

What other advice do I have?

We're using Enterprise Guide simultaneously with Enterprise Miner.

From my perspective, I believe that open-source analytics tools are closer to fitting our needs. We prefer open-source options like Anaconda. They offer good support and features. Anaconda also integrates well with Jupyter NET, which is important for us.

Overall, on a scale from one to ten, I'd rate the solution at a five. If there were better protocols and wasn't as complex as it is, I'd rate it a bit higher.

Which deployment model are you using for this solution?

On-premises
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
Alexis Bustamante - PeerSpot reviewer
STI Data Leader at grupo gtd
Real User
Top 5Leaderboard
Lacking image analysis and stability, but useful for test projects
Pros and Cons
  • "The most valuable feature of Microsoft Azure Machine Learning Studio is the ease of use for starting projects. It's simple to connect and view the results. Additionally, the solution works well with other Microsoft solutions, such as Power Automate or SQL Server. It is easy to use and to connect for analytics."
  • "Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."

What is our primary use case?

We use Microsoft Azure Machine Learning Studio when we need to connect with the customer's data. We can connect easily, and fast, and test and train quickly. We have quick results.

What is most valuable?

The most valuable feature of Microsoft Azure Machine Learning Studio is the ease of use for starting projects. It's simple to connect and view the results. Additionally, the solution works well with other Microsoft solutions, such as Power Automate or SQL Server. It is easy to use and to connect for analytics.

What needs improvement?

Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me.

For how long have I used the solution?

I have used Microsoft Azure Machine Learning Studio within the last 12 months.

What do I think about the stability of the solution?

The stability of Microsoft Azure Machine Learning Studio could improve. The solution is good for test development but it is not good for production environments.

What do I think about the scalability of the solution?

Microsoft Azure Machine Learning Studio

Which solution did I use previously and why did I switch?

I have used other solutions, such as Anaconda previously, and I prefer them over Microsoft Azure Machine Learning Studio. They are more stable.

How was the initial setup?

The initial setup of Microsoft Azure Machine Learning Studio is easy.

What about the implementation team?

We have one data scientist for the deployment and a data analyst for maintenance of the Microsoft Azure Machine Learning Studio.

What other advice do I have?

I would recommend this solution for MPPs for fast production or deployments, but do not recommend the solution for production.

I rate Microsoft Azure Machine Learning Studio a five out of ten.

Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
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Buyer's Guide
Data Science Platforms
September 2022
Get our free report covering Amazon, Microsoft, Databricks, and other competitors of Anaconda. Updated: September 2022.
633,572 professionals have used our research since 2012.