Amazon Deep Learning AMIs vs. Ataccama ONE

Amazon AMIs has been very useful for the quick setup and implementation of deep learning for data analysis which is something I have used the service for in my own research. We commonly use the service to enable students to run intensive deep learning algorithms for their assessments. This service works well in this scenario as it allows students to quickly set up a suitable environment and get started with little hassle. If you are looking to run simple, surface level deep learning algorithms (kind of contradictory statement I know) then AMI is more complicated than most will need. When it comes to teaching the basics of Machine Learning, this kind of system is unnecessary and there are other alternatives which can be used. That being said this service is a must if you are looking to run complex deep learning via the cloud.

Incentivized

Usage for enterprise wide data management and governance across wide range of user group. Ataccama ONE enables achieving higher data quality amongst the data products. It is a powerful platform that supports integration of several checks on different data sets that can be also consolidated in reports later on. Data discovery works quite fast and easy.

Incentivized

• Setting up environment
• Support for different types of machines
• Perfect for Machine Learning / Deep Learning use cases
• Nvidia / Cuda / Conda support easily

Incentivized

• It is one of the leading data quality tools in the industry, in our opinion.
• Offers free data profiling.
• Integrates with other tools for complete end-to-end lineage.

• Some aspects of the User Interface are quite confusing and activating packages can be a bit convoluted
• It can be a bit confusing to switch between frameworks for novice users

Incentivized

• Performance in loading
• Reduction of pop-up messages

Incentivized

One of the key factors in our choice to onboard Ataccama was its usability - general end users have everything at their fingertips, it is not difficult for IT developers to setup the tool, and it has been an overall pleasure.

Support has been excellent to date - very user friendly and knowledgeable to help support our needs and issues as they arise.

Both of these services provide similar functionality and from my experience both are top class services which cover most of your needs. I think ultimately it comes down to what you need each service for. For example Amazon DL AMIs allows for clustering by default meaning I am able to run several clustering algorithms without a problem whereas IBM Watson Studio doesn't provide this functionality. They both provide a wide range of default packages such as Amazon providing caffe-2 and IBM providing sci-kitlearn. My main point is that both are very good services which have very similar functionality, you just need to think about the costs, suitability of features and integration with other services you are using.

Incentivized

Ataccama ONE is a designated tool for Data quality monitoring. Supports end to end. Quite easy to deploy. Alteryx is more about coding or almost as complicated while Ataccama ONE is a bit easier to use. Different interfaces. Many views automatically available for data sets in Ataccama ONE. Output is vizualized in the tool. While more data transformation is required in Alteryx.

Incentivized

• Saves a lot of Infra Costs
• Saves a lot of time in handling environment issues
• Easy to start a new instance

Incentivized

• Less data inconsistencies in the system enable processes to run smoother without interruptions

Incentivized