Amazon Forecast vs. Azure Machine Learning

I personally get the feeling that Amazon Forecast must have been a direct product released on the models Amazon themselves must have used at some port. Amazon Forecast definitely shines when using it for product demand, inventory, and pricing throughout store locations, etc. Everything, including data-set importing, works best in this context. When applying it to more edge cases like resource planning around events, it can be a bit more tricky to apply effectively.

Incentivized

Azure can be a more unified product. It feels like 10 different tech teams were building it but we're not talking to each other. An example is when the user needs to know what is the next step. Automatically saving a previous state is very helpful as new users are usually not aware of the functionality.

Incentivized

• Develop benchmarks for use in future forecast.
• Performs contingency planning during challenging financial times.
• Anticipate the impact of new expanse.

Incentivized

• Easy to create the experiment.
• Easy to adopt the best algorithm.
• Efficient way to deploy the model as a web service.
• Centralized platform for the life cycle of machine learning goal.

• Potential very high costs
• Predicting ongoing running costs
• Very product focused

Incentivized

• Few models: Even though it has a lot of Machine Learning models, it is quite limited when compared to R. Most Data Scientists still use and prefer R, so the newest models tend to release as R libraries. With Azure ML, we need to wait for Microsoft to evaluate and decide if including a new model is a good idea or not
• Tableau interface: last time I checked there was no easy way to connect with Tableau.
• Cloud based: You always need a good internet connection to use it.

Incentivized

Good UX/UI and overall good usability, but it takes a while to get used to the product & platform. The whole design seems fragmented with little in terms of integration with project management tools such as JIRA, or wireframing. Overall it feels like an unfinished product that's meant for teaching more than for production.

Incentivized

I'm satisfied with the Azure Machine Learning Studio- it fulfilled my goal in a single channel. Even haven't worr[ied] about the maintenance or any fault tolerance. This provide[s] the user interactive UI to grab the features easily. [Their] support teams also very help[ful], they stand with us at any time.

Not sure

There was no other product or service that was considered before making the choice to go with Amazon Forecast as the forecasting that the company was looking for had everything running in the AWS environment, the choice had to be obvious. Integrating with Amazon Forecast also ensured that everything is under a single roof and we didn't have to go multiple places looking for data when needed.

Incentivized

The answer is quite simple: Microsoft Azure Machine Learning Workbench is the cheapest and most user friendly analytics tool I have ever seen! Unless you are running a team of data scientists, this is the tool to go. Most functions (marketing, sales, finance, supply chain, logistics, HR, R&D, etc.) could easily integrate Azure ML in its day to day activity.

Incentivized

• Insights have been available much more quickly and well designed manner
• Integration with other tools has been flawless

Incentivized

• It is easy to learn and construct, which impacts directly on productivity.
• Good for experimentation and validation for simple models.
• Has a use cost less than the best alternatives in the market.

Incentivized