IBM Watson StudioPricing

Cheaper storage Faster data processing Faster data analysis

Checking if it is under use or not because for free users who cannot afford to pay, it is hard to manage the amount of computation periods provided … provide the lite pack with a few more resources to help those who cannot afford to pay

Sharing with team Github integration Free pricing plan if you want to try things out … for companies who already has large built production ML pipelines, as the cost of migration could be high and the initial overhead of learning the tools

Ease of deployment. The cost of ownership is high for a personal use. It's very convenient for quick hit

data. Positive - For this price tier, it was well worth the price as the ROI was greater than the cost. Negative - The cost for the next tier is a bit

It is used in the form of value chain at a macro level to drive optimization value and manage unplanned upsets. It is used by my department. … should have the capability to utilize thermodynamic models and extract key values.

years. Less suited for lower level data analysis which does not add much value. … is currently used by the data analytics department. It is used to address cost analysis and a…

embed the decisions into our existing offering without a lot of changes The pricing model is flexible Like the opportunity to embed more data

The cost is steep and so only companies with resources can afford it It will be nice to have Chinese versions so … product development so that we're able to test concepts and ideas quickly The cost of ownership is high for a small company like ours, and so we talked to

also stood out to us because it was more affordable and free for our organization to try out. We also greatly value the open source ecosystem Watson Studio … also stood out to us because it was more affordable and free for our organization to try out. We also greatly value the open source ecosystem Watson Studio … unusual ways. We think Watson studio could also improve by decreasing its…

customers evaluate IBM technologies and compare them against alternatives in a cost effective and time efficient way It has helped customers implement completely … other Watson APIs and components (e.g. NLU, Speech to Text, etc.), and cheaper usage costs

Pricing. The price for this product is quite steep and, since it features so many solutions, it makes sense to cost as much as it does. But … organizations that plan on using data science on a small scale because of its price and the high number of features.

are ready to work in the cloud. To create a cluster in-house could be expensive. I would like marketing would make more emphasis on the advanced funtions

IBM DSX. Last, I should say AliPAI is a good alternative, but it's too expensive.

all our data engineering work. We are analysing weather risks and produce pricing and risk analysis in Python. We also use stream analytics through Python … analysis and publish them Easy to integrate with other services and create a value added product. Easy to produce commercial…

team to do so.Google Tensorflow : impossible for programming and very expensive to hire the consultingSales force : Didn’t have the capabilities of creation

alternatives and costs we considered that using a big data platform would be too expensive for the kind of studies we are developing in the company. After that we

insurance industry has been in flux for several years, and there is greater value than in previous times on faster analytic turnaround. DSx provides the speed … influenced business decisions into tens of millions of dollars by impacting the cost of the "unknown." Many business questions simply were infeasible to be understood … than Cognos as a result. I have a dedicated server for anal…

Pricing is not clear Complicated to set up and onboard Too many different IBM products … Big, international projects where price is not an issue … Too expensive ROI not given In the future maybe applicable

capabilities, since various services can be included at a very competitive price: optimization, machine learning, storage, etc. Collaborative solution, since

As a senior consultant, I'm always looking to discover value in our's client data. This is crucial in our commercial model. Moreover, we always calculate … deployment cost Positive: ASP model, at the beginning it's cheaper than other solutions as on-premise. Ha…

machine learning models to calculate several customer metrics as future value and churn. … machine learning models to calculate several customer metrics as future value and churn.

catalog within the DSx. Visual Data Modeling; this results in faster time to value because you won't spend all day tuning a data model. Allowing you to compare … industries would Pharma data, Oil & Gas, Financial Markets, HR, Sales, Price Variance, and etc. Most professionals…