Azure Databricks vs. IBM Watson Studio on Cloud Pak for Data

Having access to all databases and tables in one place is what has helped me and my team to function better. The in built functionality/access to SQL and Python is definitely an added bonus! The icing on the cake is the ability to export your data into an Excel spreadsheet for additional analysis. If you have less to no working knowledge of SQL or Python, its better to look at alternatives.

Incentivized

It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.

Incentivized

• Consistently great performance when dealing with huge scale data with the help of spark architecture
• Magic commands such as spark sql, pyspark, scala . This comes really handy in day to day work
• Integration with other Azure services is super smooth and robust

Incentivized

• Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
• SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
• Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
• Estimator validation lets data scientists test and prove different models.

Incentivized

• Intuitive interface
• Ease of use
• Providing FAQ or QRGs

Incentivized

• The cost is steep and so only companies with resources can afford it
• It will be nice to have Chinese versions so that Chinese engineers can also use it easily
• It takes a while to learn how to input different kinds of skin defects for detection

Incentivized

because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)

Incentivized

Based on my extensive use of Azure Databricks for the past 3.5 years, it has evolved into a beautiful amalgamation of all the data domains and needs. From a data analyst, to a data engineer, to a data scientist, it jas got them all! Being language agnostic and focused on easy to use UI based control, it is a dream to use for every Data related personnel across all experience levels!

Incentivized

The UI flawlessly merges this offering by providing a neat, minimal, responsive interface

Incentivized

From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected

Incentivized

Never had slow response even on our very busy network

Incentivized

I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path

Incentivized

The trainers on the job are very smart with solutions and very able in teaching

Incentivized

The Platform is very handy and suggests further steps according my previous interests

Incentivized

It surprised us with unpredictable case of use and brand new points of view

Incentivized

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

Incentivized

The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.

Incentivized

It helped us in getting from 0 to DSX without getting lost

Incentivized

• The support team is amazing, they help you at every stage of the projects, from sales to delivery.
• On a framework level, it has had an amazing impact and has reduced the clients overall data platform costs by a staggering 65%
• There has been a 40% Manual work requirement on average for the clients when they move to Azure Databricks Data Platform

Incentivized

• Could instantly show data driven insights to drive 20% incremental revenue over existing results
• Still don't have a real use case for unstructured data like twitter feed
• Some of the insights around user actions have driven new projects to automate mundane tasks

Incentivized