H2O.ai vs. Qlik Cloud Analytics (Qlik Sense)

Most suited if in little time you wanted to build and train a model. Then, H2O makes life very simple. It has support with R, Python and Java, so no programming dependency is required to use it. It's very simple to use. If you want to modify or tweak your ML algorithm then H2O is not suitable. You can't develop a model from scratch.

Incentivized

Qlik Sense is a program whose purpose is to greatly improve all your operations and use of all data in an organic way. The mission will always be to increase the economic and commercial processes of the company in a short time. I recommended it for its high technology, which was Created for this area, the results are successful. We have noticed how it has increased relationships with our clients thanks to the credibility and security that we provide.

Incentivized

• Excellent analytical and prediction tool
• In the beginning, usage of H20 Flow in Web UI enables quick development and sharing of the analytical model
• Readily available algorithms, easy to use in your analytical projects
• Faster than Python scikit learn (in machine learning supervised learning area)
• It can be accessed (run) from Python, not only JAVA etc.
• Well documented and suitable for fast training or self studying
• In the beginning, one can use the clickable Flow interface (WEB UI) and later move to a Python console. There is then no need to click in H20 Flow
• It can be used as open source

Incentivized

• Flexibility in data recording, from the app, as well as in handling them. Allowing you to view reports quickly and effectively.
• Easy to generate dynamic graphics according to our needs.
• It is very easy to use, intuitive, so it does not generate costs in the learning process compared to the tool with collaborators

Incentivized

• Better documentation
• Improve the Visual presentations including charting etc

Incentivized

• Scalability is RAM limited, all data is associative and in-memory so server's RAM is directly proportional to performance
• Limitation on advanced analytics capabilities in the form of R integration to perform complex statistical and analytical calculations
• Can have more intuitive interface

Incentivized

Qlik Sense is a constantly improving it's software and working with its' users to make it better. They are great at keeping their users informed of progress and care about delivering a quality product

Incentivized

Qlik Sense has a better and easy to learn user interface compared with other analytics tool which always help us to create regular and adhoc reports within the stipulated time frame and can be easily refreshed at a scheduled time and sent to multiple stakeholders for timely update regarding the Key metrics indicator.

Incentivized

The overall experience I have with H2O is really awesome, even with its cost effectiveness.

Incentivized

Qlik is great for companies with lots of business domains and departments because it scales well, especially if data that is reported is saved in SQL and similar structures. Its ease of use and good UI enables business units to create and manage their own reports. That removes a great burden of creating and managing/modifying these pages from the IT team. Overall, it's a win-win for both IT and business units.

Incentivized

The instructor was very knowledgeable.

Incentivized

The online instructor was very knowledgeable.

Incentivized

Hire Qlik consultants. It's better done by them or with their aid.

Incentivized

Both are open source (though H2O only up to some level). Both comprise of deep learning, but H2O is not focused directly on deep learning, while Tensor Flow has a "laser" focus on deep learning. H2O is also more focused on scalability. H2O should be looked at not as a competitor but rather a complementary tool. The use case is usually not only about the algorithms, but also about the data model and data logistics and accessibility. H2O is more accessible due to its UI. Also, both can be accessed from Python. The community around TensorFlow seems larger than that of H2O.

Incentivized

The customization of the platform opens up plenty of other options depending on the use cases. The API layer is incredibly rich and makes integration of Qlik based visualization into web pages a simple and effective pattern. It's been very easy to use with a great community made up of professionals. Qlik Sense has introduces artificial Intelligence into my data visualization and reporting activity.

• Positive impact: saving in infrastructure expenses - compared to other bulky tools this costs a fraction
• Positive impact: ability to get quick fixes from H2O when problems arise - compared to waiting for several months/years for new releases from other vendors
• Positive impact: Access to H2O core team and able to get features that are needed for our business quickly added to the core H2O product

Incentivized

• Once an app is published and running good, we can quickly see the time we save to analyze data.
• It's hard sometimes to realize the money we save by using this system.
• People start understanding the power of data and asking more questions.

Incentivized