Google Universal Analytics was an enterprise-level analytics solution that was sunset in July of 2024.
$150,000
Up to 1 Billion hits/month
H2O.ai
Score6.4 out of 10
N/A
An open-source end-to-end GenAI platform for air-gapped, on-premises or cloud VPC deployments. Users can Query and summarize documents or just chat with local private GPT LLMs using h2oGPT, an Apache V2 open-source project. And the commercially available Enterprise h2oGPTe provides information retrieval on internal data, privately hosts LLMs, and secures data.
As I have discussed previously their insights were very useful. The second thing is since it is a Google product you will connect the data very easily from other platforms like Bigquery, Google Drive, etc. and even you can connect Google marketing platform. through this tool, you can track your live campaign how they were performing, and how it will be engaging your customer as well.
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
It is an excellent cloud analytics platform that is easy to install and configure and easy to deploy and use, allowing us to measure web traffic and other tools.
It is an entirely online tool; it does not take up hard disk space like other desktop tools.
Since this tool is draggable, Google is constantly adding more features.
Even beginners who do not have a custom dashboard can get information. If there is a problem somewhere on the site that needs to be investigated, Google Analytics 360 will notify you.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Generally I think there is a lot you can do within the tool, but as it is a Google product it means there is limited support - something which I think lets all of the platform stacks down
There could be more visual signifiers to identify if a feature is a normal or 360 feature. This would mean you can really get to grips with what the extra more advanced elements are
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Google Analytics 360 is an upgraded version of the most widely used web/app analytics tracking tools in the market. The price is stable and predictable making it a long-term product of choice. It's easy to use and pairs so well with other Google Marketing Platform products.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The UI is very easy to navigate and use. The features are well designed and intuitive. As long as the user has a good understanding of basic digital analytics definitions and capabilities, this tool should be quite easy to use. I consider Google Analytics Premium to be the easiest of all of the enterprise solutions out there to use.
If you purchase Premium through a reseller like LunaMetrics, you are going to be taken care of. The additional amount of support and services that a reseller provides to make sure you have the best experience with the product is the reason why the reseller program exists to begin with. Support doesn't have to be just reactive, it can be proactive as well.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
There is a ton of information online about Google Analytics, but Google Analytics Premium users will have dedicated support and training from Google or an Authorized Reseller.
If you already have the basic version of GA installed, "getting" GA Premium happens immediately through a virtual flipping of the switch - no need to re-implement. You'll want to expand your use of custom dimensions and metrics (you get 10x the amount with Premium). Ideally, you'll be using a tag management solution to talk with GA Premium, in concert with implementing a dataLayer (to note, Google's Tag Manager platform is covered under the same GA Premium SLA, and it's free). There are some welcomed "configurations" with GA Premium, such as integrating with DoubleClick products, activating data driven attribution models, and building roll-up executive reports - but all of these are easy point and click solutions. In comparison with any other enterprise analytics solution, implementing GA and GA Premium is traditionally easier and more flexible. And if you have any trouble or need an extra set of hands for implementation, GA Certified Partners like LunaMetrics can help
Unless you have very complex and edge case analytics needs, Google Analytics [360 (formerly Google Analytics Premium)] is likely going to be the best choice. From both a cost and usability stand point, Google wins. Adobe has the edge case when you need to create really custom reports, dimensions, metrics, etc. In my experience, this is rarely the case and you end up biting off more than you can chew. Stick with Google unless you are or plan on hiring an Adobe Analytics expert.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
