Well suited for my big data related project or a static data set analysis especially for uploading huge dataset to the cluster.
But had some issues with connecting IoT real-time data and feeding to Power BI. It might be my understanding please take it as a mere comment rather than a suggestion.
Looker Studio is well-suited for those wanting to analyze web/site data and performance quickly. It is simple enough to learn/use for quick report-building or drilling into data. Looker Studio is easier to use/understand than the GA4 console and thus has a better UI/UX. It is an efficient tool for fast, simple data needs—especially for team members with limited analytical capabilities and knowledge.
Easier pricing and plug-and-play like you see with AWS and Azure, it would be nice from a budgeting and billing standpoint, as well as better support for the administration.
Bundling of the Cloud Object Storage should be included with the Analytics Engine.
The inability to add your own Hadoop stack components has made some transfers a little more complex.
It is the simplest and least expensive way for us to automate our reporting at this time. I like the ability to customize literally everything about each report, and the ability to send out reports automatically in emails. The only issue we have been having recently is a technical glitch in the automatic email report. Sadly, there is almost no support for this tool from Google, but is also free, so that is important to take into consideration
It is not ideal and requires time and dedication to understand how to work with it. Also, it has a lot of limitations around data it can accept. But in most cases, this tool is sufficient for everyday tasks of product and marketing departments. I wouldn't say that the interface is very user-friendly, but for people who regularly work with analytical tools, it must be ok.
I give it a lower support rating because it seems like our Dev team hasn't gotten the support they need to set up our database to connect. Seems like we hit a roadblock and the project got put on pause for dev. That sucks for me because it is harder to get the dev team to focus on it if they don't get the help they need to set it up.
We initially wanted to go with Google BigQuery, mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM. Apache Spark was also in the running, but here IBM's domination in the industry made the choice a no-brainer. As previously stated, the support received was not quite what we expected, but was adequate.
The free version of Looker Studio is still better than the leading enterprise-embedded BI tools, despite its weaknesses. The leading embedded BI platforms have terrible visualizations that can be spotted a mile away. They are also primarily locked to a grid, making it very hard to fully customize. The price point is also a major deterrent, since users end up paying for lots of features they might never use. Looker Studio has weaknesses on the blending and modeling side, but we've been able to get by via connection to GBQ and transformation done in dbt.
This product has allowed us to gather analytics data across multiple platforms so we can view and analyze the data from different workflows, all in one place.
IBM Analytics has allowed us to scale on demand which allows us to capture more and more data, thus increasing our ROI.
The convenience of the ability to access and administer the product via multiple interfaces has allowed our administrators to ensure that the application is making a positive ROI for our business users and partners.
