Looker
Tableau
Microsoft Power BI
Sisense
Domo
Qlik
QlikSense
Google BigQuery
Apache Apex
Apache Spark
Google Cloud Dataflow
Apache Storm
Snowplow
logstash
Google BigQuery
Amazon EMR
Looker is a business intelligence platform with an analytics-oriented application server that sits on top of relational data stores. The Looker platform includes an end-user interface for exploring data, a reusable development paradigm for creating data discovery experiences, and an extensible API set so the data can exist in other systems. Looker enables anyone to search and explore data, build dashboards and reports, and share everything easily and quickly.
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Based on our record, Looker seems to be a lot more popular than Apache Apex. While we know about 14 links to Looker, we've tracked only 1 mention of Apache Apex. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Then in the "foldername" you can have 5 folders, each one for each of the groups. This means that when group1 enters looker.com, his default page will be the "foldername", which contains group1folder (he cannot see the rest of the folders if you have set the permissions correctly for each folder). Source: about 2 years ago
Even if you want to make Wide Tables, combining fact and dimensions is often the easiest way to create them, so why not make them available? Looker, for example, is well suited to dimensional models because it takes care of the joins that can make Kimball warehouses hard to navigate for business users. - Source: dev.to / over 2 years ago
We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / about 3 years ago
Dashboard: I like to use Datastudio because it's easy (just like using google sheets), but you can also try out Looker. Source: over 3 years ago
For Growth and larger, I would recommend Looker. The only reason I wouldn't recommend it for the smaller company stages is that the cost is much higher than alternatives such as Metabase. With Looker, you define your data model in LookML, which Looker then uses to provide a drag-and-drop interface for end-users that enables them to build their own visualizations without needing to write SQL. This lets your... - Source: dev.to / over 3 years ago
Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 3 years ago
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Microsoft Power BI - BI visualization and reporting for desktop, web or mobile
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Sisense - The BI & Dashboard Software to handle multiple, large data sets.
Apache Storm - Apache Storm is a free and open source distributed realtime computation system.
