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.
Looker might be a bit more popular than Metaflow. We know about 14 links to it since March 2021 and only 12 links to Metaflow. 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 1 year 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 1 year ago
We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / about 2 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 2 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 2 years ago
I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home. Source: about 1 year ago
1) I've been looking into [Metaflow](https://metaflow.org/), which connects nicely to AWS, does a lot of heavy lifting for you, including scheduling. Source: about 1 year ago
Even for people who don't have an ML background there's now a lot of very fully-featured model deployment environments that allow self-hosting (kubeflow has a good self-hosting option, as do mlflow and metaflow), handle most of the complicated stuff involved in just deploying an individual model, and work pretty well off the shelf. Source: over 1 year ago
They had to figure out video compression that worked at the volume that they wanted to deliver. They had to build and maintain their own CDN to be able to have a always available and consistent viewing experience. Don’t even get me started on the resiliency tools like hystrix that they were kind enough to open source. I mean, they have their own fucking data science framework and they’re looking into using neural... Source: over 1 year ago
Github Actions, Metaflow and AWS SageMaker are awesome technologies by themselves however they are seldom used together in the same sentence, even less so in the same Machine Learning project. - Source: dev.to / almost 2 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 Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Microsoft Power BI - BI visualization and reporting for desktop, web or mobile
Luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs.
Sisense - The BI & Dashboard Software to handle multiple, large data sets.
Azkaban - Azkaban is a batch workflow job scheduler created at LinkedIn to run Hadoop jobs.