Our Mission is to empower data teams to build a strategic data capability that delivers high-quality, complete, and relevant data across the business. Our users and customers use Snowplow for numerous use cases – from web and mobile analytics to advanced analytics and the production of AI & ML ready data, whilst maintaining data privacy compliance. Our customers reflect the diversity of use cases that Snowplow solves and includes Strava, The Wall Street Journal, CapitalOne, WeTransfer, Nordstrom, DataDog, Auto Trader, GitLab and many more.
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 Snowplow. We know about 14 links to it since March 2021 and only 10 links to Snowplow. 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.
We’ve also thought about Ops :-). There’s a backend 'Collector' that stores data in Postgres, for instance to use while developing locally, or if you want to get set up quickly. But there’s also full integration with Snowplow, which works seamlessly with an existing Snowplow setup as well. - Source: dev.to / over 1 year ago
Sure thing! Say you run an online store. Your source systems could be the inventory, orders or customer databases. You could also track click/site behavior with something like snowplow. An ERP system is essentially just a combination of what I mentioned previously. Another good example is a CRM such as Salesforce or Zendesk. Hopefully that helps! Source: almost 2 years ago
Well if you have to structure and create Schema and manage Data Warehouses, you need a tool to do that, so in the background you see SnowPlow, which helps you do just that. Make the data into some kind of sensible structure so that later on business analysts can come see whats up. Want to do a quarterly report on how you performed, go to the application that goes to the data warehouse and builds your report for... Source: about 2 years ago
We also have telemetry set up on our Monosi product which is collected through Snowplow,. As with Airbyte, we chose Snowplow because of its open source offering and because of their scalable event ingestion framework. There are other open source options to consider including Jitsu and RudderStack or closed source options like Segment. Since we started building our product with just a CLI offering, we didn’t need a... - Source: dev.to / about 2 years ago
Https://matomo.org That's the only full featured open source competitor I am aware of, so it should be mentioned. https://snowplowanalytics.com/ Somewhat FOSS. There was a story there, but I don't remember the details. - Source: Hacker News / over 2 years ago
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
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
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.
Heap - Analytics for web and iOS. Heap automatically captures every user action in your app and lets you measure it all. Clicks, taps, swipes, form submissions, page views, and more.
Sisense - The BI & Dashboard Software to handle multiple, large data sets.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Microsoft Power BI - BI visualization and reporting for desktop, web or mobile