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 monkeylearn. We know about 14 links to it since March 2021 and only 11 links to monkeylearn. 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
MonkeyLearn: A platform for text analysis and machine learning, allowing users to train custom models for tasks like sentiment analysis and topic classification. Source: 6 months ago
Monkeylearn.com — Text analysis with machine learning, free 300 queries/month. - Source: dev.to / over 1 year ago
MonkeyLearn supports 11 languages for data analysis (Spanish, Portuguese, German, Russian, Italian, French, Dutch, Chinese, Japanese, Korean and Arabic). But for sentiment analysis, only Spanish seems to be available, I’m not sure about that. Source: over 1 year ago
R3: Used RedditExtractoR in R to download all-time top posts, and ran the resulting .csv through https://monkeylearn.com/. Downloaded the resulting table and deleted top result "OC" - then visualized it with ggplot to give a sense of absolute numbers. Total posts considered in this are 988, the word cloud only looks at the 98 most mentioned words/phrases. Let me know if you have got any questions/concerns! Source: almost 2 years ago
Go to monkeylearn.com and sign up for a free demo. Then cut and paste your blog text into the extractor/classifier. Source: almost 2 years ago
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Google Cloud Natural Language API - Natural language API using Google machine learning