
Segment
Google Analytics
Mixpanel
Egnyte
Zapier
Hotjar
RStudio
Geckoboard
Apache Pig
Looker
Jupyter
Google BigQuery
Presto DB
Databricks
Rakam
Informatica
Segment
Apache PigApache Pig is recommended for data engineers and analysts who are working in Apache Hadoop environments and need to perform ETL (Extract, Transform, Load) operations on large datasets. It is also suitable for teams looking to leverage existing Hadoop infrastructures without delving into complex Java MapReduce programming or when migrating legacy processing scripts based on Pig Latin.
Based on our record, Segment seems to be a lot more popular than Apache Pig. While we know about 46 links to Segment, we've tracked only 2 mentions of Apache Pig. 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.
For teams just starting out with PLG enrichment: Datagma as the primary personal email resolver, PDL as fallback, Segment as the event bus, Mixpanel for behavioral event storage (the SQL explorer makes it easy to export activation cohorts for offline scoring analysis without touching production code), and whatever CRM you already have. - Source: dev.to / 3 months ago
Twilio Segment: Specializes in customer data collection with a more neutral stance toward destination platforms. Its API allows flexible data routing across your tech stack without being tied to specific engagement channels. - Source: dev.to / over 1 year ago
To collect these metrics effectively, you'll need specialized tools like Google Analytics, Mixpanel, Segment, or Amplitude. - Source: dev.to / over 1 year ago
Segment for event collection and routing. - Source: dev.to / over 1 year ago
Segment โ Customer data platform for tracking and analytics. - Source: dev.to / over 1 year ago
Pig, a platform/programming language for authoring parallelizable jobs. - Source: dev.to / over 3 years ago
In the early days of the Big Data era when K8s hasn't even been born yet, the common open source go-to solution was the Hadoop stack. We have written several old-fashioned Map-Reduce jobs, scripts using Pig until we came across Spark. Since then Spark has became one of the most popular data processing engines. It is very easy to start using Lighter on YARN deployments. Just run a docker with proper configuration... - Source: dev.to / almost 5 years ago
Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
Egnyte - Enterprise File Sharing
Google BigQuery - A fully managed data warehouse for large-scale data analytics.