Apache 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, Google Analytics seems to be a lot more popular than Apache Pig. While we know about 36 links to Google Analytics, 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.
Let’s discuss Google Analytics in particular and other tools in general, which are available online to measure the website performance. Source: almost 2 years ago
Google Analytics: A free tool from Google that provides in-depth website analytics and performance metrics, including traffic sources, user behavior, and conversions. Source: almost 2 years ago
Automating your affiliate marketing has a clear advantage: scalability. As your affiliate network grows, manual management becomes difficult. Automation makes it easier to handle a larger volume of affiliates, communicate with them, and monitor their performance. This means that your affiliate program can grow without sacrificing efficiency. You can also use automation tools to track and report affiliate... Source: almost 2 years ago
Google Analytics: It provides in-depth insights into website traffic, user behavior, conversions, and other important metrics. Source: almost 2 years ago
Implement a robust website analytics tool, such as Google Analytics, to track key metrics and gather insights about user behavior. Set up goals and conversion tracking to measure the impact of your website redesign or migration on your business objectives. Source: almost 2 years ago
Pig, a platform/programming language for authoring parallelizable jobs. - Source: dev.to / over 2 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 / over 3 years ago
Matomo - Matomo is an open-source web analytics platform
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so 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.
Adobe Analytics - Adobe Analytics is an industry-leading solution that empowers you to understand your customers as people and steer your business with customer intelligence.
Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)