Six Key Components of an Analytics Data Pipeline

This blog post is aimed for anyone planning to build a data pipeline or upgrade their current setup.

An end-to-end analytics data pipeline is a secure and reliable mechanism that is responsible for feeding your business with valuable data that can be used for reporting, analysis, machine learning or any other activity that requires accurate data about your business.

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Working with Google Analytics Data Using Python and Jupyter Notebooks

Python is a programming language with virtually limitless functionalities and one of the best languages for working with data. Jupyter Notebooks, on the other hand, is the most popular tool for running and sharing both your Python code and data analysis.

Putting Python and Notebooks together with Google Analytics, the most popular and a really powerful tool for tracking websites, gives you almost like a superpower for doing your analysis.

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Data You Should Be Tracking Using Google Analytics Custom Events

Out of the box, Google Analytics already tracks a bunch of really useful data points. What the default setup lacks, though, is context and events that are specific to your website and business.

Custom Events provide a perfect solution for adding context and tracking more specific user actions. In this article, we are giving you a good amount of ideas for custom events you should implement on your own and/or your clients’ websites.

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Using Google Analytics for Tracking SaaS

While it was originally built for tracking general marketing and ecommerce websites, Google Analytics can be configured to track your SaaS app as well. After building tracking setups for 11 different SaaS tools, I can say that Google Analytics excels in tracking SaaS. In this article, I’m giving you a bunch of practical guidelines for doing the same with your own (or your client’s) SaaS app.

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