Google BigQuery is a great big data storage – it is simple, fast, and highly scalable. BigQuery’s SQL allows you to satisfy most of the needs that usually buisness may have – join tables, data transformation, calculations and so on. But sometimes you may need more complicated cases of data transformation when SQL does not Read more about How To Start Using PySpark On Your BigQuery Data Using Google Dataproc[…]
Google Cloud Platform offers a wide range of serviced which allows you to deploy your own web applications and share them with the whole world. Here you have: App Engine, Compute Engine, Kubernetes clusters or even Cloud Functions for simple endpoints. All this solutions are mainly differ with technical complexity, flexibility and of course costs. Read more about How To Deploy A Simple Dockerized Flask App On Google Cloud Run[…]
If your work is even slightly related to online marketing – you probably have heard already about new version of Google Analytics – Google Analytics 4 Property. Everybody are talking about it now because Google Analytics is the most popular web analytics tool, so a lot of businesses worldwide are depend on it. One of Read more about How To Get Google Analytics 4 Property Report to Pandas Dataframe Using API[…]
Google Sheets is a great tool for storing not too large amount of data, with possibility of easy adding and editing data manually without deep technical knowledge of SQL or programming. On the other hand Google offers a BigQuery – a big data warehouse with super-fast SQL wich allows to manipulate and analyse huge amount Read more about Import Google Sheets Data Into Google BigQuery Using Python And Pandas[…]
Google Analytics have different built-in integrations with other Google advertising platforms like Google Ads or Campaign Manager (in case of GA360) in order to import data from those platforms and present more complete reports. But in case of non-Google ad platforms like Facebook Ads – there are no built-in solutions within Google Analytics. It can Read more about How To Import Cost Data Into Google Analytics Using API and Python[…]
Many web applications require PDF reports and downloads. There are numerous open-source libraries that can build basic PDFs, but if you need a more complicated PDF document or are sending your document to a printer, you’ll need a commercial PDF generation tool. Unlike the browser-based open-source HTML to PDF libraries, commercial engines are designed specifically Read more about How To Make Complicated PDFs From Basic HTML And CSS[…]
Google Cloud Platform has a lot of different data storing options, but if you are looking for a simple NoSql solution with fast read-inserts – Google DataStore will be the right choice here. If you are writing some web application – Google Datastore will help you to easily handle your app’s data like data of Read more about Google Cloud Datastore – A Simple And Fast NoSQL Database For Your Project (with Python API examples)[…]
Google App Engine is a Google Cloud service which lets you to deploy your web site or web application and share it with other world in a very simple way without carrying about all these complicated server stuff and infrastructure. In this guide we will deploy our own app, the whole process can be described Read more about How To Deploy A Simple Flask App On Google App Engine In Couple Of Minutes[…]
Regular expressions are great helpers for every data analyst because they allows to transform dimensions applying quite complicated logic rules. In Google Data Studio I often use REGEXP text functions – so I decided to share with you some my most often use cases. In addition – we’ll find out the difference between REGEXP_REPLACE, REGEXP_EXTRACT Read more about Regular Expressions (RegEx) in Google Data Studio – Guide With Examples[…]
People that never tried programming often think, that programming is something very complicated and hard to start. Honestly I had the same thinking until I tried python – one of the most intuitive programming languages with a low entry barrier. While learning programming it’s important to be able instantly try your knowledge in practice. In Read more about Pandas Python Library = Excel On Steroids (tutorial for beginners)[…]
When I created my first bot with Selenium library – I could not believe how easy and intuitively Selenium is. It’s like writing a scenario for a movie – You just describing step by step what should be going on. In my particular case – Selenium helped me to automate reporting of some advertising platforms, Read more about How You Can Create Your Own Bot Using Selenium WebDriver And Python[…]
If You ever wanted to create a dashboard with Facebook Ads data – You probably had an issue with data connectors. The most popular like Supermetrics costs lot of money, although there are some cheap solutions like Pipelinica. But also You can try to create your own solution for free. There is a scheme of Read more about How To Automate Facebook Ads Reporting In Google Data Studio With Python And FB Marketing API[…]
“Markov Chain Attribution” is one of the most popular data driven attribution models. The most important concept behind this model is removal effect. In this article I`ll try to explain the math behind removal effect in a simple way without any formulas. As an example we will take a very simple use case – four Read more about Markov Chain Attribution – Simple Explanation Of Removal Effect[…]
Working with Pandas dataframes It`s often needed to reshape the data, in order to prepare it for further analysis, visualization or library that requires particular data form. I`ve decided to share with you some functions that I used a lot working with customer journey paths, exported from Google Analytics. For experienced data scientist that could Read more about 3 Helpful Python Functions For Data Manipulation[…]
Google BigQuery is a great big-data tool, which let you to store a huge amount of data in cloud, and manipulate it with SQL queries. But there are situations, when you want to get that data to your python environment for more advanced purposes like machine learning, which is possible thanks to numerous python libraries. Read more about Google BigQuery API Request (Python)[…]
Google Analytics Reporting Api gives you a lot of possibilities like downloading your data without sampling, exporting it to databases or just ability to work with raw data (for example in Jupyter Notebooks). The easiest way I`ve found to make a API request to Google Analytics: 1. Create a Google Cloud Platform project and enable Read more about Google Analytics API Request (Python)[…]
Parallel coordinates were invented in far 1885 by French engineer and mathematician Philbert Maurice d’Ocagne. When I discovered this way of visualization – I was really impressed how it allows to visualize such a complicated thing as multidimensional data in a simple and intuitive way. This is how I visualized few dimensions of Mobile App Read more about Parallel Coordinates For Multidimensional Data Visualization[…]
CASE statements allow you to create new dimensions in Google Data Studio based on existing ones. Syntax of CASE statement is pretty intuitively and reminds SQL a lot: In order to create a new calculated field – open your Data Studio report, and click “Create new field”: Give your new dimension a name, write your Read more about CASE Statements In Google Data Studio[…]
Google Spreadsheet formulas is a powerful tool which can make your life much more easier if you are working with data a lot. There are a lot of interesting extensions that can be very useful for a online marketeer, like Google Ads extension or Google Analytics extension for Google Spreadsheets, but output data which you`ll Read more about 5 Google Spreadsheet Formulas Which Every Web-Analyst Should Know[…]
Sometimes, while configuring tags in Google Tag Manager, we want to know if the user visiting our site for the first time or not. Variable like that can be very useful if we want to fire some of our tags only for new or returning users, or assign different conversion value of the same conversion Read more about New vs Returning Client-ID Variable In Google Tag Manager[…]
Vanity URL – is a short version of your site domain, that is easy to remember and enter in the browser. This picture from newspaper should explain you pretty well why publishing of usual links in your offline advertise is not a good idea. Let`s imagine I`m promoting my app – SKAGs Table Creator, which is Read more about Offline Campaigns Measuring With “Vanity URL”[…]
As you might know, people often doesn`t buy anything just after they have seen an advertisement. How many people you know, that have bought a car just after they`ve seen for the first time a banner (even very attractive), with that car? Yes, some cheap products can be bought impulsively, but before buying any kind Read more about Multi-Channel Analysis In Google Analytics[…]
Google Apps Script is an environment, from which you can interact with Google G Suite Services like Google Docs, Sheets, Forms and so on. It can be really helpful if you want to automate some of your routine job. With some basic knowledge of JavaScript you can create really great things, that would save you a lot of Read more about Why Google Apps Script Is Simple[…]
Data sets in Google Analytics are allow to import external data into your account. An example of such data could be your costs, spend on SEO or Facebook campaign. Keeping all data in one analytical system allows for comprehensive analysis of all your advertising channels. So, that`s how to create a Data Set in Google Read more about How To Create A Data Set in Google Analytics[…]
AdWords editor lets you to import data for your campaign from other sources in table-like format. You can prepare that table in Microsoft Excel, Google Spreadsheets or any other similar tool. Preparing data for your campaign in that way will save your time and nerves. You can prepare table with data for your AdWirds Search Campaign Read more about How To Import Data To AdWords Editor[…]