Data Science & Automation in Digital Advertising
The demonstration will outline the current state of Digital Media. It will provide industry level knowledge on topics like:
- Digital Advertising
- Digital Analytics
- Data Science & Business Analytics in Advertising
- Data collection through 1st, 2nd & 3rd party data
- Management of more than 30 data sources on cloud at scale (using Google Cloud Platform)
- Data transformation and steps needed to enrich data lake.
The main focus of this demonstrations would be on buliding an "Advanced Analytics: R Shiny Application" from scratch. The application will cover parts of data importing, data joining, UI setup, Graphical representation using R plotly & ggmap, data transformation using dplyr, machine learning use case like anomaly detection, time series model.
Outline/Structure of the Demonstration
- Overview of Digital Media/Advertising
- a) Most important source of data for digital media. (Google Analytics with Introduction, feature description and data type provided by platforms).
- b) Paid Media data sources and type of information we can collect (Social Media, Google Search Media, SEO platforms)
- c) Other source of information (Google Search Trends, Weather data etc)
2. How to manage all the aforementioned data (Google Cloud Platform, Python & APIs).
3. Next Step: Demonstration of R Shiny Application to create an Advertising 360 environment for your client.
- Digital Advertising & Analytics Overview
- Data Source & Management on industry-scale using Google Cloud Platform, Python & SQL.
- Data Visualization using R.
- Machine Learning Algorithms like Holt-Winter Prediction to predict sessions or users, Anomoly detection to catch tagging, trafficking errors etc.
- How to make an R Shiny Web application using the data sources of our choice.
- Dynamic graph to text narration.
- Google Cloud Platform basics.
- Google Marketing Platform landscape.
People interested in R programming, R shiny, Shiny Dashboards, Business Analytics, Advanced Analytics in production, Cloud platform, R packages, Machine Learning using R
Prerequisites for Attendees
- R basics