Wide World Importers (WWI) is a traditional brick and mortar business with a long track record of success, generating profits through strong retail store sales of their unique offering of affordable products from around the world. They have a great training program for new employees, that focuses on connecting with their customers and providing great face-to-face customer service. This strong focus on customer relationships has helped set WWI apart from their competitors.
Over time, WWI modernized their business by expanding to online storefronts. During this expansion period, WWI experimented with various marketing tactics to drive online sales, from offering in-store shoppers special discounts online with promotional coupons after making a purchase, to running ad campaigns targeted toward customers based on demographics and shopping habits. These marketing campaigns proved successful, prompting WWI to invest more resources to these efforts and grow their marketing team.
Today, WWI has a host of online stores for various product offerings, from their traditional product catalogs offered by their physical storefronts, to specialized categories like automotive and consumer technology products. This expansion has made it more challenging to analyze user clickstream data, online ad performance, and other marketing campaigns at scale, and to provide insights to the marketing team in real-time.
Real-time marketing analysis is provided through interactive reports and dashboards on WWI's home-grown web platform, ReMarketable. This platform has served them well, but they are currently hindered by their inability to keep up with demand. ReMarketable's primary users are members of the marketing team, and the secondary users are shoppers on their various online platforms for whom website interaction behavior is being tracked. Other sources of data are fed from online ad data generated by ads run on social media platforms and email marketing campaigns. They use this type of data to evaluate ad effectiveness and customer reach, ultimately leading to sales conversions.
In this workshop, you will learn how to use advanced features of the managed PostgreSQL PaaS service on Azure to make your database more scalable and able to handle the rapid ingest of streaming data while simultaneously generating and serving pre-aggregated data for reports. You will design a resilient stream processing pipeline to ingest, process, and save real-time data to Postgres. Next, you will learn how to explore and gain insights from flat files at scale, perform aggregates, and save the valuable information to your database. Finally, you will create complex reports containing advanced visualizations, using a drag-and-drop interface, and use them to build a customizable dashboard that gets updated in real-time.
At the end of this workshop, you will be better able to implement a highly scalable, managed open source database solution that can simultaneously handle real-time data and roll-up and serve data for advanced visualizations.
In this whiteboard design session, you will work with a group to design a solution for using advanced features of the managed PostgreSQL PaaS service on Azure to make your database more scalable and able to handle the rapid ingest of streaming data while simultaneously generating and serving pre-aggregated data for reports. You will provide guidance for designing a resilient stream processing pipeline to ingest, process, and save real-time data to Postgres. Next, you will design a solution for exploring and gaining insights from flat files at scale, perform aggregates, and saving the valuable information to your database. Finally, you will provide guidance on how to create complex reports containing advanced visualizations, using a drag-and-drop interface, and use them to build a customizable dashboard that gets updated in real-time.
At the end of this whiteboard design session, you will be better able to design a highly scalable, managed open source database solution that can simultaneously handle real-time data and roll-up and serve data for advanced visualizations.
In this hands-on lab, you will implement a proof-of-concept (PoC) for using advanced features of the managed PostgreSQL PaaS service on Azure. These features help make your database more scalable and able to handle the rapid ingest of streaming data while simultaneously generating and serving pre-aggregated data for reports. You will create a resilient stream processing pipeline to ingest, process, and save real-time data to Postgres. Next, you will implement a solution for exploring and gaining insights from flat files at scale, perform aggregates, and saving the valuable information to your database. Finally, you will create complex reports containing advanced visualizations, using a drag-and-drop interface, and use them to build a customizable dashboard that gets updated in real-time.
At the end of this hands-on-lab, you will be better able to implement a highly scalable, managed open source database solution that can simultaneously handle real-time data and roll-up and serve data for advanced visualizations.