Getting Started
Build a social media dashboard using machine learning and BI services
In this workshop we’ll make use of:
- Amazon Translate
- Amazon Comprehend
- Amazon Kinesis Data Firehose
- Amazon Athena
- Amazon Quicksight
- Amazon S3
We’ll use these tools to build a natural-language-processing (NLP)-powered social media dashboard for tweets.
Social media interactions between organizations and customers deepend brand awareness and these conversations are a low-cost way to acquire leads, improve traffic, develop relationships, measure brand sentiment, and improve customer service.
A major shoutout to Ben Snively and Viral Desai for their original work on this. You can read their blog post for more.
What It Looks Like
This is what our final dashboard will look like:
CloudFormation
We’ll provision and deploy this workshop with a tool called AWS CloudFormation which allows us to define our infrastructure as code. In this case, YAML.
We can proceed with provisioning the workshop resources by using the “Launch Stack” button below.
Launching The Stack
We launch this by providing our EC2 instance keypair name and our Twitter tokens provisioned in the prerequisites.
From there we can pass in a few other variables like the languages we will support and translate as well as the terms we want to search for on Twitter.
