Hi and welcome to the SAP HANA Academy.
My name is Julie and in this series of videos called Live 5
we're going to walk you through the steps to build out an application
that can deliver advanced analysis of Twitter feed in real-time using the HANA 2 platform.
For our scenario we're going to look at Twitter data or tweets being created for a given topic or hashtag.
If I were a sports fan, I might want to know what people thought about my favorite team, say around the playoffs.
Are people generally excited or not so excited about what's going on?
But if I were the sports team itself and that was my business i might want to know more
than just whether people are positive or negative.
For example,
are the people that are negative shouting to the world and having a lot of people pay attention to them ?
Sharing those messages really broadly?
Or are those messages centered in a certain area or around a certain association of people?
So all of this information is actually available to us if we delve a little bit deeper into the data
using text, predictive, and graph processing analysis.
Lucky for us, all of that is actually in our SAP HANA platform.
So, here's an overview of what the series will teach you.
Firs t, we have Twitter data.
Next, will be our SAP HANA platform.
In our example, we'll actually be using the HANA express edition,
which is available for free for the 32 gigabyte starter edition.
By using this free edition you could be up and running in no time
and through this hands-on example created by the HANA Academy team
we can show you how easy it is for you, the developer, to build the advanced analytic applications
for an end user using SAP HANA.
The first group of videos will help you to establish the landscape.
We will look at how to install and configure the HANA express environment for our solution.
We will walk you through how to get the software, where to find the documentation, how to find support for this edition.
We will look at how to create the tenant database for our HDI module, which contains our views and our tables.
We will be using know Node.js, Odata, and XSJS, or JavaScript Web Services,
to handle our data movement both the incoming tweets and the outgoing data to the end user.
We will look at using Fiori and the UI5 Framework to create our user interface,
which will include some segmentation and maybe some charts.
We'll need to establish trust between the different components of our development environment
using user authentication and authorization area.
We want to do all of this through our browser-based development environment called webIDE
And finally we'll need to establish a connection to our Twitter API to read the data from Twitter into our application.
And of course we'll have to create the connection between our application and the end user.
Again, we'll be sending that data using an Odata web service.
Next, we'll turn our attention into the advanced analysis area and take a look at
setting up text analysis so we can
perform the sentiment analysis against our Twitter data
and possibly even filter out some profanity that we might find. It is social media after all.
Next, we'll use the predictive analysis library of algorithms to do some segmentation and clustering to further analyze
our tweet data for impact or reach and we'll talk about that a little bit later.
And finally we'll use the graph processing engine
to be able to analyze the neighborhood or the connections of the different associations that we find.
So, clustering like-minded tweets together.
The final result will be an interactive application that could be viewed by an end user
using a browser like Chrome or possibly on a mobile device.
So as the tweets come in to Twitter
we will read them into the database, we'll do all of our processing, and we'll show those out to the end user.
The end user might want to filter on that data or might want to create a different hashtag that they want to search.
So we'll push that information back through our processing , back up to Twitter and bring down the new data.
So there you have the Life 5 scenario in a nutshell.
As with all the Building Solutions series from the HANA Academy, please visit the HANA Academy repository on GitHub
for more information and examples of all of the code that's used in these videos.
Thank you for your interest.
We wish you lots of fun as you build out your very own advanced analysis for Twitter data
Connect with us on Social Media to keep up-to-date with the latest content created and published for you of all things HANA.
Thanks for watching.