This course covers the current state of Business Intelligence in the cloud, as well as goes into functional examples using Google Big Query and Tableau Online. This is a beginner course, but it is assumed you are familiar with the basics of databases and business intelligence concepts.
I work as a feedback mechanism for organizations and teams to help them understand what’s going on with their products and processes. I do this by collecting and organizing their data, visually exploring it, enriching it with other data and metrics, then presenting my findings using creative information design techniques. This leads to improved business performance and often sparks a data-driven culture throughout my clients organizations.
Business Intelligence Overview Hey everyone! This is Ben Sullins, and welcome to this course on Cloud Business Intelligence: The Big Picture. In this course we're going to talk a lot about doing business intelligence in the cloud and what that means in today's world. It's been a long time coming, and the cloud is pretty mature now, but the BI world has been falling behind quite a bit. So, in this course we'll walk through all the different vendors and how to think about it and even some functional examples later on about how to accomplish this. Let's kick off the conversation with talking about why we have business intelligence in the first place.
Cloud BI Vendors In this module we're going to take a look at some Cloud Business Intelligence Vendors. First I want to talk about the types of vendors there are. We basically have two different categories. If you remember from our diagram here on the left we have our data sources coming in, they flow into a data warehouse structure, and then they flow out into our business intelligence outputs, our dashboards, our charts, our analytics, our recommendation engines, etc, and the two that are most prevalent right now in the cloud are the BI as a Service, the guys in the upper right taking care of all the analytics, the presentation, the aggregation, the actual analysis, and down below the Data Warehousing as a Service, basically a place where you can put all your data so then later you can analyze it. There's also a third type that I'll get into, but first let's take a look at BI as a Service.
Google Big Query Hey! This is Ben Sullins, and welcome to this module on Google BigQuery. Let's review where Google BigQuery fits into our picture here. Remember we have our BI products as a Service that provide all the analytical capabilities, the charting and graphing, and we have our Data Warehousing as a Service, which provides our data storage and aggregation and query access. And the latter there is where Google BigQuery fits in. It is incredibly robust. You can store terabytes, possible petabytes of data up on the cloud in Google's servers and access that through several different really easy methods that really take all the headache and hassle out of standing up a really petabyte scale data warehouse away and allow you just to really focus on the data. Imagine if you just upload your data and then you start using it. And it really is that simple, and in this module that's what I'm going to do. I'm going to walk through all the steps you need to actually start using Google BigQuery as a Data Warehouse as a Service.
Tableau Online In this module we're going to take a look at Tableau Online as our BI as a Service cloud platform. Let's review what our diagram looks like for the overall picture here. We have our Data Warehouse as a Service, which we just looked at Google BigQuery for that option. Now we're going to take a look at the BI as a Service, and we're going to look at Tableau Online.