Welcome back.
In this lesson, we are going to continue
our discussion of some Azure services
and we are going to introduce Azure Synapse Analytics.
So in this lesson,
we're going to talk about Azure Synapse Analytics.
So what is it?
Let's give you a brief introduction.
We're going to talk about the architecture
of Azure Synapse Analytics,
and then we're going to take a little bit of time
to actually jump into the portal
so you can see what it looks like.
So let's start off with our introduction.
Azure Synapse Analytics.
What is it exactly?
Well, to start off with it's SQL.
And so when we talk about SQL
if you remember from a previous lesson,
we talked about structured data, relational databases,
(that chart) and we talked about SQL and NoSQL.
This is SQL.
So you need to keep that in mind. It's very important.
It's more than SQL, though.
Azure Synapse Analytics actually includes data integration,
enterprise data warehousing, and big data analytics.
So Microsoft likes to say Azure Synapse Analytics
brings worlds together with a unified experience
to ingest explore, prepare, manage, and serve data
for immediate BI and machine learning needs.
Basically what Microsoft wanted to do
was take SQL Data Warehouse along with some other services
like Data Lakes, Data Factory,
and actually build a unified service
that's going to allow you to stay in that service
and really do an entire data engineering experience
from start to finish.
That was the goal for Azure Synapse Analytics.
And so when we look at the architecture
for Azure Synapse Analytics, we have 4 main components.
We have our ingest phase,
so this is going to be basically taking Data Factory
and putting it into Synapse Analytics.
We have our store phase,
which is going to allow you to use Data Lakes,
Blob storage, and SQL databases.
Prep and train;
so this is kind of combining Databricks
and Azure Machine Learning together.
And then our model-and-serve phase,
which is going to be modeling data
in a SQL Data Warehouse-like experience.
So seeing that in action,
this is what it actually looks like.
You can see that we have our ingestion source
and we're going to use something like Data Factory
to pull that data in.
And I'll show you this in just a second.
And then we are going to store that data
using our big data storage services
like our Data Lakes, prep and train using Databricks,
and then we're going to use our model and serve,
which is your SQL Data Warehouse,
again, all of this is Azure Synapse Analytics.
And then all of that gives you outputs
into either kick-off other apps
or it allows you to give insights
into something like Power BI.
And here is a chart
kind of showing this in a different image.
So you can see all of the different services
and how we kind of have a cyclical approach,
so that we can stay within Azure Synapse Analytics
and effectively manage our data warehouse experience
or our data engineering experience,
assuming we're using things that would belong
only in Azure Synapse Analytics.
Now don't get too hung up on this,
we are actually going to have an entire section,
where we talk a lot about Azure Synapse Analytics,
we're going to talk more about Data Factory.
So again, this is the introduction section,
so don't get too bogged down
into having to know all the details.
What I want you to understand is
the overarching architecture, and what's kind of happening
within each of these services.
So with that, let's jump on over
and let's take a look at Synapse in the Azure portal.
So I've opened up the Azure portal,
and I've clicked on Azure Synapse Analytics Studio.
So rather than go through all of these buttons,
let's actually jump over here to the left,
this is more of a visual representation
of the guide over here on our panel.
So let me expand that.
And over here we have our Home,
Data, Develop, Integrate, Monitor, and Manage sections.
In our Data section,
you can actually see any databases that you have linked.
This is going to be a very nice way
to go through and actually see your data
with a directory approach or hierarchical namespace,
if you remember our Data Lake.
So we have our Storage Gen2 here.
This is just the standard database
and then it would open up and show you
all of the data inside here if we had it,
and we could, kind of, drill down
into where our databases and files live
and then actually see those as well.
Develop. Develop is a place that we can go in
and we can create SQL scripts or notebooks or data flows.
And then when we're not working with our data directly,
we can come into our integrate
and we can actually use pipelines.
So we've been talking about this
in Data Factory for a while,
this is almost an exact replica of Data Factory,
but it's in Synapse Analytics.
So we can click on this and we can actually
start to build some different pipelines.
So let's just say, for example,
that I have 2 different data sources,
and again, I'm going to show you how to do all this later,
I just want to give you
kind of a high look at how this works.
So let's say I had 2 different ingestion sources
and I'm going to ingest data into the Cloud.
I could take those and move those 2 sources
into a Data Lake,
and then I could kick off
a notebook as well if I wanted to.
And so we can start to build some different pipelines
that we can use for our Azure Synapse Analytics workloads.
And then finally we can come into Monitor
and we can see all kinds of information
about our databases and about our pipeline runs,
so we can kind of see what's going on over here.
So again, very high-level look,
but I wanted to give you just a kind of a sneak peek
of what you'll be seeing later on in the course.
So in review, what do you need to know?
First, you need to know what Synapse is
and what it's used for.
Synapse architecture. You need to keep in mind
the main components that are in Azure Synapse Analytics,
so that you can kind of get a feel for what is
and is not possible in Synapse.
Keeping in mind, of course,
SQL, structured, relational databases,
keeping that in mind as well.
And then as we move through the course,
it's not as important for right now
that you understand what you saw in the portal,
but as we move through and, especially,
as you start getting more practice and hands-on labs,
you need to get a good feel for,
"Okay, I know where this is,
"I've clicked on these different things,
"I understand how it works,"
because that's going to help everything click together
when you're taking the exam itself.
Alright, that's it for our introduction
to Azure Synapse Analytics,
I'll see you in the next video.