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MATTHEW HICKS: Hello, welcome, everyone.
We're so glad to have you join us
virtually for this Microsoft Build session
on Industry aware analytics
with Azure Synapse database templates.
I'm Matthew Hicks, Product
Manager on the Azure Data Team.
In this session, Lakshmi Murthy,
Product Manager for Synapse database templates,
will tell us all about
Synapse and this game-changing feature.
First, we'll learn about some
of the challenges of today's data solutions.
We'll explore what address and apps analytics
offers in this space.
Then we'll learn more about
Synapse database templates with an end-to-end demo.
I'm really looking forward to this.
Lakshmi, the floor is all yours.
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LAKSHMI MURTHY: Hi, everyone,
I'm Lakshmi Murthy,
Product Manager for Azure Synapse Analytics,
driving database templates, and lake databases.
First, let's start by looking at some of
the key challenges customers
face in their data transformation journeys.
Given the volume and velocity
at which data is gathered today,
a common problem among customers
is how to unify this data estate in
a way such that they can quickly reason
over this data and make key business decisions.
In most cases, this data sits
in application-specific silos and
requires huge standardization efforts
to derive meaningful insights.
Azure Synapse Analytics strives to solve
this problem by introducing
industry-specific database templates,
which can be used to provide
a standardized way to store and shape data.
These templates provide schemas
for predefined business areas
enabling data to be loaded
into the data lake in a structured way.
Azure Synapse Analytics is
Microsoft's limitless analytics platform that brings
together the foundational capabilities for analytics,
data integration, enterprise data warehousing,
and big data analytics.
It gives you the freedom to
query data on your own terms,
either serverless or dedicated resources at scale.
Irrespective of the user persona,
be it the data engineer,
a data scientist,
or a business analyst,
Azure Synapse offers a unified experience to ingest,
explore, prepare and manage
data for BI and machine learning needs.
With the addition of database templates,
we are effectively making
our analytics platform industry aware
by enabling business contacts to
reach metadata to describe your data.
These templates serve as industry blueprints that can be
extended or customized to standardize your data.
There are over 5,000 entities and
30,000 attributes across
18 different
industry templates.
The entities are grouped by
business areas and each template has
over 25 different business areas
covering key business functions.
Now let's take a closer look
at how to put these templates to use.
Let me walk you through a typical user journey
with database templates within Synapse.
Users start by browsing through the various templates in
the Synapse gallery and pick
the industry that's of interest,
say for example retail.
Next, users can select a subset of the tables
from the relevant business areas such as product,
customer sales, marketing,
and visually create a lake database.
A template approach means that
your data engineers and architects don't have to create
the database from scratch and leverage the definitions
available through the templates
and customize them as needed.
Once created, you can
populate lake database with data from
various data sources using
data flows and Synapse pipelines.
You can also utilize existing data in the lake by
pointing the link database to
the appropriate data lake locations.
Once data is loaded,
you can query these databases
using either Spark or Serverless SQL.
All of that rich metadata from
the templates add business contacts
to your query results.
This metadata is also available when you connect
to Power BI to build reports and dashboards.
Now I'll give you a quick end-to-end demo of
this capability in Azure Synapse Analytics.
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LAKSHMI MURTHY: I start an Azure
Synapse studio
and navigate to the gallery to
select the database template I want to
use when creating my lake database.
I select "Retail" and click "Continue."
I then land on
the template exploration page where I can choose from
over 5,000 entities to
create my own retail lake database.
These entities are grouped by
business area as shown in the left navigation pane.
Some of the most used tables are
already added to my canvas by default.
I can browse entities by expanding each of
these business areas and selecting
the tables I want to add to my canvas.
I can also search for
specific tables to add to my canvas.
Let's start by clearing the tables on the canvas.
I search for "Customer" in the search box
and then select the relevant table from the result.
I can view the detailed information provided by
the retail database template such as the entity name,
a rich detailed description
of what "Customer" represents
as well as detailed column information
such as descriptions and data types.
I can click into the "Relationship" tab and select
the toggle to see all of the
relationships to "Customer."
I can now search for relationships that I'm
interested in and add those tables to the canvas.
Now, I'm ready to create my lake database.
I then land on the database designer
or the customization experience where I can
choose the location for where my data will
live in my lake and give my lake database a name.
I can also edit the table metadata and customize
the column details like name and
data types aligning it to my organization's data.
I can also create custom tables and custom columns.
Once I finish customizing
my lake database I'm ready to publish.
As you can see, I was able to
create a lake database without writing
a single line of code and now
it's ready for me to populate it with data.
I create a new data flow using
the workspace database connector to
load data directly into the table I
want by selecting it from the dropdown.
I can also add transformation steps during
this step if my source data
does not actually match the table I've created.
I can then add this data flow to a pipeline and
execute it to load data into my lake database.
I can then jump over to
my data lake to see all of that data showing up in
the location that I specified as
a part of my lake database table.
With the data now in my lake,
I can leverage the SQL on-demand
capabilities to easily query
my data and gather insights.
I can also use a notebook experience with
Synapse Spark for
more data science-oriented capabilities.
I can now work on creating
a Power BI report using
the new Synapse database connector.
It can pull in all of the data
from the database I've just created.
The rich descriptions from the template
now show up in the connector allowing
me to easily understand
which tables I need to include for my report.
Power BI also pulls in
the "Relationship" information from the database,
making it easy to quickly leverage
these relationships when I'm building my report.
Next, I can easily continue and build
my Power BI report using
all of the data in my lake database.
By using one of the retail templates
with lake databases in Synapse
I was able to easily load the data
I needed into a single location,
adding structure to my data lake and enabling
quick creation of reports using Power BI.
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LAKSHMI MURTHY: Database templates
and lake databases
are now generally available to all
of our Azure Synapse Analytics customers
at no additional cost.
You can go to your Synapse Workspace and navigate to
the gallery to see all of the industry templates.
Some of the new templates we've
added are in alignment with
the Microsoft industry Cloud such as
healthcare and financial services.
Watch out for new improvements coming soon.
Lake databases will soon support Delta formats,
tight integration with Microsoft Preview
to enable end-to-end data governance,
and also improvements to performance and
exploration and customization experiences.
With that, I'd like to pass it back to Matthew
to wrap up this session. Thanks, everyone.
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MATTHEW HICKS: Excellent demo, Lakshmi.
Thanks so much for introducing us to
the latest improvements to Synapse database templates.
Here are the main takeaways from today's session.
Azure Synapse Analytics allows you to
design your lake databases in
a no-code manner with
the easy-to-use database editor experience.
Synapse lets you standardize the data in
your lakes using database templates.
It comes with 18 detailed models for
various industries and it's generally available now.
Synapse allows you to query your data on
your own terms using SQL Serverless or Apache Spark.
This empowers your business professionals
to build meaningful
BI reports with rich metadata and insights.
That wraps up this Microsoft Build
session on Industry aware analytics
with Azure Synapse database templates.
Thanks so much for joining,
and to learn more and get
started today visit aka.ms/SynapseDBTemplates.