Join Lynn Langit for an in-depth discussion in this video Why use AWS data storage services?, part of Amazon Web Services: Data Services.
- Now you might be wondering why I decided to create a course just around AWS Data Services. There's so much more to the AWS ecosystem. Well, there are a couple of reasons. I find the data service options on a particular vendor cloud often drive not only the choice of those services, but actually the choice of the vendor. This is a very, very active development area for the various vendors: Amazon, Google, Azure, and other vendors as well, and I find that as I'm building solutions with my customers, the data services that are available are really critically important in the selection of the cloud itself.
So I really wanted to take the knowledge that I'd gained from real world implementations and share that with you. Another aspect of this is that data today is partitioned not within a set of databases on a server, rather between data services on a cloud. And this might not make any sense to you at this point in the course, but we're going to talk about this and see examples of architectures where data is split amongst, for example, NoSQL databases and relational databases and other types of data storage systems on the Amazon cloud because it makes the most sense given the product line available.
So this is definitely a new direction that I'm seeing more and more in my work as an architect, and I want to show you how I've implemented these types of solutions on the Amazon cloud using their data service offerings. The other thing about the Amazon data service offerings is the strength of the partner ecosystem. It's critically important that what is built is usable by the team you have in-house. So again, I'm going to draw from my real world experience and highlight third-party partners, partners who provide service around key aspects of the use of data, such as importing data, cleaning data, processing data, visualizing data, being able to process complex queries, including machine learning.
The partner ecosystem that exists around the AWS Services in general, but the Data Services in particular, is unmatched, and it's important that you consider that when you're looking at building solutions on the Amazon cloud. Now, just to make this a bit more real, I'm back on the Amazon Web Services console. And I just want to call out the sections we're going to focus on in this course. We're going to focus on the products that are offered in Storage and Content Delivery, that would be files in my vernacular. Databases, that would be relational and non-relational databases.
And if I scroll down here, Analytics, which would be huge data solutions, streaming, processing, and pipelines. Now, peripherally we'll talk about some of the other services that either are new and have an impact on data architectures, services like Container Service and Compute and Lambdas. We'll also talk about some of the other services that I've used with some of my customers that, again, are either new or enhanced. Things like API Gateway and some of the monitoring and administration tools over here as well.
But the core focus for this course will be storage, database, and analytics.
- Why cloud tools matter
- Storage choices on AWS
- RDBMSs such as Core RDS, Aurora, and Oracle
- Working with semistructured data in NoSQL
- Connecting to data warehouses such as AWS Redshift and Snowflake
- Graph databases and AWS Machine Learning
- Working with Hadoop
- Common data scenarios and architectures