I will fully admit that when I started using AWS, it took me a while to learn Amazon's "language." Unfortunately Amazon does a bad job of distinguishing between their core offerings (e.g. S3, EC2, Route53, etc) and their very niche ones (e.g. EMR, Kinesis, SWF, etc), so new users are left scrambling to figure out what they need to know.
I understand their desire to create unique "products" that people can use in a conversation (e.g. "Have you considered Route53 for your DNS?"), but ultimately mixing common and niche things together and giving everything confusing names is likely doing Amazon more harm than good.
That all being said, Amazon are slowly improving. See this page[0]. They now have a list of their products and how they fit into different categories. But the console can still be a jumbled mess of different acronyms and made up words.
This is why I REALLY like the MS/Azure way of doing things.
"I need to host a web app" "Okay there's Azure Web Apps for that"
"I need to store lots of files" "There's Azure Storage/Blob Storage for that"
"I need a SQL Database" "There's Azure SQL for that"
"I need a VM" "There's Azure Virtual Machines for that"
"I need a Data Lake" "There's Azure Data Lake for that"
"I need a Data Lake" "There's Azure Data Lake for that"
"I need a Data Warehouse" "There's Azure Data Warehouse for that"
"I need a Cache" "There's Azure Redis Cache for that"
I could go on, but you get the picture. Cute names are not the way to go when you're offering dozens of services which may overlap with eachother somewhat. I can just scroll down a list of things MS offers on Azure and be able to easily pick out the things I need to use by their names alone.
"A massive, easily accessible data repository built on (relatively) inexpensive computer hardware for storing "big data". Unlike data marts, which are optimized for data analysis by storing only some attributes and dropping data below the level aggregation, a data lake is designed to retain all attributes, especially so when you do not yet know what the scope of data or its use will be."
The intended use is to be able to use things like Hadoop or other tabular text processing systems to glean information from enormous amounts of data, then once valuable insights are found, use the Data Lake source to process it into a form suitable for a data mart, or preferably, a data warehouse.
I understand their desire to create unique "products" that people can use in a conversation (e.g. "Have you considered Route53 for your DNS?"), but ultimately mixing common and niche things together and giving everything confusing names is likely doing Amazon more harm than good.
That all being said, Amazon are slowly improving. See this page[0]. They now have a list of their products and how they fit into different categories. But the console can still be a jumbled mess of different acronyms and made up words.
[0] https://aws.amazon.com/