Making sense of Microsoft technology


In my role as a Data Platform Solution Architect (DPSA) at Microsoft, part of my responsibility is to keep up with all the Microsoft on-prem and cloud data-related technology and trends, as well as non-Microsoft technology and trends in areas such as Hadoop and NoSQL.  I work with Microsoft clients by first understanding their current data-related architectures and then educating them on which technologies and products they should consider in order to update their current architectures or to build new solutions.  There is a lot of knowledge transfer as most clients are so busy keeping what they have running that they are not aware of many of the products Microsoft has and how they all work together (I often say “they don’t know what they don’t know”).  I like to think of it as I help them put all the pieces of the puzzle together.  And as I mentioned in my previous blog, I try to show the clients The art of possible with the cloud.

It is a daunting task keeping up with all the technology as it changes so often.  Even though I spend half my days learning, I can barely keep my head above water, and that is with me just focusing on data-related products and not all the other Azure products such as networking, web and mobile app services, media services, etc. (we have “cloud solution architects” that cover those products).  To narrow down the technologies a client should consider, I will learn about their environment and ask a bunch of questions.  To help readers of my blog learn about the Microsoft technologies and which one’s might be a good fit, I wanted to list a few documents and blog posts:

Azure Quick Start Guide by me.  This is a short overview with helpful links to most of the Azure data platform and analytics products

Microsoft BI and IM Design Guidance by Rod Colledge (Data Platform Solution Architect at Microsoft).  This document contains a detailed description of the data platform and analytics products for Azure and on-prem and includes example architectures.  This is an excellent document that will give you a true understanding of many of the Microsoft products and when best to use each

Ivan Kosyakov (Data Platform Technical Architect at Microsoft) blog: Decision Tree for Big Data solutions and Decision Tree for Machine Learning.  Also check out his glossary.  These are great blogs to help you narrow down which products to use based on your use case

Azure Info Hub: An excellent list of all the Azure products that is updated frequently.  Includes a short description of each product and the latest news, along with training videos, e-books, whitepapers, tools, and even StackOverflow discussions

Hear are other useful blogs and presentations of mine:


Azure SQL Database vs SQL Data Warehouse

Relational databases vs Non-relational databases

Why use a data lake?


Relational databases vs Non-relational databases

Should I move my database to the cloud?

How does Microsoft solve Big Data?