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Data & AI


COVID Survival Kit: Demand & Inventory

I interviewed Michael Walton on Demand and Inventory centric to AI, Microsoft tech, business survival and other topics. Great conversation with a great guest talking about helping businesses maximize their opportunity to succeed in a challenging world.

Nathan Lasnoski by Nathan Lasnoski

Building a Simple Smart Restart Bot with Teams & Azure QnA Maker

You’re returning to work and you want to get your Smart Restart off the ground, but you are concerned about a flood of requests hitting your service desk. You want to create something that will provide immediate value but has a low time to implement. We had the same problem and started with a simple […]

Nathan Lasnoski by Nathan Lasnoski

Practical AI Examples in 2020

In my article on Top 10 Tech Trends for 2020 I started by talking about artificial intelligence as a mega theme where businesses are achieving real, measurable value from the AI front. If you look at any trend analysis on AI you could believe anything from “AI is still vaporware” to “AI has arrived and […]

Nathan Lasnoski by Nathan Lasnoski

Role of Artificial Intelligence in Chatbot Development

Chatbots are among the most visible applications of AI technology. The successful adoption of chatbots by end users has led to the use of more and more bots in advanced artificial intelligence technologies and their usage by a custom software development company.

Akashdeep Kaur by Akashdeep Kaur

Power BI vs SSRS

A detailed description of the differences between Power BI and SSRS

Zed Dietrich by Zed Dietrich

Moving Big data in and around Azure using Azure Data Factory.

There are numerous data storage options available on Azure, each one designed and developed for different modern data storage scenarios. These storage options could be in the form of database, data warehouse, data caches and data lakes. Usage of these depends on the application and the scale that they serve. Within databases, some applications might need relational database, some might need NOSQL, or a key-value storage, or in-memory database (for caching), or blob storage (for media and large files). Another criteria to keep in mind when selecting a database for your application is the required read-write throughput and latency. Azure has a wide array of fully-managed database services which frees up the development teams valuable time in managing, scaling and configuring these databases.

Whatever database you choose, you should also keep in mind how easy or difficult it is to move the data in and out of that database. You might have a situation in future where you need to move to a new database solution because of reasons like change in application architecture, scale, performance, or even cost. Microsoft Azure has a very powerful ETL tool called Azure Data Factory to easily move data in and around Azure at scale. It has over 80 native connectors which can serve both as source and sink.  In this blog, I would like to highlight a few features and concepts of Azure Data Factory which will serve as a quick start guide for anyone looking to do data movement and transformation on Azure.

Siddharth Bhola by Siddharth Bhola

Data Collection on Twitter

Learn Data Collection on Tweeter with python and a Tweeter Developer account.

Alex Zhang by Alex Zhang