Since I have begun working in banking industry, I will start a new learning project. I will rewrite my previous currency collector to use the OpenExchangeRate API for real-time data for a given set of currencies like Bitcoin, ethereum, USD, NOK and EUR. The OER API supports the following currencies. At the current time, the developer plan only cost 12$/month with 10K calls to the API – a good deal, if you as me.
My new employer komplettbank.no offers consumer loans and credit cards at the moment. But in my learning project, I will expand this to involve currency loans and maybe blockchain with bitcoins and ethereum.
I will create entities for customer, account, loan and currency, in addition to supporting entities for calculating risk and corralation. My goal will also include to add some machine learning into this for a starter. In addition, i will create a BOT for asking for currency rates and currency conversions.
My goals will be to use Azure SQL, Web Apps and Azure Functions and/or Azure App Fabric for a Microservice application architecture.
Happy coding and designing…
There have been a lot of blog articles about chat bots and robots that will invade our daily life. Don’t worry, they are already here. Microsoft Azure
has a lot of services that can be used to create Bots of different kinds.
Azure has some powerful cognitive services
that enable chat bot to accept user input categorized as utterance – either as voice or written text. Azure has Speech APIs
and Translation APIs
to convert back and forward between speech to text, in addition to translate between different languages.
The past years, Microsoft Azure has released a lot of services around analytics and data management. Many of them is centered around what is called Cortana Intelligence Suite
(CIS) shown in the picture below:
This suite connect many services together and shows the way how Microsoft is defining Analytics for the future. On the right bottom side the chat bots are resides with mobile and web applications. In short, CIS collect on-premise and cloud data from a different of sources like IoT devices, external apps, APIs and similar. These data can be stored in Data Lake Store
or SQL DW that is the basis for analytical services as Azure Machine Learning
, Data Lake Analytics
and Stream Analytics
. The data from the storage or result of analytics tools can be visualized with PowerBI, and queried with web/web/bot applications.
But this will be the topic of future blog posts – over and out!