Articles

Partnering with Spot Solutions We have partnered with a WA-based consultancy to combine our network of talented people in order to better service our clients. Spot Talent is our partner, providing coverage across several technology fronts. Spot Solutions boasts a robust network of specialists predominantly based in Australia and New Zealand. With a trusted network built over 20 years, they source talent across all experience levels—from graduates to seasoned veterans. ...

Intro Here is a quick way to setup a new WordPress blog with a custom domain on Azure (optionally using free using credits). Azure Resources Overview Resources used to setup the blog may be seen below. These were created within a single resource group called ‘blog’ WordPress Setup 1. After logging into Azure go the the marketplace and search for WordPress 2. Click create and begin to enter the details for your blog. All resources below were created in a new resource group called ‘blog’ ...

Often we need a fresh copy of the production database in another environment (eg DEV/TEST/UAT). Previously this was a tedious task involving getting a backup file, copying it to another location, restoring the database. Here is a solution to automate this process using Azure Pipelines. User Story Given a production database exists in subscription 1 When we do a release of the Azure Pipeline named ‘_Refresh Database – DEV’_ Then an copy of production is available in the DEV environment in subscription 2 And permissions are correct for the DEV environment Pipeline Overview For each environment that you wish to restore into create an Azure Pipeline with 3 stages. ...

Cloud Adoption Framework For organisations just starting out their journey and those looking to better their governance structure, we facilitate and deliver the Microsoft Cloud Adoption Framework. This will give your organisation a future plan on how to move and operate a governed Azure enterprise environment. To provide optimal cloud infrastructure we will help you · Connect your on-premise Active Directory to Azure Active Directory (AAD) ​ · Connect your on-premise network to Azure · Setup Azure Security Centre to continuously monitor and assess your environment​ ...

Intro Recently I was asked to inspect and old VB.Net Windows Forms & SQL Server application to see determine its future life. Part of this technical review was analysing the code base and database structure. To analyse the code base I used NDepend a well-known code quality analysis tool that has progressed by leaps and bounds since I last used it on the build server circa 2013 (then version 5). Now on version 2019.2.4 ...

Azure Global Bootcamp – 27th April 2019 Slides here

Reactive Architecture with Azure Event Grid Reactive, event-driven architecture Deep dive into Azure Event Grid “Take a ride on the grid” demo series 📈 Why Event Thinking Matters Enterprises should embrace “event thinking” as part of their digital strategy. By 2020, event-sourced, real-time situational awareness will be required for 80% of digital business solutions, and 80% of new business ecosystems will require event processing. — Gartner Top 10 Strategic Technology Trends (2018) ...

Overview on how to publish data entity changes from Dynamics Finance and Operations to Azure Event Grid. Step 1 In D365FO, Navigate to the Business Events Catalogue page Step 2 Navigate to the endpoints tab and select ‘Azure Event Grid’ Step 3 In Azure, create an application service registration Take note of the Application Id and the Secret Id Step 4 In Azure, create an Azure Event Grid Topic ...

To create the D365 FinOps C# OData Proxy do: 1. Install the following plugin https://marketplace.visualstudio.com/items?itemName=Unchase.unchaseodataconnectedservice 2. Using a Visual Studio Standard Library project and add a new ‘Connected Service’ 3. Open the Reference.cs file in VS Code (VS Code seems to handle the file better than Notepad++ and Visual Studio) 4. Search for the EDMX mega string in the file private const string Edmx = @”[mega big xml string we need to change]” ...

Predicting BS using ML.Net Machine learning is typically the realm for R/Python. But can .Net move into this space? In this talk we will run through Microsoft’s new ML.Net framework including what it currently offers, how to build a learning pipeline and how to deploy a model to an Azure Service. https://slides.com/chrismckelt/deck-451cdb94-a37d-47b7-9d49-6686065e7d03

In the previous post we built a machine learning model using ML.Net, in this post we will deploy the model to an Azure app and allow it to be used via a HTTP API Using the output model in zip format ‘vita-model-1.zip’ we can include this in our web application as an embedded resource or simply include the file for deployment. To use the file from a HTTP endpoint: Include the zip file in your deployment – embedded resource/content/read from blob storage etc.. Initialise the model as a singleton during application start up by using a file path or stream Call the model using the function PredictionModel.Predict(‘my data from which to predict’) Sample below that logs to Logz.io ...

In this post we will build a prediction model using ML .Net to classify an individual bank transaction into a pre-defined group using the description text. We will then evaluate the effectiveness of the model using standard evaluation metrics. The steps involved to create a model using ML.Net are: Decide what type of machine learning problem we are trying to solve? Retrieve and clean the data (CSV/TSV used with ML.Net for no) Create a prediction service API Create a ‘Learning Pipeline’ to iterate over the model build process Training Testing Evaluating result metrics Exploring the output model file ...

So what are we trying to do here? Hypothesis Given a users bank statement we will be able to predict (within a statistical confidence level ) the transactions within a period into categories & sub categories for spending classification. Target Categories Banking & Finance Entertainment Food & Drinks Groceries Health & Beauty Holiday & Travel Home Household Utilities Income Insurance Kids Miscellaneous Shopping Transferring Money Transport Work & Study Sub categories available on this link ...

The proposed solution sequence flow follows: Posts in this series Charge Id – scratching the tech itch Charge Id – lean canvas Charge Id – solution overview Charge Id – analysing the data Charge Id – the prediction model Charge Id – deploying a ML.Net Model to Azure Code https://github.com/chrismckelt/vita

Lean Canvas Problem This is the start of a series of blog posts where I try to build an online personal budgeting system. The motivation for this was me trying to do a household budget usin With Open Banking approaching a common service to classify income and expenditure for bank statement transactions is not currently available on the market. The ability for a consumer to categorise their transactions sits within varied personal finance providers (eg. pocketbook, mint). ...

This is the start of a series of blog posts where I try to build an online personal budgeting system. The motivation for this was me trying to do a household budget using existing tools (Pocketbook, CashDesk, QuickBooks, Xero). Each time I needed to classify a large number of transactions manually (except Pocketbook they have got a pretty good classification engine) As I do lots of transfer between accounts the summaries never made sense. So I thought Id give it a go to build my own personal finance budgeter. ...

https://www.rpubs.com/chris_mckelt/capstone-presentation

After initially using Trello with ‘Scrum for Trello’’ to run our companies Agile process and having to manually create burn downs and release estimates with Excel (after mangling data from the Trello API and a Google Spread sheet) we moved to Trello with GetCorrello (and switched to Kanban after a few months with the teams consent) Charts from this tool are below. The GetCorrello team were able to add features on demand. Would use them again! ...

Coursera Practical Machine Learning - Prediction Assignment Chris McKelt 17 September 2017 Introduction Executive summary Background Goal Data Obtaining Data Data Exploration Cleaning Data Training Model build - Random Forest Prediction - Random Forest Model build - Gradient Boosting Machine Prediction - Gradient Boosting Machine Introduction This is an analysis for final assignment of the Coursea course ‘Practical Machine Learning’. http://web.archive.org/web/20161224072740/http:/groupware.les.inf.puc-rio.br/har Executive summary The gradient boosted machine (0.9998) achieved a better accuracy than the random forsest (0.9997) ...

Format to run a small story mapping workshop Elevator Pitch As a team work to decide on the elevator pitch ala For [TARGET CUSTOMER TYPE] who want to [NEED DESIRE], [PRODUCT / FEATURE] is a [MARKET CATEGORY] that [KEY BENEFIT]. Driver, Approver, Contributors, and Informed Identity key objects and people to deliver Story mapping Story Map Structure: Goals > Activities > Tasks > Stories