The Program Development Life Cycle (PDLC) consists of the following stages: Analyse the problemAnalyse and define the problem, check and understand that the problem is clearly defined. What are the inputs /outputs, process steps, logic, rules and requirements.Design the solution (program)Design the solution using tools such as flow charts and pseudo-code.Code the programUse appropriate tooling … Continue reading Program Development Life Cycle (PDLC)
Agile makes me think of the agile attribute used in role playing or when discussing comic book characters (e.g. Spider-Man). Agile in Software Engineering, and business, terms is very similar in that it is a mindset that helps deliver small incremental changes quickly. Like Spider-Man using several small quick jumps / web swings to get … Continue reading What is Agile?
Stop. Take a moment or two to look away from this review and at your surroundings. If you are reading this outside on a smart device (tablet, phone etc..) you may see roads, power cables and cell towers. If you are indoors you probably have electricity, internet connectivity and water flowing into your building (in … Continue reading Engineering In Plain Sight – Book Review
During a recent administrative task I needed to make a list of all members of a local group on a Microsoft Windows device. Originally I opened up Computer Management and started scrolling through the group. Physically writing down each member would take some time and I prefer the command line approach. A quick (and quite … Continue reading Exporting Local Group Members (Windows)
“Don’t let fear get in the way and don’t be afraid to say ‘I don’t know’ or ‘I don’t understand’ – no question is a dumb question.” (Margaret Hamilton) The title "The History Of The Computer" makes me think of a heavy, hardback book filled with pages of text and no pictures. The type of … Continue reading The History Of The Computer -Book Review
Five decades of video game fun is heading back to the Manchester Museum of Science & Industry (MOSI) for Summer 2022. I've previously blogged about Power UP (back in 2018), and made a short YouTube video when I visited in 2019: https://www.youtube.com/watch?v=3qm6d90tVt4 Sadly the last two years (2020, 2021) reduced my visits to tech events … Continue reading Power UP Is Back For 2022!
With my Data Analytics learnings continuing at a fair pace I need to be able to turn data into something nice (e.g., plot it onto charts). I could use Power BI or R , but as regular readers may know my preference for most tasks is Python. Python offers several libraries that are great for … Continue reading Jupyter Notebook via Docker on Raspberry Pi (Python, Raspberry Pi)
Continuing on with my Data Analytics learnings, with a jump into Descriptive Statistics vs Inferential Statistics and an attempt to clear up Population vs Sample from my last blog post. Descriptive Statistics Descriptive statistics takes a sample, e.g. a group and records data about that sample. The data is then presented in summary statistics and … Continue reading Statistics: Descriptive vs Inferential, Population vs Sample (Notes)
When discussing data variability (i.e. how much the values vary) there are two methods that can help. These are Sample Standard Deviation and Sample Variance. Other Terms That Are Needed Measures of Centre The middle or centre of the data. Measures of Spread How diverse from the Measure of Centre data is, or how concentrated … Continue reading Data Variability: Standard Deviation and Variance (Notes)
A quick overview of the differences between SQL and NoSQL. SQL Structured Query Language (SQL) is used for relational databases, which are table based. For example, an column in table A (e.g. User_ID) may have a relation with a column in table B (e.g. Order_Ref) and table B may have a relation to a column … Continue reading SQL vs NoSQL (Notes)