Advantages of using Django? (#63)

By |2018-10-20T23:56:47+11:00October 17th, 2018|Django, Newsletter|

So what are the advantages in using Django? It does make the modelling easy, but it also adds some extra constraints or complexities. There are many advocates of Django and many places where people will try to answer the question “Why use Django?” In the table below, I have included links to eight such articles, [...]

EPANET Modelling in WaterSums – Part 3 (#62)

By |2018-10-11T17:44:02+11:00August 24th, 2018|Django, Newsletter|

Some time ago when we looked at modelling the simple example of Hezekiah’s tunnel (EPANET Network Components – Database tables and rows, Part 1 (#18)), we discussed the options for creating our data tables including some ways to use a class hierarchy.  EPANET has nodes (junctions, reservoirs and tanks) and links (pipes, pumps and valves) which [...]

EPANET Modelling in WaterSums – Part 1 (#60)

By |2018-10-11T17:25:58+11:00May 25th, 2018|Django, Newsletter|

Many software programs that model water supply networks use the public domain EPANET modelling engine for analysis.  EPANET defines many different types of object which can be contained in such networks and settings for simulation of events in the networks.  EPANET also defines an input file format which can describe these objects and settings. [...]

Django and sub-classing (#54 – #56)

By |2017-11-14T17:17:57+11:00October 17th, 2017|Django, Modelling principles, Newsletter|

When modelling data, we often need to distinguish between different types of objects.  For example, a mapping application may need to store information about both roads and lakes, or a library catalogue may need to store data about both books and DVDs.  With these examples, the objects can be quite diverse and the details stored [...]

Hardware hides performance pitfalls (#52)

By |2018-10-21T00:09:16+11:00September 21st, 2017|Modelling principles, Newsletter|

Data modelling is not the only limiter of performance. When I first started working with databases, performance in all aspects of computing was much worse than it is now.  However well an expert might craft a query, and however simple the query might be, technical restrictions would always limit the performance to just a few [...]

Missing data (#51)

By |2018-10-21T00:11:57+11:00September 11th, 2017|Modelling principles, Newsletter|

A very common problem with databases is missing data. Missing data makes searches difficult (or impossible) and statistics unreliable. Two common reasons for this are: Records contain optional fields which have been left empty. Records are completely missing because some of the mandatory information was not available. Since the missing data was in mandatory columns, [...]

Which RDBMS? (#50)

By |2018-10-21T00:16:30+11:00September 4th, 2017|Modelling principles, Newsletter|

In this series of newsletters, we concentrate on data modelling in general and discuss relational databases when we need to consider specific applications.  In general, we do not consider the so-called “NoSQL” databases.  Relational database management systems lend themselves to the use of fixed schemas and also provide easy type checking. […]

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