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15.03.2023 18:20

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A clear plan for the future

Effective database planning means that your

software is capable of managing and

consolidating all the data generated and relied

upon by your business. A good database plan

will allow your organisation to develop a clear structure for the way in which data is stored

and managed by every person or application using it. This process will also help identify a

base for future needs and could provide the framework for both an immediate and long

term growth strategy.

Optimising your data

With your input, we can produce detailed plans and database diagrams to represent the

structure of your database. Our goal is to optimise the performance of the database by

determining the exact amount and type of information required. Planning databases in this

way will also identify any necessity for default values and constraints on the data being

stored, as well as the potential relationships between certain areas of the database.

Relational databases allow for multiple types of data 'objects' to be stored with keys and

indexes to link related data across multiple tables. For example, one table holds customer

details and assigns each customer a numeric ID, while another table holds order details,

including the customer ID - removing the need to duplicate customer details if there are

multiple orders from the same customer. This approach is referred to as data normalisation

and in its simplest form, attempts to minimise data redundancy. Normalised database

structure ensures concise database architecture with the elimination of unnecessary data

duplication, as well as the potential for optimised database operations and balancing

workload between the databse server and the web server, for example. Having the correct

plan and structure for your database also has arguably the most important benefit; greatly

reducing the potential for human error, making the data flowing through your bespoke

software robust, reliable and scalable.

Beyond the structure

Our database engine of choice is Microsoft® SQL Server® for all of our new build

projects. Similar to many other enterprise level database engines, Microsoft SQL Server

allows the planning process to go a step further towards managing your data, as opposed to

just storing it.

We try to take advantage of these features wherever possible. Some of the features we

commonly recommend in our database plans:

 A feature that our clients find more useful than any other is 'Full text catalogs'.

This feature allows the database engine to create a detailed store, or 'Full text

index' of desired textual content within your database. This full text index enables

textual searching based on language, proximity of words, inflectional forms and

thesaurus-based expansion sets, and can rank results on their accuracy. This is

true search engine capability.

 'Stored procedures' are one of the most commonly used functions provided by

modern relational database engines. Stored procedures are scripts written in the

native language of the database engine and housed in the database that can

perform almost any operation, from the simple to the extremely complex. They

execute only within the database, but can be invoked from both inside the

database (as part of a trigger, for example) and outside the database from

connected software, like a web or desktop application.

 Using 'Views' as part of your database structure, the database engine can cache

predefined queries that join data from multiple sources into a single table,

encouraging faster access to commonly requested data.

 Including database 'Triggers' into your plan allows for the provision of

programmable functionality that is executed automatically upon an action

occurring within the database. For example, your content management database

maintains a virtual path for each folder and file within it. Updating a folder's

parent ID (moving it from one folder to another) triggers the database to

recalculate and reassign the virtual path for each folder and file beneath the one

moved. The content management system we built for this site does exactly that.

 Defining relationships between tables adds an extra layer of assurance that your

data maintains its integrity. In simple terms, this means that changes made to data

in one table can cascade down through related tables. For example, assigning a

new stock keeping unit (SKU) code to a product in your products table will

cascade down to your orders table; updating any orders awaiting processing that

contain the same product.