Layering collated data – the future of construction?

The term ‘collated data’ comes from the process of collating or gathering together.

This kind of layering is extremely useful for combining individual datasets that may have been generated for very different purposes – such as geographical, statistical, and financial information – into a single cohesive set.

Contrast this with the existing practice of simply merging all the datasets into one huge entity and leaving it up to manual processes to try and make sense of this new cross-discipline resource. By using these layers, each element becomes more usable while also contributing to an overall understanding of the whole dataset. Data can then be rearranged according to specific requirements without needing to start again from scratch.

If we consider a single company as an example, collated data can help to demonstrate specific performance and financial targets. We may be able to see the yearly percentage change of liquid sales compared with that of non-liquid sales across all stores in the country and how this compares with other companies’ results. This could also include information on local demographics and weather patterns, allowing us to better understand if there has been any variation in customer behaviour; for example, do more people spend at the shops when it rains?

By layering additional facts relating to spending habits, such as birth rates or tourism statistics, we can determine the regional impact on local store sales across different industries – whether those be clothing shops or car rental outlets.

To make the best use of collated data, it is important to understand exactly what we mean by ‘data’ in this context. Basically, anything that can be collected or stored electronically falls into this category: text, images, video, and audio files etc. Databases are also a form of collated data; they contain structured sets of information that can be easily accessed by multiple users simultaneously.

We must recognise the importance of thorough analysis at every stage of the collation process. Laying down certain fundamental principles – such as capturing all relevant facts and leaving none out – will ensure adequate coverage for any subsequent work on collating data. In essence, there’s no point making copious notes if we fail to include some extremely vital element later.

Ultimately, using collated data allows us to make better-informed decisions and ultimately become more successful as businesses or organisations. By layering different datasets together in this way, we can gain a greater understanding of how all the pieces fit together and use that knowledge to our advantage.

More articles to come in the following weeks.

To find out how the Ulti-Mate® range of screw fastenings can make your business more efficient, call Andy Boden on 07706 783563 or email

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