Which postcode sectors adjoin each other? MapMechanics offers fast way to find out
Ready-to-use lookup table and 2011 Census data package underline Process Promise
Two new products from MapMechanics, the UK-based specialist in digital mapping and related data, underline the benefits of the company’s Process Promise scheme, which saves users from many of the intricacies and hassles of preparing and formatting map data for their specific requirements. MapMechanics processes the data so the user doesn’t have to.
A new data set called Neighbouring Postcode Sectors allows users to find any postcode sector bordering on another given sector – in this case without needing any supporting map data; and data from the 2011 Census is now available from MapMechanics as a package that comes complete with boundary lines, giving it a built-in geographical dimension.
The Neighbouring Postcode Sectors data set is brand new, and reflects MapMechanics’ readiness to respond to users’ requirements by developing appropriate products. In essence MapMechanics has processed the postcode sector data to create a lookup table of 9,251 postcode sectors in Great Britain, cross-referenced with all adjacent postcode sectors.
Without this type of lookup table, users would not be able to identify that, for example, RG17 7 is adjacent to OX12 8 but SW12 9 is not next to SW13 0. Whereas typically it would require map-based analysis to find adjacent postcode sectors, this data set can be used without specialist software. It is seen as ideal for many applications such as business intelligence and territory management, where using separate map data might be unnecessarily complex or expensive. It also has appeal in logistics planning and management.
The file is supplied in the user’s chosen format, including for example simple CSV (comma-separated value) text format, which makes it compatible with most spreadsheet and database applications, as well as with mapping software.
Example data directly from originator - boundary extends into the sea to encompass an island
Example data after the Process Promise has been applied - the extension has been pulled back to the standard coastline
The 2011 Census data, provided by MapMechanics at local authority level, is another example of how MapMechanics processes data to make it easier to use. The MapMechanics 2011 Census data is provided in ready-to-use GIS formats, with the population counts already attached to matching boundaries (which are included in the product). This means that the user can start creating shaded maps immediately in order, for instance, to identify trends, hot spots and gaps in the market. The first release includes information such as population levels, household numbers, sex and age groups.
MapMechanics can provide the data in a form to suit a wide variety of mainstream computer applications used in digital mapping and analysis – for example GeoConcept, MapInfo and ESRI products, and spatial enterprise databases such as Oracle and SQL Server.
The Process Promise scheme was launched by MapMechanics in recognition of the fact that raw map data and related geodemographic and business intelligence data is often supplied by the developers in a generic form, which may not be immediately compatible with mapping or other software, or easy to use straight out of the box. Roads may not be correctly linked for routing applications. Boundaries may not be closed, meaning they can’t be filled with colour to make a shaded trend map. Data from different originators might also be more useful when linked together and grouped to different geographic levels.
Such data may require special processing and formatting to suit the intended usage – a task that can take many hours, and may be beyond the technical competence of less experienced users. Even where it is ready for use, the data may benefit greatly from the kind of enhancement that is seen in the Neighbouring Postcode Sectors data.
MapMechanics’ Process Promise takes care of these tasks in advance, and optionally can also include the provision of suitably formatted updates when they become available. In essence, Process Promise converts raw data to real-world requirements, saving users the need to do the job.