Location Intelligence

“Where” takes on the big data challenge

By Lorena Hathaway

Everybody’s looking to add context to business decisions—but it’s not so easy.  By 2017, over 30% of enterprises will access big data via intermediary data broker services (Gartner). However, a KPMG study found that 85% of CIOs and CFOs are still having trouble accurately analysing and interpreting their existing data.

Organisations need ways to link the data they own and the data they acquire. They also need a way to keep up as data volumes and velocity continue to grow. Fortunately, that’s getting easier.

People move. Boundaries are redefined. Infrastructure grows. Natural disasters happen. Locations though stay the same.

Latitudes and longitudes provide a common denominator, pinpointing those locations with precision. In the swirling tsunami of data, these geocodes are rock steady. They’re the constant that can be used to link information across data and datasets.

So many people are using geocodes to create maps. In addition to cool, real-time visualisations, they’re layering in demographic, geographic and even industry-specific detail.

Things get really exciting when you see how geocodes can help to integrate, improve and expand insight. Here are a few examples:

  • Pitney Bowes and SAP HANA® support seismic processing and 3D visualisation.
  • GE Predix is embedding Location Intelligence into the Internet of Things.
  • Law enforcement agencies are detecting crime patterns.
  • Banks are uncovering relationships that others miss to avert fraud.
  • Organisations across industries are driving better Business Intelligence for their clients.

All of these things are possible because of geocodes.

Pitney Bowes has taken geocodes a step further. Today analysts spend hours upon hours creating rules and running programs to add the most accurate latitude and longitude coordinates to their data. But there’s no need to reinvent the wheel. We’ve developed a massive dataset called Master Location Data. At 170M+, it’s the biggest dataset of known US addresses. (It even includes non-USPS addresses). Every location is pre-geocoded. The quality of every geocode is coded. And every address is assigned a unique identifier.

This eliminates so much work for analysts. They don’t have to mash together different datasets to test the accuracy of addresses. It’s already been done for them. This is data that is multi-sourced and continuously improved, with the accuracy of each geocode designated.

Master Location Data is so efficient, inclusive and precise, it can help analysts assess both big picture questions (like network optimisation) and detail questions (like flood risks for particular properties).

Businesses can optimise geocoding to improve and enrich the addresses they have. They can also use the “open” version of this massive dataset to identify addresses they don’t know, like territories with similar characteristics to their strongest markets, best prospects for balancing insurance portfolios, the optimal intersections between “homes-passed” and best potential telco customers.

Suddenly, big data becomes so much more manageable, informative and empowering. Who knew geocodes would be the key to so much insight?

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