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Data Enrichment – The Nail in the Coffin for Legacy Analytics

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cables 2From weather to crime, smart meters and traffic, the diversity of open data sources is incredibly exciting, but it is also creating a challenge. So how can organisations experiment with this data quickly and efficiently without incurring the untenable costs associated with traditional data analytics.

Unprecedented Data Choice

This concept of data enrichment is not new – leading retailers, for example, have integrated demographic data sets to enhance customer data not only to improve customer understanding but also inform key strategic decisions such as the location of new stores. However, the sheer volume and innovation associated with the new generation of open data sources is radically transforming the opportunity. The choices are virtually unlimited – so just as it presents opportunity, therein also lies a problem: How can organisations begin to experiment with these data sets without incurring prohibitive costs?

Legacy Constraint

Big data is all about being first – organisations need to be able to experiment with these data sets quickly, effectively and cheaply. The latest generation of analytics database technologies have been designed not only to manage vast data quantities but also to compress that data into manageable – and affordable – volumes and provide the business with the insight required. Exploiting innovation in areas such as data compression and pattern matching, these solutions require not only minimal infrastructure – and hence cost – but deliver a new way of locating information within the mass of data to enable rapid exploration of each new open source dataset.

Future Cities

With the right model organisations can embrace these new data sources quickly and efficiently Take the smart city project underway in Milton Keynes which is collecting vast amounts of data relevant to city systems from a variety of sources, such as local and national open data repositories; data streams from both key infrastructure networks, including energy, transport and water and other relevant sensor networks such as weather and pollution data; satellite data; and data crowd sourced from social media or through specialised apps.

The diversity of data being collected and shared is amazing and will provide a chance for innovative organisations to devise extraordinary new ways of exploiting that data to drive better business. For example, a retailer can use smart information feeds from utilities regarding planned and emergency works that may affect customer access to stores and automatically contact customers due to use click & collect that day and suggest an alternative location. This is a simple but effective way of not only ensuring the click & collect service is unaffected but also improving overall customer perception.

Time for Change

Companies have begun to recognise that the old fashioned goliath databases have no place in the big data era. This new data model is all about speed of response and about creating actionable insights within a timeframe that enables truly effective business change.

Data enrichment is fast becoming an essential sidebar to every big data strategy – isn’t it time for every business to accept the need for a new analytics model that enables fast, effective and affordable data experimentation?


Laurence Armiger

Laurence Armiger

Laurence Armiger is Sales Director for Zizo where he responsible for working with customers to deliver business benefits by quickly transforming raw data into actionable information. Laurence believes that businesses of all sizes should have the ability to access and use data to improve their business, without the costly investment associated with traditional big data solutions.

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