Big data is an integral part of the information strategy of many businesses, driving operational efficiencies and competitive advantage. For organisations wanting to leverage big data for business advantage, its volume, variety and velocity presents a complex mix of challenge and opportunity.
One of the most compelling opportunities for businesses is to gain added value by analysing big data in a geographic context. The emergence of location analytics tools is driving the ability to discover location-based patterns and relationships from data that may exist in disparate places, streams or web logs.
It is also enabling organisations to visualise and analyse big data to reveal previously hidden patterns. Here, I provide tips outlining how your business, whatever its size and type, can get the most out of a location analytics implementation.
Maximising your analytics strategy
1. If you want to see the story behind your data, bring together maps with multiple data layers.
You can combine big data with maps to optimise your information assets. Retailers can see where promotions are most effective and where the competition is. Credit card companies can map data from transactional systems, customer information and social media, to build profiles of card users to help shape outbound marketing strategies.
Climate change scientists can combine data with maps to see the impact of shifting weather patterns. By visualising data on maps, businesses across all sectors can start to realise previously hidden treasures.
2. Use location analytics to interrogate your data in real time.
Spatially-enabled data on a map allows you to answer questions and ask new ones. Where are disease outbreaks occurring? Where is the insurance risk greatest given recently-updated data? Taken one step further, by integrating social media data into these maps, you can now track dynamic behaviour and sentiment in real-time.
There are huge potential benefits. Big data technologies provide access to unstructured machine-generated, web-generated and NoSQL data. Map visualisation and spatial analysis on this data can reveal patterns and trends that are beyond the capabilities of traditional databases, spreadsheets and files.
3. If you are looking to use mapping to harness large data volumes more efficiently, learn from the experience of others.
Now, with the emergence of GIS tools for big data processing frameworks like Hadoop, analysis and predictive modelling can be carried out on massive data sets to gain unrivalled insight. Governments can use it to design disaster response plans. Health service organisations can model the potential spread of a disease and identify strategies to contain it.
The Energy Saving Trust works with the Government, local authorities and commercial organisations to help them improve energy efficiency initiatives and reduce fuel poverty. They combine information from big data sources including open data, demographic and solar potential to identify housing that is suitable for specific energy-saving measures.
4. Adopt a rounded approach to data
Big data is not just about a mass of data, it's about an approach to working with data, the location analytics tools required to work with it, and derive business value. The Aberdeen Group's recent report "Location Analytics: Putting the Evolution of BI on the Map" revealed that organisations with data visualisation tools can access timely information 86% of the time, compared to 67% of the time for those without visualisation tools.
This means that BI users without data visualisation have to make twice as many decisions based on gut instinct or incomplete, outdated information.
By bringing together big data and mapping, organisations can tap into a raft of benefits. They can drive faster time to market by highlighting previously unseen patterns within existing data sets. They can bring together different technologies like BI and CRM with Location Analytics to deliver enhanced business insight.
And the combination of big data and mapping can lead to more accurate decision-making as well as delivering enhanced customer engagement, improved profitability and greater competitive edge.
- Sharon Grufferty is head of SaaS product management at Esri UK. She is responsible for product and content strategy across new public and private sector markets
