Big data new year’s resolutions for 2014

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If you’re anything like me, you’re probably wondering if you can stick to your New Year’s resolutions (unlike last year).So far in 2014 (ten days in) I’ve managed to succeed in one resolution – catching up on reading – and it got me thinking about some “Big Data New Year’s Resolutions.”

Use big data applications to give you something new

We’ve got all this big data, what are we doing with it? Data scientists can use it to find answers, customer service/experience teams can get a better view and understanding of what we’re buying and IT can use the machine data to ensure operational effectiveness. What about developers? My first big data new year’s resolution is to look at the applications we’re going to be able to build in 2014 now we have better access to all the data.

Consider how analytics for contemporary generation data solutions offer something different from data warehouses

Mine the insight your machine data will give you into how your business processes really work

In a previous life I spent many years working in middleware and BPM. One of the challenges was always how to get started in identifying how things “really worked”. This was sometimes described as process discovery. A lot of this information is already captured. Your log files probably contain a very high percentage of a customer’s behavior across multiple channels, both business and technical. This information remains untapped in a lot of cases but probably describes a number of your business processes. I spent some time with a large UK retailer before Christmas. They thought they had modeled their customer processes. When they compared this with the data they were already capturing from their core application log files – they saw the real process was very different, more complex and less streamlined. They appear to have had a very successful Christmas season for sales and positive customer experience having understood their customer “journey” better.

Treat app management and IT operations as a big data problem

Look for the sweet spots where analytics, IoT and big data converge

My colleague, Brian Gilmore, spent some time with the guys at ABI research before Christmas and they are doing some really interesting research into analytics and IoT. If the Internet of Things delivers 10 per cent of what it promises then we’re going to be generating a lot of data that could give us some hugely valuable analytics into our behaviour, the environment, health, security, safety, lifestyle etc. There are going to be some fascinating use cases we’ve only just scratched the surface of and some predictions suggest that it could spark a new industrial revolution.

Security looks like being a place that’s going to drive innovation, proactivity and disruption

A bit of imagination and the spirit of the “garage inventor” will show us something new

Excluding how Santa Claus is using Big Data – 2014 will be a year where we’ll see people start to combine the big data that’s available with their imagination and the spirit of invention. Consistently we see the first person who “gets” big data and what’s possible with it become a very popular person inside an organization. Being able to answer questions you haven’t been able to before gets people’s imagination going. Questions such as “can you tell me what this customer has done” or “when does this happen most” or “do we have information on xxx?” often trigger a company to think in different ways. The phrase “the art of the possible” is probably overused now but when you can see the kinds of value and solutions that can be created in a much shorted timescale than ever before – it does push back the boundaries of what a company considers creating or inventing themselves. You can see this spirit of “garage inventor” and using imagination in a couple of examples – the NHS and New York Air Brake. To quote the New York Air Brake example:
“… Splunk customer New York Air Brake’s (NYAB’s) Train Dynamic Systems Division has harnessed operational intelligence by collecting large volumes of data from freight train locomotives and braking systems. The system calculates and analyzes forces occurring on each of the couplings between freight cars in real time to present an optimized driving strategy to the engineer. Using Splunk for real-time data analysis allows them to notify key personnel about system and driver anomalies, present customized analytics dashboards that give operational insight, and continuously improve optimization algorithms. NYAB is providing insight that eliminates inefficient physics in the operation of those trains and has a potential to save customers a billion dollars or more in fuel costs a year.”
Good luck sticking to your own resolutions and hopefully the above gives you food for thought (just not too much food if you’re trying to keep to a losing weight New Year’s resolution!)