Big Data & Digital Marketing

I was not aware of the existence of economic theories that disagree with the positive effect of the digital revolutions. Their main points are:

1. The impact of the current ICT revolution is not as radical as the previous one (steam engine, railways, telephone ...)

2. Too many traditional businesses are disappearing, and the average required level of skills to enter the market is going up

3. The peak of the revolution has passed, and the progress is slowing down.

Mark Cliffe, ING's chief economist, replies like this:

1. Part of the current growth slowdown is due to the financial crisis

2. One needs more time to evaluate the impact of new technologies (even electricity took decades to have its full effect)

3. A key aspect of the "Anytime Anywhere" technology is its network effects, i.e. benefits spread faster with adoption

4. Hundreds of millions of people in the emerging world are being lifted out of poverty

5. The digital revolution is actually increasing, becoming the Internet Of Things, or "Anytime, Anywhere, Anything" economy

In such a scenario machine learning and predictive anlytics will be essential to not drown in Big Data. But keep this in mind: "Machines are for answers, Humans are for questions".

Up to now the Internet of Things has mainly focused on the data generation part (sensors and devices).

It is now time for the Analytics side to take over. Here is where Hadoop can make the difference.

However, my expectations are that IoT will boom with Real-Time analytics, and Hadoop can be of little use in this scenario.

Here are five ways how car manufacturers can use the data cars generate to make our cars smarter:

1. Talking Cars

2. Decrease congestion

3. Proactive Maintenance

4. Self-Driving

5. Personalized Experience

Machine-to-Machine data is growing fast: 71% of companies consider M2M as a way to develop new business opportunities.

In the coming decade 40% of all data will come from sensor data.

M2M is part of the Internet of Things, and here are its 3 main fields:

1. Smart Cars

2. Smart Homes

3. Robotics

After giving us the definition of Big Data, Gartner is now giving us 3 predictions on what will happen with Big Data in Business Intelligence:

1. By 2020,

information will be used to reinvent, digitalize or eliminate 80% of business processes and products from a decade earlier.

2. By 2017,

more than 30% of enterprise access to broadly based big data will be via intermediary data broker services, serving context to business decisions.

3. By 2017,

more than 20% of customer-facing analytic deployments will provide product tracking information leveraging the IoT.

A common challenge when dealing with the Internet Of Things is the lack of standardization. This, in turns, makes it difficult for all of the sensors to communicate, for all of the data to be gathered, analysed and eventually leveraged.

IBM and ARM have teamed up to lower the barrier for developers in IoT: the mBed IoT Starter Kit costs just around 100eur, and can be directly connected to the IBM IoT Foundation (to channel data into IBM Bluemix serivces).

The Internet of Things will include many strange and wondrous devices. That's why analysts at ABI Research predict more than 30 billion devices will be wirelessly connected by 2020. Health-related data collection will play a large role in the IoT, of course.

In sports, injuries don’t just cost wins. They cost money. By one estimate, teams across Major League Baseball spent $665 million last year on the salaries of banged-up guys and their replacements.

Now, the fast-growing industry of performance analytics says it can minimize those massive losses. The trick: using data to anticipate how an athlete will get hurt before it actually happens.

Performance analytics have the potential to extend a player’s career, but it can also reveal hidden physical problems and shorten careers. If a player is shown to be at a heavy risk for injury, what owner is going to pay that person big bucks?

The Internet of Things can dramatically improve the quality of our city life.

- In Birmingham, lamp-posts are being fitted with sensors that can transmit information about cloud cover to offer hyper-local weather forecasting.

- In Seattle 5,000 pieces of rubbish were geo-tagged and tracked around the country for three months to find out whether recycling was really efficient.

- A project in Singapore offers advanced weather forecasts to taxi drivers to get them to places in the city ten minutes before it starts to rain.

- In Germany a3D dynamical city-model was used to show people what the impact of a new railway line would be.

All this is fantastic but scary at the same time and shifts the way the world works. The danger is that when smart cities become a reality, individuals will not be able to control the ways they are monitored or what happens to the information.

The issue has huge implications for society and is going to need serious debate.