One of the speakers, Tony Cosentino, VP at Ventana Research, shared the Big Data Analytics trends as follows:

• Moving from 20^th century designed data to 21^st century organic data; from confirmatory analytics to exploratory analytics
• Moving from sample type of analytics to sensors type. Analytics and data are coming together into one environment instead of being separate.
• Moving the conversation from data to outcome or business orientation

I was particularly interested in Tony’s speech so I did some research about these trends as follows:

• Designed data vs. organic data:

This Census Bureau’s blog explains that the Census Bureau has created “designed data” based on pre-specified purpose. In contrast, data collected  through internets, sensors and other systems are organic data. The blogger believed “The combination of designed data with organic data is the ticket to the future”.

• Sample data vs. sensor data:

Sample analytics is used widely in the conventional market research. The research population is generally too big to be covered in a survey; therefore, researchers usually choose a portion of the population (i.e. sample) to do a survey. The sample size and selection are carefully determined in order to capture the representation of the whole population.

A sensor is a device that measures a physical quantity / activity and transforms it into a digital signal. Sensors are always on, capturing data at real time and powering the “Internet of Things.” Sensors can collect enormous data and Cloud computing and storage help to make the analytics possible.

• Conversations on data vs business:

Data itself is not the focus of the conversation anymore. Nowadays, the business value provided by the big data is the focus.

I agree that the combination of organic data and design data will create valuable data. I believe we need to have a sampling mechanism with organic data since the volume is big. For example, NFC is one of the sensors. When the technology takes off, it will provide interesting data sets. How to translate the data into value added information for businesses take specific design.

This Hadoop blog suggests that “sensors can be used to collect data from many sources, such as:

• To monitor machines or infrastructure such as ventilation equipment, bridges, energy meters or airplane engines. This data can be  used for predictive analytics, to repair or replace these items before  they fail.
• To monitor natural phenomena such as meteorological patterns, underground pressure during oil extraction or patient vital statistics during recovery from a medical procedure.”

I think sensors go beyond these domains. For example: an NFC embedded wearable device can monitor body movements and vitals, such as heart rate and blood sugar. Digital health and fitness mentioned in a blog of Aaron Rose  is possible because of the sensors. The Fujitsu NFC smart glove shows a use case beyond digital health and there is unlimited space for monitoring these types of innovations.

These thoughts were triggered by a two hour Meetup. Can you imagine what thoughts will be triggered in two days? I am looking forward to attending the Big Data Innovation Summit held in Santa Clara on April 9 and 10^th. With 80+ sessions, it will definitely broaden my vision and expand my imagination.

What are your thoughts on these trends?

Big Data Innovation Summit 2014

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