The Amazing Ways Coca Cola Uses AI And Big Data To Drive Success
“One of the first firms outside of IT to speak about Big Data and AI applications”
Coca-Cola has been a big player in the big-data space in recent years, and have shown many times their practical use of big data as a form to improve products. In 2012 chief big data officer, Esat Sezer, said “Social media, mobile applications, cloud computing and e-commerce are combining to give companies like Coca-Cola an unprecedented toolset to change the way they approach IT. Behind all this, big data gives you the intelligence to cap it all off.”
More recently, Greg Chambers, global director of digital innovation, has said “AI is the foundation for everything we do. We create intelligent experiences. AI is the kernel that powers that experience.”
More and more companies every day are adopting data analytics technologies and applying them to their marketing to optimize their products and create new ones, much like the case of Coca-Cola.
Disaster Response In The 21st Century: Big Data And IoT Save Lives
“Technology improves authorities ability to predict, prevent disasters”
Leveraging Big Data to predict, prepare, and prevent
Even before Harvey made landfall, organizations such as NASA, NOAA, and municipalities were using sensor data, surveillance and satellite imagery to predict not just where the storm was likely to impact, but also coordinate with first responders and law enforcement. This allowed them to identify staging locations, evacuation routes, likely flooding areas, etc., and to be prepared for the worst. Data collected from sensors and meters located throughout the region were mined and machine learning algorithms applied, in order to predict patterns and outcomes.
For example, clustering algorithms helped to determine the probability of where flooding would occur, and allowed agencies to devise a set of recommendations for evacuation routes, resource staging, and the identification of locations for shelters along these routes. The more data collected from past incidents, the more insight these agencies are forecast future behavior, using operations such as regression algorithms. This gives officials more detailed insight into potential problems before they happen, so they can allocate resources in a timely, data-driven manner. There is no doubt data mining played a critical role in the effectiveness of first responders which, in turn, led to a reduction in the loss of lives.
IoT sensors provide a huge potential platform for those that want to collect data. IoT is a fast growing market and with the right technology applied, it could provide extremely significant use cases. Not only is the data collected from these sensors helping preparations for hurricane Harvey as explained in this article, but they also have the ability to help with the aftermath. Smart IoT sensors applied across cities on their networks can alert them when certain areas are dealing with black-outs. During natural disasters like this one, some utility providers may be able to address affected areas with greater speed since they’ll be automatically notified on the statuses of effected areas.
Apple’s FaceID: Get ready for ‘big data’ to get even bigger
“Big Data cemented as trending up”
It’s not just Apple utilizing the benefits of biometric and behavioral authentication. Organizations are realizing the treasure trove of contextual insights and valuable information about customers that are available through sensor-based, ground-breaking technology.
Organizations use big data analytics to monitor the behavior of a consumer, or potential consumer. Insurance agencies can benefit from such data to assess everything from driving behavior or home settings to reduce in-home risks, to health risks based on daily habits and routines to detect anomalies. Healthcare organizations can perform remote monitoring, while the automotive industry can profile drivers via connected cars and autonomous vehicles. Even apps like Maps, Camera, Weather and Uber use location services to cater to users based on their location. Big data is getting bigger, but that’s not necessarily a bad thing.
Transparency will be key going forward. As people often don’t fully read through privacy statements because of their length and complexity, government mandates, such as the EU’s pending General Data Protection Regulation are beginning to require organizations to present privacy statements in a “clear, transparent, intelligible and easily accessible form — using clear and plain language.”
In this article, Dutt speaks on how organizations can gain valuable insights from Apple’s new FaceID sensor. He touches on one of the most talked about issues engulfing the world of big data today, privacy. Dutt explains that if Apple does intend to collect data using the facial recognition software, they should be as transparent as possible, using easy to understand clear language to avoid any issues regarding data protections. Although the data collected from this could bring incredible insights, it would be safe for Apple to proceed with the caution and transparency.
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