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When the internet and world wide web first came to life in the early 1990s, few predicted that entire industries, businesses, cultures and governments would be transformed by the technology. Today, with 5 ounces of amazing mobile phone power in their hands, more than 3 billion people on the planet are participating in this ongoing digital revolution.
In the last decade, cloud, social and mobile technologies, along with greater wireless broadband access around the globe, have pushed digital technology into the mainstream of everyday life. Everyone and everything is becoming connected.
Running a business from a smartphone
When we started Salesforce 15 years ago, I never expected that I would be able to run my business from my smartphone. But today, it’s a reality. We often overestimate what can be done in a year, and underestimate what can be done in a decade or even a century. For comparison, the first digital calculator, first demonstrated in 1944, weighed nearly 5 tons, was 51 feet long, 8 feet high and consisted of 765,000 parts and more than 500 miles of wire.
One result of the increasing power and reach of digital technology is the creation of massive amounts of data. In fact, some researchers estimate that 90% of the data in the world has been created in just the past two years.
In addition to billions of people sharing images, videos, texts, “likes” and tweets, billions of devices with embedded sensors are sending trillions of real-time signals – such as GPS coordinates, environmental data, clickstreams and health monitoring – daily to the cloud. A modern aircraft sends as much as half a terabyte of data per flight from sensors monitoring jet engines, flaps, flight controls and other parts.
The opportunities in the data deluge
This data deluge is creating a new opportunity to harness information in extraordinary ways. It’s the beginning of a data science revolution that is going to change the world in profound ways. Buried in the torrent of data are key insights that can be gleaned by applying machine learning and other data science techniques. This revolution is about moving beyond just automating business processes to the next generation of data-driven, predictive computing.
Sensors embedded in roads can alert drivers, or self-driving cars, to dangerous road conditions on routes they have entered into their navigation systems. Fitness bands and other wearables tracking health data can alert users and their healthcare providers to potential problems, and data aggregated from millions of anonymized users of those devices could be used to discover insights that could eventually save lives.
Machine learning algorithms can look through massive amounts of data with little or no human intervention and capture the knowledge that can lead to more accurate predictions. For example, a radiologist doesn’t have the capability or time to ingest and interpret millions of image scans to derive subtle patterns to quickly identify various types of cancer at a glance. By using data science to analyse millions of images, every radiologist could have access to the most comprehensive and accurate diagnostic aid, from anywhere in the world.
From fighting Ebola to fraud
Data science can also lead to more accurate projections of the spread of infectious diseases, such as Ebola, or predict whether financial transactions should be blocked because they are likely to be fraudulent. With data aggregated from a variety of sources, businesses could predict which products are most likely to create abnormal service issues, allowing them to proactively work with suppliers and customers to mitigate the problems.
The stage is set for intelligence rendered by data science to become part of the internet fabric. Every app that collects and provides data will deliver some kind of intelligence from the cloud. And, with data storage costs declining, processing speeds increasing and improvements in machine learning algorithms, data science is poised to make major leaps forward.
But for every potential breakthrough that data science and the unrelenting flow of data bring, there are security and privacy issues that must be addressed. Ultimately, this global digital technology revolution must be part of a trust revolution. People want transparency, the right to know how their information is used and what data they can withhold. With increasing concern about security breaches, such as incursions last year at Home Depot, Target, J.P. Morgan and Sony, we also need to double down on efforts to protect user information. Unless we can do this, there can be no trust.
We all have a responsibility to harness the power of technology in a way that engenders trust. Without that commitment, the promise of the cloud, social, mobile and data science to transform our lives and businesses will never be fully realized.
Author: Marc Benioff is Chairman and Chief Executive Officer of Salesforce
Image: A broker monitors share prices while trading at a brokerage firm in Mumbai August 22, 2013. REUTERS/Danish Siddiqui
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The views expressed in this article are those of the author alone and not the World Economic Forum.
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