The landscape of data is ever- changing. This is a result of innovation following an exponential graph in regards to data infrastructure and the process in which organizations are redefining their data strategies. There is an explosion of data around us, and it is transforming our world and touching our daily lives like never before. Thus, it comes as no surprise that data science was coined the “sexiest job of the 21st century”.
“In god we trust; all others bring data” — William Edwards Deming. This quote strongly resonates with the current data strategies.
Before continuing, let’s have a quick look at some of the key players in the data landscape
Not so quick, was it? Let’s summarize how we got here:
Mobiles upgraded from 3g to 4g- Networks where mobile phone usage increased from 32 minutes in 2011, to 132 minutes in 2019.
The social media boom: With the shift of social media to smart phones, it became an instaneous broadcast of life experiences. Social media became a one stop shop for information, communication, sales and marketing. Not just individuals anymore but companies, news organization and governments leverage social media to communicate faster in real time.
A few key players emerged who started analyzing data generated not only by operational systems but also the data generated by users. They labelled themselves ‘data-driven organizations” and started to build “data-product” that harnessed the power of behavioral data to dictate their company strategy.
With cost of hard-drives nose-diving, companies and governments were able to store astounding amount data which could then be analyzed for a wide range of purposes by achieving Big Data driven insights.
Eric Schmidt, executive chairman of Google tells a conference that the amount of data generated every two days today roughly equals what was generated from beginning of human civilization till the year 2003
Unstructures storage of data in repositories were being redefined. The CTO of Pentaho coined the term “Data Lake”. A data lake is a large centralized repository where where there is no hierachy or organization in the individual pieces of data. This redefin2ed the way we saw the problem of having pre-categorise data at the entry point.
In 2011, Apache released Hadoop version 1 which beat supercomputers and Google’s MapReduce implementation. Hadoop and datalakes together were able to supercharge your data for better buisiness operation.
2015 was milestone year of the field of AI, along with deep learning and machine learning techniques made what was once was though as fiction a reality. In 2015, Jack Clarke of Bloomberg wrote that Google has scaled up its AI driven software projects from “sporadic usage” to more than 2700 projects.
Cloud computing transformed an organizatiosn apprroach to Information Technology. Everyone started opting for a cloud-first approach. It made collecting, storing, moving data easier, faster and secure. The rise of cloud computing also supported innovation in other fields such as Internet Of Thing (IoT). Ideas like smart cities would never have been possible without cloud based services for monitoring and collecting data in real-time.
The previous decade is righfully justified as the decade of disruption, especially in the field of data. With increasing advancements in technology such as cloud computing, artificial intelligence and big data analytics, a lots of things once though to be fictional is becoming a reality.
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