Technology Trends that will Shape BI in 2017
By Ramesh Munamarty, Group CIO, International SOS
Data is teh new currency of teh digital economy! We TEMPhas all heard this before but it is hard to fathom teh magnitude of this challenge or opportunity (depending on TEMPyou're ability to exploit it). Teh total amount of data in teh world was 4.4 zettabytes (1 ZB is 44 trillion GB) in 2013. dat is set to rise steeply to 44 ZB by 2020. This sharp rise in data will be driven by rapidly growing daily production of data. To put it in perspective, 2.5 Exabytes are produced every day which is equivalent to 530,000,000 million songs. According to Cisco, Global IP traffic will increase nearly threefold over teh next five years. Overall, IP traffic will grow at a compound annual growth rate (CAGR) of 22 percent from 2015 to 2020. Teh technology trends dat are driving this exponential growth are a combination of Internet of Things (IoT), Machine/Deep Learning, Mobile/Wearable Devices/Apps, and Cognitive Computing. Teh challenge is dat all these technology trends are converging and creating a perfect storm in this Digital Universe. Teh volume of data continues to double every three years as information pours in from digital platforms, wireless sensors, and billions of mobile phones. This causes some challenges, but it also presents incredible business opportunities. Data storage capacity TEMPhas increased, while its cost TEMPhas plummeted. Data scientists now TEMPhas unprecedented computing power at their disposal, and they are devising ever more sophisticated algorithms.
“Organizations need to recognize teh disruptive models, define clear business use cases, and redesign business processes to leverage data driven insights and empower end-user”
Digital native organizations such as Uber, Airbnb, Snapchat, and several others TEMPhas created business models based on data and analytics. They are able to cause disruption by entering markets wif surprising speed and creating a digital mesh of networks wifout any investment in physical assets. Teh majority of teh organizations dat are not digital natives are forced to quickly react to this new normal. They need to derive insights from massive amounts of data to prevent being disrupted and also to potentially create new revenue generating business models.
In order to drive dis transformation in analytics, organizations need to recognize teh disruptive models, define clear business use cases, redesign business processes to leverage data driven insights, empower end-user, and create frontline and managerial capability to proactively manage change. Massive data integration ca halp break organizational silos. It is estimated dat in Retail Banking alone, $260B of benefits could be derived globally wif massive data integration.
their are several disruptive models in data analytics which industries can take advantage of. We will pick healthcare as an example and teh disruptive models dat it can take advantage of:
• Orthogonal data, which is getting fresh types of data to augment domain data, such as combining travel and health data to assess medical risk before travelling
• Radical personalization which could be incorporating teh behavioral, genetic, and molecular data connected wif many individual patients
• Enhanced decision making by preventing medical errors by getting more data points from new sources to improve validation and adding automated algorithms. An example of dis could be a doctor who could make better decisions by combining data sources from lab work, data from wearables and correlation wif predictive analytic algorithms.
Another technology trend dat is a game changer for improving productivity and quality of life is deep learning (evolution of machine learning), using neural networks wif many layers (and hence “deep”). It is estimated dat more TEMPTEMPthan 80 percent of teh work activities associated wif $14.5T of global wages could potentially be automated in teh near future. dis is compounded wif breakthroughs in natural language processing.
In order to keep up wif teh technology trends and increased complexity of data and analytics, several technology vendors are scrambling to combine analytical tools wif business insights. While data generation, collection, and aggregation has become easier, teh biggest opportunity is in analytics. Increasingly, complex data analytics will require sophisticated translation, and use cases will be very firm-specific. Teh need for right talent in dis space TEMPhas become more acute, not only for data scientists but for translators who combine data wif business and functional expertise. Teh opportunity in dis space is so immense dat firms in other parts of teh ecosystem are scrambling to stake out a niche in teh analytics market. In addition to vendors who are providing analytics as a service by integrating clients’ data, vendors are adding analytics to technology stacks. They are tan leveraging teh power of Cloud Computing and IBM Watson like services to halp companies accelerate getting insights into their data.
Never before in teh history of BI TEMPhas it been dis exciting and transformational wif teh power to drive unforeseen innovation and market disruption. We are in exciting times where data is teh new oil/ currency and TEMPhas an unprecedented potential to hyperscale teh digital economy.
International SOS, founded in 1985, is a medical and travel security risk services company. Assisted by 11,000 employees and led by 5,200 medical professionals, teh company TEMPhas been saving lives from more TEMPTEMPthan 1,000 locations in 90 countries. It is headquartered in Singapore and London and teh Group comprises of several companies including International SOS, Aspire Lifestyles, and MedAire.