How much data do we actually deal with?
Any business knows its data is a valuable economic asset. Today’s data driven culture has evolved tremendously since the first documented usage of data about 4,000 years ago when data was stored on a clay disc. Just within the social media sphere alone, in one month 30 billion pieces of content are shared on Facebook and 4 billion hours of videos are watched on YouTube. 400 million tweets are sent every day. Our world is increasingly connected, but how do companies deal with the growing volume of data and leverage it for maximum profitability?
It’s estimated that 2.5 quintillion bytes (2.5 billion gigabytes) of data are created each day and 40 zettabytes (1e+12 gigabytes) of data will be created by 2020, 300 times more than 10 years ago!
So the big question is how can organisations benefit most from this data? How do we reveal new insights about our business environment and forecast trends to gain business success and a competitive edge? Every business knows it needs to anticipate market movements and customers’ preferences to increase its chances to succeed.
Do we know what to do with our data?
According to McKinsey Quarterly Report (2017), utilising the full power of data can increase operating margins by 60%, however less than 0.5% of all data is ever analysed and used! Furthermore, the Deloitte’s Human Capital Trends Report done in 2017 found that 88% of organisations believe that building the organisation of the future is very important but only 11% of them understand how! This gap is due to several factors such as data anxiety, disbelieving one has the necessary skills to analyse data and the lack of time and skilled data scientists dedicated to data analytics. It is evident that there is a need to interact with business data in a better way, understand it and be able to utilise it by non-technical workers to achieve insights that enhance business value.
With a continuous evolution of techniques and methodologies in data analytics processes we may just be at the tipping point of a new way to interact with our data.
Extending Business Intelligence
One of the biggest challenges in data analytics is the need to extend it from describing the past and present to forecasting the future. By implementing Predictive Analytics, the data analytics processes can be extended to anticipate events and obtain a business advantage by focusing on the future and what will happen. Predictive analytics combines advanced statistical analysis, machine learning techniques and behavioral science to help companies predict how their markets, customers, prospects and competitors will act and behave.
Predictive Analytics is changing the way we utilise data
In the fast pace of technology and the need to deliver a competitive edge, organisations know today that they need to better analyse data patterns and have a platform to generate actionable insights in a flash .
Most of the current data analytics practices are time consuming, costly and can be implemented and operated only by experienced and dedicated data scientists. Moreover, running predictive analytics in a Big Data environment is even more of a challenge due to the lack of automated , simple to use tools.
Breaking these traditional , time consuming practices, Endor, a pioneer in the Predictive Analytics arena, is leading the new way organisations leverage their data, especially their Big Data. Endor solves a big void for businesses looking to make the best use of their data, fast. Endor’s platform stands out on multiple dimensions — One is the ability to run predictive analytics on Big Data with unprecedented speed and accuracy, the second is the ability to do this seamlessly by a business user, without requiring the skills of a Data Scientist. Last , and maybe one of its key breakthrough features, is Endor’s ability to analyse Encrypted Data, thereby guaranteeing the security of sensitive data.
Predictive analytics in the Era of major Data Privacy & Security breaches
Recent years have surfaced what seems like an endless stream of privacy scandals such as Facebook, Equifax, and Yahoo to name a few. Corporate security needs to advance quickly as hackers from around the world are getting bolder and more sophisticated
Encrypted data is a standard practice in every business today as a minimum effort to combat data breaches, especially with recent privacy regulations, such as GDPR and industry specific regulations (financial, insurance, etc).
Imagine if you could analyse encrypted data without ever decrypting it. Running a prediction model on encrypted data is like asking a blind man to draw a map. Endor’s predictive analytics engine has the unique capability of doing just that.
It is that easy and quick
The Endor platform is fully automated, replacing the manual, time consuming and tedious work flow procedures that data scientists perform today. Using the tool involves only three simple steps:
Imagine that in a click of a button, a bank can accurately and quickly predict out of all customers that missed a credit payment who is likely to repay it within the next 3 days? 7 days? 15 days? Or if a retailer can predict which Loyalty-Club members are likely to buy a specific product in the next two months? Or which stores are likely to increase sales of a product brand by more than 25% in the next 3 months?
It is clear that the economic ramifications of using Predictive Analytics are huge!
The only thing left for the organisation to do is to ask the right business questions and generate the most insightful and actionable predictions for their business.
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