September 21, 2020 Continent 8 Team

Starting a Data Journey by Continent 8’s Anthony Abou-Jaoude

Anthony Abou-Jaoude’s story with Continent 8 continues as he re-joins the Group in a key role as Director of  Product Engineering. Anthony, who was the first software engineer to ever be hired at Continent 8, shares with us his personal data journey. Read more about Anthony’s professional highlights, the current unprecedented volume of data and how companies across the globe can ensure they get value from it.

By Anthony Abou-Jaoude 

I am sure everyone has been hearing the term Big Data more often in the past few years and the discussions addressing the importance of it.  This has never been as true and as relevant than during these pandemic times, where we are constantly being bombarded by statistics and charts that we must make sense of.

In these ever-challenging times, data is enabling decision makers to act fast and make choices based on facts and statistics.  Even more, this pandemic is highlighting the importance of the visualization of data and extracting intelligence from it. At the same time the general public a way of understanding the impact of this virus in a more familiar format, whether it is different forms of graphs and charts, or infographic pictorial maps.

Personal and professional highlights

Personal and professional highlights

First, let me start with a few data points about myself:  I am a returning employee of Continent 8, where I was the first software engineer ever hired. It was a great way to start my professional career right out of university.  In the spirit of data and visualization, I can share some personal and professional highlights with you using a diagram:

I am so glad and privileged to return to such a success story and familiar faces at Continent 8.  From my first week back, I dove into the data and visualized how the company has been experiencing exponential growth across multiple verticals. For example, as nothing depicts it better than a chart, the data flowing within our network shows no sign of slowing down:

Data flow within Continent 8's network

                     Data flow within Continent 8’s network from 2012 – 2020

 

In the same vein, we, as a population in general, are creating unprecedented amounts of data. In fact, every two days we generate as much data as we did from the beginning of time till 2003.  It is estimated that in 2018 we have accumulated 33 zettabytes (ZB) of data, and by 2025 that number will grow by 430% to total 175 ZBs.

This growth of data is challenging companies across the globe to get value out of their data, and to optimize its collection, storage and usage.  The best big data applications are those that unlock value from both structured and unstructured data, and to achieve that, you need a combination of tools, data scientists and leadership. All coming together on a data journey to deal with this massive influx of data.

Just like Maslow’s pyramid, there exists a data science hierarchy of needs where the first and most basic of requirements must be met in order to have a proper and successful data strategy:

The Data Science Hierarchy of Needs Pyramid

                   The Data Science Hierarchy of Needs Pyramid SOURCE: “THE AI HIERARCHY OF NEEDS” MONICA ROGATI.

 

Anthony Abou-Jaoude

Anthony Abou-Jaoude

An organization must start by looking at what data it has, how it’s being used and collected, it’s quality, what is missing and where it can be optimized.  Once this is understood, it can move on to the next step, which is enabling and supporting personnel that need the data to be able to query it themselves by empowering them with the right tools and training.  The ability to slice and dice the data and securely share it with multiple groups in the organization, is the difference between just collecting the data and having it idle versus operationalizing it by extracting value from it and reducing risk.

After setting a proper data foundation, a company can get into the final stages of the journey which really gives the competitive edge.  With proper correlation and data sets in place, we start getting into the forecasting and machine learning cases.  Using a multitude of tools, techniques and algorithms, we can pre-empt future needs, or prevent failures, with a reasonable level of confidence.

The data journey is a never ending one, always affected by factors outside a dataset and in need of continuous improvement, with the human component very much important at every stage.

 

Without realizing it, many of us are already working together on this data journey. Let us know where Continent 8 can help as we are continuing to unlock the power of data for ourselves and our customers.