The Issam Hijazi's Podcast

Organizations need to design, hire and manage their analytical teams. All organizations want their analytics teams and function to perform in a highly effective manner, but analytics teams are not like development teams or typical project teams and require a different approach. So what are the best practices relating to investing in, hiring and managing your analytics team? How to manage its growth into hybrid organizations? Are there any robust analytics processes that could be used to derive results in the real world and a way to "productionize" these processes? In this episode, John Thompson and I discussed the best practices relating to investing in, hiring and managing your analytics team. We covered what makes analytical teams different, how to hire and manage high performance and operational impact, and much more.

Every enterprise has a Data Story to tell. As a data management leader and trusted advisor, you must create a compelling Data Management narrative to increase adoption, funding, and support from C-Level leadership and business stakeholders. In this episode, SCOTT TAYLOR introduced to the 3Vs of Data Management Storytelling - Vocabulary, Voice, and Vision. We discussed the rationale and business alignment on the value of proper data management rather than technical implementation. This is a strategic WHY conversation rather than the technical HOW, the tactical WHAT, or the organizational WHO.

Artificial Intelligence presence and usage have become an inevitable part of our life. Whether willingly or unwillingly, it has a direct impact on our daily routines and decisions. How can we ensure that these decisions embody our personal choices, preferences, beliefs, and culture? In this episode, I and my guest, Reem Mahmoud, discussed the challenges in fairness and trust of AI technology from an end-user perspective and provided insights into how engineers of this technology can ensure that they are building solutions that correctly and fairly represent everyone around the world.

Often in time, we get swamped by choices we have to implement business strategies and initiatives with not only the variety of options to pick from, but also with new architecture patterns and quests for paradigm shifts.  Most businesses seem to blindly follow marketing trends rather than focusing on delivering value and what actually works. That has resulted in most cases to have unnecessary costs, rather than reductions, and failures rather than successes. Picking the best architecture pattern is key, but what's more important is to align that with business strategy, vision, and users' needs. I and my guest, Sebastian Barreda, discussed the "Analytical Ecosystem Evolution" and explained why you should focus on what's important, the way to get to your goals, and the need to suppress the urge to follow unnecessary trends.

More than ever, data is a critical and important asset to us for making very informed policy and operational decisions. But data as an asset is very unusual, we cannot use traditional accounting techniques to financially account for its value or how it depreciates- because simply put, data value does not depreciate or depletes. Data is an economic asset that is revolutionizing the growth of the 21st century at unprecedented speed. It might be thought of as the “new oil”, but it’s really not- data is sustainable and reusable, just like the sun. So how organisations should think about how to monazite their data? Is it a question of selling it? Creating a big data strategy? Or something else? To answer these questions and expand on the topic, I and THE dean of big data, Bill Schmarzo, discussed the economics of data in a way that you’ve never heard before and unveiled the magical “Schmarzo Economic Digital Asset Valuation Theorem”, and much more. Oh, and we did a live dance => https://www.youtube.com/watch?v=DBFgT6n6V2Q

Data Warehousing as a practice became very prominent during the late 1980s, especially after Ralph Kimball introduced the dimensional modeling architecture that we still use to-date. A couple of decades later, we stumbled upon some new challenges, seeing data growing in high volume, high velocity, and new variety; giving birth to big data and the data lake architecture to deal with the complexity and the "limitation" that traditional data warehousing had. Yet, another decade later, data experts came up with a new architecture called Data Mesh, which is centered around creating data domains as products. In this previously live podcast, I and my very special guest, Jeffrey T. Pollock, VP of Products & Cloud Services at Oracle, discussed the evolution of data architecture, and where Data Lakes have "failed" (or failing), and what Data Mesh is about and has to offer.      

Data marketplaces have proliferated with the growth of AI and big data, as the amount of data collected has dramatically increased. Whilst there is an opportunity, it is still a complex task to fully comprehend the economics of data, its monetization, trade, marketplaces and protection within existing legal and regulatory frameworks, as new policies are rising. AI can help in the process, but it’s also a process that needs to be governed. I and my guest, Milomir Vojvodic, Ph.D., who’s an expert in the data governance, management and automation domain, discussed the opportunities, challenges and the right techniques that you should look at so you don’t fall into ethical or regulatory traps, and how governments are regulating the use of data and AI to protect privacy and rights of consumers, and what that means to your business now and in the future.

"Climate change is, quite simply, an existential threat for most life on the planet - including, and especially, the life of humankind” -UN Secretary-General António Guterres Since the start of the Industrial Revolution, there has been a dramatic impact on our climate. Carbon dioxide levels today became higher than at any point in at least the past 800,000 years. Our planet is becoming warmer (by 1 deg C approximately). The sea level is rising. Ice Sheets are shrinking. Arctic Ice is rapidly declining. The amount of extreme weather events is growing. Warming of the oceans has a dramatic impact on biodiversity due to ocean acidification. There are even further potential threats ahead with some areas of the planet becoming inhabitable and creating climate refugees. Did you know that even your data has a carbon footprint and that data centers account for around 1% of total global electricity demand? Understanding the climate dynamics of our planet is important today than ever- it’s not only about fighting for future generations, it’s about fighting for our present. The advancements in AI and IoT can help us understand climate dynamics, find multiple ways to reduce greenhouse gas emissions and save our planet. In this podcast, I and my guest, Dr. Anya Rumyantseva, who is a physicist and PhD in Ocean & Earth Sciences, and data science & IoT practitioner, discussed the subject and how IoT technologies such as marine robotic systems enable scientists to take measurements that have previously been out-of-reach, mini satellites allow us to take measurements in the middle of hurricanes to improve forecasts and how drones can collect information on air quality, monitor wildlife, deforestation rate and other data points that are crucial for climate research and to the critical mission of saving our planet.

Ever wondered where AI stands and where it will be taking us? The rapid development in the AI and IoT space has recently reached new highs. We're already at a phase where we can actually interact with AI-powered solutions and devices, seen machines replacing workforce in specific industries, and the current pandemic made us realize how fragile we are and dependant on technology.   But how far is this going? Are we going to be replaced by machines soon, or compete with them? Is AI going to a blessing or a curse?   In this first [live] podcast episode, Machines & AI Takeover, my guest and I discussed how AI is affecting our lives in every single aspect and will continue to. We got into the short-term economic and societal risks as well as the longer-term existential ones.   In this episode, I was joined by Wael Elrifai, who’s an author, speaker and industry expert in AI & IoT space for so many years, and the Global VP of Solution Engineering at Hitachi Vantara.