Data Science / AI
Data Science leverages data and uses the most advanced technologies and algorithms to create knowledge and drive predictions. By developing analytical models, it makes possible to explain, predict and automate decisions.
Data Science is the root for Artificial Intelligence and its uses are exploding. There are many disciplines that are related to Data Science: Artificial Intelligence, which includes Machine Learning and Deep Learning, Statistics, Data Preparation, Data Visualisation (Dataviz).
Integrating AI and Data Science
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Integrating AI and Data Science
Green AI: Responsible artificial intelligence is also frugal
When it comes to Artificial Intelligence, it’s not only about improving performance at any costs. Its benefits along its adoption requires AI to be responsible by also including an environmental side. Taking environmental issues into account is no longer an option. The IPCC’s April 2022 report is clear. It is also, pun unintended, one of…
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Integrating AI and Data Science
AI Industrialization: the key steps to a MLOps approach
The industrialization of artificial intelligence – one of the 7 hot data topics for 2022 requires the implementation of MLOps. This approach includes some necessary steps, including a common platform and a feature store. To learn more about this approach, we offer you a how-to-guide for an iterative, but unavoidable transformation. After years, which were…
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Integrating AI and Data Science
Data Science applied to Vertical Farming: the future of sustainable farming
By 2050, there will be over 6.5 billion people living in urban spaces according to a United Nations report, making it a real future challenge to feed them all. Vertical farming is becoming a critical component of agriculture’s future. This concept aims to optimize plant growth and soilless farming techniques using as little space and…
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Integrating AI and Data Science
Data Ethics/AI Ethics: the 2 faces of a responsible future
Artificial Intelligence is at the heart of all attentions and concerns right now. Did you know that the real difficulty with Artificial Intelligence is not the algorithms, nor the design of the models but it is above all the Data! And yet, Data is increasingly distrusted today. How to solve that and produce trusted &…
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Integrating AI and Data Science
Artificial Intelligence: Stay in control of your future!
If there is one topic that really ignites passion and fuels all ideas and discussions in the world of new technologies, it’s Artificial Intelligence. What are the opportunities for enterprises? How to launch AI projects? What are the best practices, benefits, and risks? You will find all the answers in this white paper, available and…
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Integrating AI and Data Science
Statistics versus Machine Learning: should they really be opposed?
This “seemingly” old debate deserves to be revisited with fresh perspective. Data Science (such as Big Data) is a constantly evolving field with nowadays proven applications namely in the fields of customer knowledge and marketing… Statistics and machine learning in the era of Data Science and customer knowledge Even though the field of application is fairly recent, the basic methods used in Data…
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Integrating AI and Data Science
The 5 key Data Science practices
In the wake of Big Data, many companies embarked on the Data Science journey, the field having established itself as the inescapable route towards Big Data transformation into knowledge and actions. Discover in this blog article the 5 key practices to observe in order to ensure project success. 1. Methodology Data Science methodology is essentially agile and iterative. It derives from inductive reasoning, which…
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Integrating AI and Data Science
The key to Data Science success is the CRISP methodology
The CRISP methodology (originally known as CRISP-DM), first developed by IBM in the 60s for data mining projects, remains, today, the only truly efficient process used for Data Science projects… CRISP methodology: User guide The CRISP methodology includes 6 steps that range from business understanding to deployment and implementation. 1. Business understanding The first step involves acquiring a good understanding of the business elements and issues that Data Science aims to improve or solve. 2. Data…
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Integrating AI and Data Science
Data Science and AI: how to properly scope your business projects?
An increasing number of companies are opting for data-driven strategies and embarking on marathon Data Science and Artificial Intelligence projects, in the hope of sharing the benefits of new technologies and data. What is the best way to ensure the success of Data Science or Artificial Intelligence projects? Which players will help effect change and…
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Integrating AI and Data Science
How is the Port of Antwerp optimising logistics with data science?
Looking for fast, intelligent exploitation of its mass of data, the Port of Antwerp turned to Orange Business to optimise and secure the safety and efficiency of its maritime transport. A report.
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Integrating AI and Data Science
CRM and artificial intelligence: how to develop and optimise your data
We are launching a series of three articles setting out our current vision of digital projects connected with customer relations. In this first article we will investigate the current trends for enriching a CRM and how to optimise data quality.
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Integrating AI and Data Science
Artificial intelligence, machine learning, data science: are these terms interchangeable?
Many writers talk about AI, machine learning and data science, as if these terms were broadly interchangeable. What’s going on exactly?
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Integrating AI and Data Science
[EXPERT DISCUSSION] Artificial Intelligence in 7 key points
Artificial Intelligence (AI): these two words are on everyone’s lips at the moment. They carry both hope for unprecedented development and fears revealed by the greatest science-fiction writers.
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Integrating AI and Data Science
VIDEO: Soccer Player Predicted As Top Rising Star – Back In November
Did you know that Big Data can help us predict who the future soccer stars will be? This is precisely what happened in Riyad Mahrez’s case, PFA Player of the Year, who has conquered the English Premier League with Leicester City. During last year’s Big Data Week Conference in London, Malta-based entrepreneur Valery Bollier correctly…
Understanding AI and Data Science
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Data and AI news
Generative AI is not a sprint… but a Marathon
Discover in this webinar how to not only sprint off the starting blocks but also conquer the long-distance race to AI success! Ready, Set, Innovate! Discover how Generative AI is revolutionizing businesses by shifting from quick wins to long-term transformative strategies. Hosted by Pierrick Reglioni (Data & AI Expert), with expert insights from Jérémy El Aissaoui…
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Data and AI news
#Data / #AI: our experts analyze the trends for 2022
In 2022, data and AI are more than ever a key priority for companies. For the sixth consecutive year, Orange Business is presenting the key trends in Data and AI topics for businesses. Discover more in this webinar available in replay (and in English for the first time!) Our experts will comment and give you…
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Data and AI news
Artificial Intelligence to better protect us in times of pandemics
Artificial Intelligence & Machine Learning technology are playing a key role in better understanding pandemics. More specifically, AI can support decision makers in taking the right actions to handle a pandemic. We discussed with Dr. Pieter Libin, Professor at the AI lab of the Vrije Universiteit Brussel, how Artificial Intelligence, and more precisely, Reinforcement Learning,…
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Understanding AI and Data Science
Can a whole Data Science project be done using R or Python?
For several years now, many Data Scientists have found themselves turning to “language” command line tools, such as R and Python, to deal with Big Data. But can you really undertake a whole Data Science project solely armed with these two technologies? The evolution of Data Science tools Looking back on the evolution of what is known today as Data science, (which,…
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Understanding AI and Data Science
Does Auto-Machine Learning (AutoML) really exists?
Automated machine learning (AutoML) has existed since 1990, it was considered as a silent revolution in the Artificial Intelligence (AI) field. When we analyze the term AutoML, we see that it refers to two words, Automated and Machine Learning. Machine Learning with its different types of learning Supervised (Labeled data) Unsupervised (Unlabeled data) Semi-supervised (A…
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Understanding AI and Data Science
Data Science: the 4 obstacles to overcome to ensure a successful project
The last five years we have seen the number of Data Science projects carried out by Orange Business in various sectors, such as the oil industry, telephony, retail and services, rise significantly. However, some difficulties must be overcome in order to efficiently implement these types of projects. Explanation. First of all, let us not forget…
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Understanding AI and Data Science
Data Engineer: which training programs to choose?
To all those young people wishing to embark on a career in Data Science, my advice was to begin with a Data Engineering job rather than directly as a Data Scientist… Today, I would like to walk you through the apprenticeships and training programmes that will help you become a Data Engineer. Data Engineer: which…