This article provides a retrospective on the 20th anniversary of Jeffrey Dean and Sanjay Ghemawat’s seminal paper, “MapReduce: Simplified Data Processing on Large Clusters”. It explores the paper’s lasting impact on data processing, its influence on the development of big data technologies like Hadoop, and its broader implications for industries ranging from digital advertising to healthcare. The article also looks ahead to future trends in data processing, including stream processing and AI, emphasising how MapReduce’s principles will continue to shape the future of distributed computing.
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Revisiting the Home Office’s Big Data Initiative: A Success Story in Modernising Border Security
This article revisits the Home Office’s 2013 initiative to modernise border security using Big Data and Machine Learning. It highlights significant cost reductions, enhanced functionality through advanced data integration, and the strategic shift to open-source technologies, which improved security and flexibility. The piece also reflects on the challenges of avoiding vendor lock-in while strengthening UK border operations.
Continue readingRevisiting the Cloud Computing Panel at Julie Meyer’s Entrepreneur Country: Reflections 15 Years On
This article revisits a 2009 cloud computing panel discussion at the ‘Entrepreneur Country’ event, hosted by Julie Meyer, examining how the ideas and predictions shared during the event have influenced the evolution of cloud computing over the past 15 years. It reflects on the entrepreneurial context of the time, the adoption and maturity of cloud services, legal and regulatory challenges, and the future vision for cloud technology, offering insights into the lessons learned and their relevance today.
Continue readingRevisiting the Cloud Computing Model: A 15-Year Reflection
This new article revisits a conceptual framework of cloud computing I introduced in 2009, exploring how cloud roles, billing models, and security have evolved over the past 15 years. It discusses the maturity of cloud services, the expansion of “as-a-service” models, and the rise of country-specific cloud solutions. The piece also highlights potential disadvantages such as hidden costs, vendor lock-in, and the recent trend of companies moving away from cloud providers. The article concludes with predictions of cloud computing.
Continue readingTransforming Border Security: The Home Office’s Big Data and Machine Learning Strategy
In September 2015, I had the opportunity to represent the Home Office and Border Force in a panel discussion at an event covered by Diginomica, where we delved into the transformative potential of Big Data and Machine Learning technologies. Alongside industry leaders from Jaguar Land Rover and Zurich Insurance, I discussed how the Home Office is actively leveraging Hadoop and other open-source tools to modernise its data management and decision-making processes, particularly within border security operations.
Continue readingExploring Real-World Applications of Hadoop and Big Data, with HortonWorks, Jaguar Land Rover, Zurich Insurance, and The Home Office
In a recent event, celebrating the opening of HortonWorks’ new London offices, three prominent organizations, Jaguar Land Rover, Zurich Insurance, and the UK’s Home Office, were invited to highlight their pragmatic use of Hadoop and big data technologies to extract value from unstructured data. I was pleased to be asked to represent the Home Office.
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