Vicky is the Head of Analytics at Merkle|Aquila. She has over 20 years experience in delivering analytics and actionable insights to large organisations. She is passionate about incorporating latest analytical developments into practical analytical solutions for our clients. As both a statistician and management accountant she bring a strong value focus to analysis – both customer value and marketing optimisation
Vicky’s aim is to take the complexity out of analytics. She is a firm believer that analytics should be delivered in the right language - not shrouded in complex jargon and latest buzz words.
Marta is a Senior Data Scientist at Merkle|Aquila. She has graduated with a MSc in Statistics and Operations Research and has since gained expertise in using statistical and ML techniques including image analysis (real time), predictive modelling, segmentation, neural networks and random forests in order to improve customer acquisition and retention. Marta devotes a lot of her time developing and mentoring junior data scientists within the organisation and has recently developed Merkle|Aquila’s Graduate Programme.
Presentation 2 - Dr Jasmina Lazić - Chief Data Technologist at Bayes Centre, University of Edinburgh - Strengths and weaknesses of different programming languages
With the ever-growing amounts of data we need to deal with, we are experiencing a growing demand for intelligent insights and data-driven strategies. We are also seeing more companies wanting to establish or further advance their data and data science functions.
But what is the right skillset for your data science team? If you need to get into hands-on coding, what languages should you learn? Or, if you are already and experienced programmer, do you need to add any more tools to your portfolio of skills? And even if you already have quite a few tricks (languages) up your sleeve, how do you decide what the best language is for the job at hand?
In this talk we will provide an overview of the top programming languages for Data Science, with their advantages and limitations.
Dr Jasmina Lazić leads, facilitates and enables the commercial adoption of state-of-the-art data science and technology developed at the University of Edinburgh, fostering new collaborative partnerships and technical engagements between the University and industry. Before joining the University of Edinburgh, Jasmina held a number of consultancy and advisory roles in the technology sector, designing, implementing and delivering technical solutions for commercial clients including blue-chip companies. She is also an advocate for high-quality mathematics education and women in technology.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Marta Portugal & Vicky Byrom - Merkle|Aquila
7.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Dr Jasmina Lazić - Chief Data Technologist at Bayes Centre, University of Edinburgh
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Vicky is the Head of Analytics at Merkle|Aquila. She has over 20 years experience in delivering analytics and actionable insights to large organisations. She is passionate about incorporating latest analytical developments into practical analytical solutions for our clients. As both a statistician and management accountant she bring a strong value focus to analysis – both customer value and marketing optimisation
Vicky’s aim is to take the complexity out of analytics. She is a firm believer that analytics should be delivered in the right language - not shrouded in complex jargon and latest buzz words.
Marta is a Senior Data Scientist at Merkle|Aquila. She has graduated with a MSc in Statistics and Operations Research and has since gained expertise in using statistical and ML techniques including image analysis (real time), predictive modelling, segmentation, neural networks and random forests in order to improve customer acquisition and retention. Marta devotes a lot of her time developing and mentoring junior data scientists within the organisation and has recently developed Merkle|Aquila’s Graduate Programme.
Presentation 2 - Dr Jasmina Lazić - Chief Data Technologist at Bayes Centre, University of Edinburgh - Strengths and weaknesses of different programming languages
With the ever-growing amounts of data we need to deal with, we are experiencing a growing demand for intelligent insights and data-driven strategies. We are also seeing more companies wanting to establish or further advance their data and data science functions.
But what is the right skillset for your data science team? If you need to get into hands-on coding, what languages should you learn? Or, if you are already and experienced programmer, do you need to add any more tools to your portfolio of skills? And even if you already have quite a few tricks (languages) up your sleeve, how do you decide what the best language is for the job at hand?
In this talk we will provide an overview of the top programming languages for Data Science, with their advantages and limitations.
Dr Jasmina Lazić leads, facilitates and enables the commercial adoption of state-of-the-art data science and technology developed at the University of Edinburgh, fostering new collaborative partnerships and technical engagements between the University and industry. Before joining the University of Edinburgh, Jasmina held a number of consultancy and advisory roles in the technology sector, designing, implementing and delivering technical solutions for commercial clients including blue-chip companies. She is also an advocate for high-quality mathematics education and women in technology.
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Marta Portugal & Vicky Byrom - Merkle|Aquila
7.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Dr Jasmina Lazić - Chief Data Technologist at Bayes Centre, University of Edinburgh
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
Vicky is the Head of Analytics at Merkle|Aquila. She has over 20 years experience in delivering analytics and actionable insights to large organisations. She is passionate about incorporating latest analytical developments into practical analytical solutions for our clients. As both a statistician and management accountant she bring a strong value focus to analysis – both customer value and marketing optimisation
Vicky’s aim is to take the complexity out of analytics. She is a firm believer that analytics should be delivered in the right language - not shrouded in complex jargon and latest buzz words.
Marta is a Senior Data Scientist at Merkle|Aquila. She has graduated with a MSc in Statistics and Operations Research and has since gained expertise in using statistical and ML techniques including image analysis (real time), predictive modelling, segmentation, neural networks and random forests in order to improve customer acquisition and retention. Marta devotes a lot of her time developing and mentoring junior data scientists within the organisation and has recently developed Merkle|Aquila’s Graduate Programme.
Ted Dunning - Chief Application Architect at MapR - https://www.linkedin.com/in/teddunning
Kubernetes and Big Data
The folk wisdom has always been that when running stateful applications inside containers, the only viable choice is to externalize the state so that the containers themselves are stateless or nearly so. Keeping large amounts of state inside containers is possible, but it’s considered a problem because stateful containers generally can’t preserve that state across restarts.
In practice, this complicates the management of large-scale Kubernetes-based infrastructure because these high-performance storage systems require separate management. In terms of overall system management, it would be ideal if we could run a software-defined storage system directly in containers managed by Kubernetes, but that has been hampered by lack of direct device access and difficult questions about what happens to the state on container restarts.
Ted Dunning describes recent developments that make it possible for Kubernetes to manage both compute and storage tiers in the same cluster. Container restarts can be handled gracefully without loss of data or a requirement to rebuild storage structures and access to storage from compute containers is extremely fast. In some environments, it’s even possible to implement elastic storage frameworks that can fold data onto just a few containers during quiescent periods or explode it in just a few seconds across a large number of machines when higher speed access is required.
The benefits of systems like this extend beyond management simplicity, because applications can be more Agile precisely because the storage layer is more stable and can be uniformly accessed from any container host. Even better, it makes it a snap to configure and deploy a full-scale compute and storage infrastructure
Agenda:
6:30 PM – 7:00 PM: Networking
7:00 PM – 7:30 PM: Marta Portugal & Vicky Byrom - Merkle|Aquila
7.30 PM – 7.45 PM: Q & A Session
7:45 PM – 8:15 PM: Ted Dunning - Chief Application Architect at MapR
8:15 PM – 8:30 PM: Q & A Session
8.30 PM - 9.00 PM: Networking and Drink
