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We hope you enjoyed EARL London as much as we did! We’re just putting the finishing touches on our highlights recap, but until then you can view the presentations we have available here, and all the photos here.

We’re so proud of the incredible speakers at this year’s EARL Conference – from tackling human trafficking, to benefitting the NHS, it’s always incredible to hear about the many different ways data science can be used for good.

Let’s take a look at some of the feedback and comments we received on this year’s London EARL:

From social:

Great to have been on the same speaking bill as experts from @BMW @sainsburys the BBC and others talking about #opensource, #R and #bigdata. World class speakers on cutting edge topics to an international audience. Thanks @earlconf– see you next year!

Had a brilliant day today at my 3rd @earlconf Have come away with a million ideas, in particular on workflows and productionising R code, and it was brilliant to both see @juliasilge speak and then have her sit in on my presentation! Thanks @MangoTheCatfor a great #earlconf

Dang, #earlconf is over again? I really need to bribe my boss to send me there one year…

Harold Selman also wrote a great round up of the conference on his Linkedin page.

From delegate feedback:

94% of delegates who replied to the feedback said they got what they wanted from EARL London, we were also left some lovely comments:

My whole data science team attended the conference and gained from both a wider learning experience and team building. The team got to discuss potential new projects out of the office environment, which really enhanced our brainstorming! This will add huge value to our future business benefit.

Fantastic conference. EARL never lets me down in providing an insightful, applicable and fun experience to learn from other companies on how they apply R in their enterprises.

EARL is a must for any organisation that wants to understand how R and technologies around R can enable them to achieve better results.

As an R user I’ve been lucky enough to attend EARL now for the last three years. Each time I come away with a fizz of ideas and energised for my year ahead

And not forgetting our mention in the Telegraph! 

A thank you

To all of our speakers, sponsors, delegates and the whole Mango team for another fantastic EARL. We will get started on EARL 2020 in early January – so keep an eye out for the call for abstracts then! If you have any comments or ideas either tweet us or drop us an email.

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The Enterprise Applications of the R Language Conference (EARL) is the place to be for anyone using R in their organisation. You’ll be joined by R users from all over the data world, presenting their real-world projects and use cases, and ideas and solutions.

The conference is run by Mango Solutions, as part of our commitment to the data community.

EARL 2019’s speaker lineup is something special indeed, with Sainsbury’s Group Chief Data Officer, Helen Hunter delivering the opening keynote and taking us through Sainsbury’s ongoing data analytics journey into an increasingly digitally-led retail future.

Joining Helen in the opening session is none other than Stack Overflow’s Data Scientist Julia Silge. You probably already know Julia from her huge Twitter following, from GitHub, or – obviously – from her prolific posting on Stack Overflow itself.

At EARL 2019, Julia will be keynoting around the Stack Overflow Developer Survey – the world’s biggest and most comprehensive survey of people who code. With 90,000 respondents in 2019, Julia’s had a lot of data to comb through, and she’ll be taking us through how and why she used R to analyse that survey.

Julia says: “We are working with a complex dataset on a tight schedule and the R ecosystem provides the fluent data analysis tools we need to deliver compelling results on time”

Also speaking is Hasnain Mahmood, Senior Quantitative Associate at clearing house LCH, where he’s working in the Change and Innovation stream in the In-Business Risk Management team.

In his session, you can learn how Hasnain and his team have been using an R-focused technology stack, to carry out quantitative research to identify unique factors driving counterparty trading behaviour.

Hasnain says: “Put simply, we make financial markets safer”

It’s no secret that Heathrow Airport is in a state of huge development, with an intention to increase passenger movement through it from 80 million to 150 million as a result of the planned third runway.

Mitchell Stirling is the Capacity and Modelling Manager handling a critical element of this uptick in passengers – their baggage. Mitchell will be explaining how, working with Mango Solutions, he and his team converted legacy PERL script into an R package to cut down manual intervention, flag errors earlier, and generally stabilise the process – hopefully meaning less suitcases will show up in Seattle when you’re in New York.

Mitchell says: “For the past 20 years, growth at the airport has been constrained by its existing assets – but there is much to do to use them to their maximum potential”

Does using R “spark joy”? RStudio’s Kelly O’ Briant thinks it does, and as a Solutions Engineer, she’s passionate about bridging the gaps between development and production in data science projects. Covering how CI/CD tools can enhance reproducibility for R and data science, she’ll be showcasing practical examples in testing and deployment.

Kelly says: “Once you’ve embraced some basic development best practices in data science, what comes next? What does it take to feel confident that our data products will make it to production?”

Data journalism is now very much ‘a thing’, and that’s why we’ll be hearing from the BBC’s Nassos Stylianou.

The Senior Data Journalist will take us through how R is now being used to extract, wrangle and analyse data for major BBC stories, including the use of ggplot2 to create production-ready charts for a global audience, as well as informing the wider BBC of its value.

Nassos says: “The transition to R let us spread its use to other members of the Data and Visual Journalism team who had no prior knowledge of R”

Join us at EARL 2019 to see these speakers and more, as well as our hugely popular workshops covering a range of topics from package development in R to producing explainable, non-black box, machine learning models.
EARL Conference runs 10-12 September 2019 at the Tower Hotel, London, E1W 1LD.

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We sent Johannes Tang Kristensen from Arla Foods a few questions about his upcoming talk at EARL London – ‘How much milk do our cows produce? Lessons learned from putting our first R model into production’.

How did the need for your project come about?

The project started out as part of a larger initiative in Arla with the goal of proving the need for and value of advanced analytics. In this particular case, our global planning team asked us whether we could have a look at their current forecasting approach and see if we could improve it. An interesting aspect of the challenge was that the performance of their current approach was very high so they did not necessarily expect us to come up with a model that could beat their forecasts, although they of course wouldn’t mind it if we did. Instead what they wanted was a model that could help them develop a more systematic approach towards creating their forecasts where it would be clearer what the underlying assumptions of the forecast were, where they would be less dependent on the knowledge of individuals in their team, and where they wouldn’t have to spend days creating a forecast in Excel.

Where did you start with your project?

The project started by conducting a proof-of-concept where we were given a data set compiled by our global planning department containing the variables they believed could be relevant. Using the data set we were able to build a model that in the end outperformed their current forecasting approach. In order to present the results in an interactive way we supplemented the model with a Shiny dashboard where our stakeholders could visualise the forecasting performance of the model in different cases and at different points in time. Based on this the project was approved and upgraded from proof-of-concept to an actual IT development project which meant we had to figure out how we actually put such a model into production.

How did you communicate the value of your work to the rest of the business?

The communication was mostly driven by our business stakeholders as they were the ones that best understood the actual value of the forecast improvements and time-savings provided by the model. However, we have of course also used it to showcase what we can deliver whenever possible.

Thank you to Johannes for answering our questions. Please take a look at the other brilliant speakers we have at EARL, we are now counting down the days! There is still time to get a ticket to EARL – our workshop spaces are filling up quickly, so don’t miss out. 

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Robert Duff (Transport for London) and Rahulan Chandrasekaran (Department for Transport)

Robert and Rahulan are doing a joint presentation titled ‘Let me in! Let me on! Quantifying highly frustrating events on the Underground’ on 11 September at EARL London. We dropped Robert an email to find out more around the subject of his and Rahulan’s talk.

How do you think technology is shaping modern transport?

Incredibly. It definitely feels like we are in something of a reboot stage at the moment. The challenge is staying relevant and positioning yourself to be flexible enough to adapt. The next advancement could be just around the corner. From the noticeable increase in ride-hailing services, electric vehicles and autonomous vehicles trials, it’s clear that technology is already shaping transport offerings as well as defining how users interact with them. The quality and quantity of information available to both public transport users and road users in recent years has really advanced. And of course, whilst we go on this journey it’s paramount to have safety at the forefront of our mind and to always be on the lookout for opportunities to encourage trips on more sustainable modes.

What challenges do organisations face in helping to shape modern transport?

Although it’s been mentioned a few times recently in various blogs that I’ve read, I’m just going to re-iterate here one of the key challenges. Organisations can do their best to keep up to date with technological trends and have vast amounts of data and the right mix of Data Scientist/Engineers, but the ability to shape really starts with making in-roads towards an organisational culture where data and openness is at the core.

To unlock the benefits of technological advancements you need to have the ability to influence and have decision-makers who are confident when talking about data.

It would be great for example, if everyone knows what machine learning is but we know this won’t happen overnight and part of the challenge is explaining such topics so that everyone has a chance of grasping what they mean. It also helps when everyone is upfront and honest, happily stating when they don’t quite understand – there’s absolutely no shame in asking someone to repeat themselves but in a slightly different way 😊. Organisations with strong analytical communities that fall naturally into the habit of sharing knowledge, learning from each other and unearthing best practices, are the ones in prime position to face this difficult challenge.

Why did you pick R for this project?

Wrangling and Visualising make up a big part of this work so R was a very good fit in that respect. Particularly important for Rahulan (my co-presenter) and I, was the ability to put the data into our stakeholders hands to interact with – and we found some fantastic packages for that.

What are you planning after this project?

The direction of travel for this project is pretty exciting. Since the project has got going, and from what we’re going to present at EARL, we’re now in a position where we have more data than before and in considerable quantities. We can now complement our ticketing and train movement data with WiFi data from within our stations. This gives us an extra dimension as we can begin to think about applying more advanced techniques to our problem, possibly taking a trip into predictive analytics territory with the aim of improving the customer experience.

Thanks to Robert for this interview – please take a look at the other speakers that we have presenting. It’s going to be 3 days of jam-packed R goodness!

There are only 4 weeks left until EARL, you can get your tickets here.

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There are so many wonderful EARL talks happening this year – it’s hard to highlight them all! But we thought we’d share some that the Mango team are really looking forward to:

Ana Henriques, PartnerRe

Using R in Production at PartnerRe

Ana Henriques is the Analytics Tool Lead in PartnerRe’s Life & Health Department. Ana is now focused on business-side delivery of platforms and tools to support data science and related functions. Her talk will focus on the open source infrastructure supporting this process: version control, continuous integration, containerisation and container deployment and orchestration.

Kevin Kuo, RStudio

Towards open collaboration in insurance analytics

Kevin is a software engineer at RStudio and is the founder of Kasa AI, a community organization for open research in insurance analytics. Kevin will be introducing Kasa AI, a not-for-profit community initiative for open research and software development for insurance analytics. Inspired by rOpenSci and Bioconductor, his team hopes to bring together the insurance community to solve the most impactful problems.

Charlotte Wise, Essense

Beyond the average: a bayesian approach for setting media targets

Charlotte manages a small team of analysts at Essence, a global media agency and part of GroupM,
WPP. Her talk will cover how the team at Essense overcame the issue of reporting ROI on marketing campaigns by using a hierarchical bayesian model.

Kasia Kulma, Mango Solutions

Integrating empathy in the Data Science process

Kasia Kulma is a Data Scientist at Mango Solutions and holds a PhD in evolutionary biology from Uppsala University. Kasia’s talk will demonstrate how empathy has a clearly defined role at every step of the Data Science process: from pitching project ideas and gathering requirements, to implementing solutions, informing and influencing stakeholders, and gauging the impact of the product.

Mitchell Stirling, Heathrow Airport

Understanding Airport Baggage Demand through R modelling 

Mitchell is a Senior Analyst at Heathrow Airport with seven years experience working in Operations, Commercial and Strategic positions. Heathrow Airport is entering a new phase of growth and the team there wanted to look at potential scenarios for occupancy and use of infrastructure to maximise existing assets and reduce the need for expensive capital works, early in the programme. To explore how these scenarios would impact the demand on baggage systems, Heathrow has worked with Mango to convert a legacy PERL script into an R package and make a number of improvements that cut down manual intervention, flag errors earlier, stabalise the process and allow for greater variation in key inputs.

There are plenty more speakers on the agenda for you to take a look at so why not join us in September for 3 days of R, learning, inspiration and fun!

Tickets available now.



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R fans, you have just one more day to get your hands on discounted EARL London 2019 tickets. Our early bird offer gets you £100 off the full price ticket, so it makes persuading your boss easier!

Visit the EARL website for more details and see 2018’s highlights below:

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We are delighted to announce that Helen Hunter, Chief Data Officer at Sainsbury’s will deliver the opening keynote address at this year’s London EARL conference.

As Chief Data Officer at Sainsbury’s plc, Helen’s remit is to maximise the value of the Group’s data asset: democratising access and finding creative ways to unlock its insight potential in support of Sainsbury’s strategy to ‘know our customers better than anyone else’

Over the last 8 years at Sainsbury’s in roles including Director of Innovation, and Director of Data and Relationship Marketing, Helen has brought to bear her experience of navigating large organisations to develop products and propositions at the intersection of data, digital, technology, performance marketing and loyalty. These have included Sainsbury’s Band Match and Sainsbury’s new Nectar.

Helen thrives on solving problems and delivering innovation by building both products and people. She relishes a blank sheet of paper against a clear strategic outcome and happily rolls her sleeves up to do the unglamorous housework of implementation. And supports people to be their best and realise their ambitions.

Before joining Sainsbury’s, Helen held roles at emnos, Home Retail Group, Woolworths Group, and Kingfisher, having read modern history at Oxford. She lives in central London with two young children (6 and 2) and is a fan of skiing, sci-fi and European crime drama.

Joining Helen to deliver a keynote address in the conference opening session will be Julia Silge, Data Scientist from Stack Overflow.

In addition to these brilliant keynote speakers, the conference agenda features a whole host of speakers from a variety of industries presenting on how they are using R to solve business challenges.

Please see the EARL website for more information, and don’t forget we have early bird tickets at a discounted price for a limited time!

We hope you will join us in September.

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We’ve been to some incredible evening reception venues over the past few years – The Tower of London, HMS Belfast, The Imperial War Museum and a cruise down the Thames! Every year our attendees tell us how valuable the conference networking opportunities are, and our evening reception is the perfect occasion to chat with other friendly R users over a few drinks and find out how they use R.

This year we are excited to announce we will be visiting Proud Embankment on the evening of Wednesday 11 September.

We will be travelling in style to the venue in vintage double-decker red London buses, upon arrival we will be greeted by the wonderfully stylish and decadent venue, followed by free drinks and canapés. We are pulling out all the stops this year and we will be treating you to some of London’s best cabaret performers.

But what makes our EARL Conference evening receptions is YOU! We are proud to run an event that supports a community as friendly and welcoming as the R community. If you’d like to join us please visit the EARL website for more information, and don’t miss out on our early bird ticket offers.

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Once again, we are delighted to announce a stellar line up of speakers for this year’s EARL Conference; from Retail and Insurance to Media, Manufacturing and Pharmaceutical, the range of industries now using R stats in their workflow continues to grow.

If you are interested to hear why companies such as BBC News, BMW Group, Arla Foods, GSK, Microsoft, Hiscox, Mumsnet and Gym Group have turned to R, then you can get early bird priced tickets for a limited time.

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Julia Silge is joining us as one of our keynote speakers at EARL London 2019. We can’t wait to hear Julia’s full keynote, but until then she kindly answered a few questions. Julia shared with us what we can expect from her address – which will focus on how Stack Overflow uses R and their recent developer survey.

Hi Julia! Tell us about the StackOverflow Developer Survey and your role at Stack Overflow

The Stack Overflow Developer Survey is the largest and most comprehensive survey of people who code around the world each year. This year, we had almost 90,000 respondents who shared their opinions on topics including their favourite technologies, their priorities in looking for a job, and what music they listen to while coding. I am the data scientist who works on this survey, and I am involved throughout the process from initial design to writing copy about results. We have an amazing team who works together on this project, including a project manager, designers, community managers, marketers, and developers.

My role focuses on data analysis. Before the survey was fielded, I worked with one of our UX researchers on question writing, so that our expectations for data analysis were aligned, as well as using data from previous years’ surveys and our site to choose which technologies to include this year. After the survey was fielded, I cleaned and analyzed the data, created data visualizations, and wrote the text for both our developer-facing and business-facing reports.

Why did you use R to analyse the survey?

All of our data science tooling at Stack Overflow is R-centric, but specifically, with our annual survey, we are working with a complex dataset on a tight schedule and the R ecosystem provides the fluent data analysis tools we need to deliver compelling results on time. From munging complicated raw data to creating beautiful visualizations to delivering data deliverables via an API, R is the right tool for the job for us.

Were there results from the survey this year that came as a surprise?

This is such a rich dataset to get to work with, full of interesting things to notice! One result this year that I didn’t expect ahead of time was with our question about whether a respondent eventually wanted to move from technical work into people management. We found that younger, less experienced respondents were more likely to say that they wanted to make the switch! Once I thought about it more carefully, I came to think that those more experienced folks with an interest in managing probably had already shifted careers and were not there to answer that question anymore. Another result that was a surprise to me was just how many different kinds of metal people listen to, more than I even knew existed!

Do you see the gender imbalance improving?

Although our annual survey has a broad capacity for informing useful and actionable conclusions, including about gender, our results don’t represent everyone in the developer community evenly. We know that people from marginalized groups and underrepresented groups in tech participate on Stack Overflow at lower rates than they participate in the software workforce. This means that we undersample such groups in our survey (because of how we invite respondents to the survey, mostly on our site itself). Over the past few years, we have seen incremental improvement in the proportion of responses that are from marginalized or underindexed groups such as minority genders or minority racial/ethnic groups; we are so happy to see this because we want to hear from everyone who codes, everywhere. We believe the biggest driver of this kind of positive change is and will continue to be improving the balance of who participates on Stack Overflow itself, and we are committed to making Stack Overflow a more welcoming and inclusive platform. This kind of work can be difficult and slow, but we are in it for the long haul.

What future trends might you be able to predict from the survey?

One trend we’ve seen over the past several years that I expect to continue is the normalization of salaries for data work. Several years ago, people who worked as data scientists were extreme outliers in salary. Salaries for data scientists have started to move toward the norm for software engineering work, especially if you control for education (for example, comparing a data scientist with a master’s degree to a software engineer with a master’s degree). I don’t see this as entirely bad news, because it is associated with some standardization of data science as a role and increased industry agreement about what a data scientist is, what a data engineer is, how to hire for these roles, and what career paths might look like.

Given Python’s rise again this year, do you see this continuing? How will this affect the use of R?

Python has exhibited a meteoric rise over the past several years and is the fastest-growing major programming language in the world. Python has been climbing in the ranks of our survey over the past several years, edging past first PHP, then C#, then Java this year. It currently sits just below SQL in the ranking. I have a hard time imagining that next year more developers will say they use Python than say they use SQL! You can dig this interview up next year and point out my prediction failure if I am wrong.

In terms of R and R’s future, it’s important to note that R’s use has also been growing dramatically on Stack Overflow, both absolutely and relatively. R is now a top 10 to top 15 programming language (both in questions asked and traffic). Data technologies are in general growing a lot, and there are many factors that go into an individual or an organization deciding to embrace R, or Python, or both.

Thanks Julia! 

You can catch Julia and a whole host of other brilliant speakers at EARL London on 10-12 September at The Tower Hotel London.

We have discounted early bird tickets available for a limited time – please visit the EARL site for more information, we hope to see you there!