EARL Conference
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If you managed to attend our LondonR in-person event in January, you will have noticed that the events team has gone purple as the baton officially passes from Mango Solutions to Ascent in supporting all R community events, from Bristol, Manchester and LondonR to the annual flagship EARL conference.

The Enterprise Applications of the R Language Conference (EARL) is a cross-sector conference focusing on the commercial use of the R programming language, and this year it’s taking place in person on the 6th – 8th September at the Tower Hotel in London.

With Mango founder Rich Pugh at the helm as Ascent’s Chief Data Scientist, we’re super proud to be continuing the legacy and picking up the organisation of industry favourite EARL, an event that has built an enviable reputation since it was introduced in 2014. Attracting presenters from some of the world’s leading brands and an audience of some of the most influential people in R, EARL has developed into a must-attend conference for many, and the source of innovative new solutions to real-world commercial challenges.

 

“EARL The conference for data scientists who use R.”

 

Real commercial R use cases.

As one of the world’s most widely adopted analytic languages, R has gained tremendous traction in data science projects over the years and today remains the programming language of choice for most statisticians. R’s vibrant package ecosystem and strong community and resources gives data scientists the ability to tackle any analytical challenge, from economic risk management to customer behavioural analysis. Across the pandemic, we saw R play a pivotal role on the global stage in informing effective, data-led decisions across an evolving landscape. The EARL conference attracts the same diversity of applications: past talks feature a wide variety of topics from journey planning to preventing human trafficking and technical talks on app development in R-Shiny and DevOps. Here’s some examples from previous years:

  • Using data to help reduce station overcrowding – Transport for London
  • Data to Deployment: Overcoming the challenges of embedding R models in Production – Royal London
  • Using data to flex analytical muscle: How data science, culture and commercial rigour comes together to drive better ROI – The Gym Group
  • Using data to determine how much milk cows produce – Arla Foods
  • Using data to drive better decisions – Hiscox

EARL is renowned for making delegates feel inspired, both by the creative work they see and in conversation with other R users. If some of these use cases have inspired you to tell your story – our call for abstracts is now open and the most appreciate and attentive audience in the industry is waiting for you…!   Submit your abstract here.

 

“EARL has given me things to change TODAY and other things I’ll be thinking about for a long time.”

 

5 reasons to attend EARL 2022.

EARL attracts a huge following and is supported by companies year after year. It offers great opportunities to learn technical skills and gives you the chance to explore solutions to the common issues facing the community. In conversation with your team, here’s some of our top reasons EARL 2022 needs to be on your list of must-attend conferences:

  • Compelling keynotes: We’ll be revealing our headliners in the next few weeks but rest assured they’ll be unmissable…
  • Deep dive workshops delivered by leading R consultants: EARL’s ever-popular Day 1 agenda features a variety of workshops for 2022 designed to enhance your skills in Explainable Machine Learning, Time Series Visualisation, Shiny, Purr and Plumber, backed by a library of resources.
  • Custom agenda: Build your own conference programme from the 60+ sessions on offer, based on relevance to your industry or use case (or just because!)
  • Expand your network: Invaluable networking opportunities throughout the conference. Meet like-minded professionals and enjoy a cocktail with the best in the business.
  • Creative playground: Get inspired by the latest solutions and explore ideas that you can take back to your business.

We came away inspired by some of the sophisticated work and creative ideas we saw and a new perspective on issues facing the community. EARL is a highly recommended event for anyone using R to support their business.

Whether you’re coding, wrangling data, leading a team of R users or making data-driven decisions, EARL 2022 offers insights you can immediately action across your company. We can’t wait to see you there.

Tickets go on sale in May 2022.

 

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Our first speaker at London R is Giles Heywood who works as Chief Data Scientist at Seven Dials Fund Management. As an alternative property specialist, he uses model-driven strategies to support residential property investment – and as a user of R for 20 years, and author of ‘its’ package for irregular time-series (published on CRAN), he naturally turns to R for all analysis.  

Once a proof of concept, his robust and optimised product readily models district, area and regional property trends, cycles and risks. 

How can the right data support property choice?  

There is a growing appetite among investors for real estate alternatives – including student accommodation, senior housing, build-to-rent residential and hotels, which can offer better prospects for income growth. It also offers risk-adjusted returns than the traditional commercial real estate segments.  

The 7-strong team at Seven Dials Fund management takes a structured and systematic approach to direct real estate investment and also indirect investment through funds in this way.   

Whilst commercial real estate lacks comprehensive open data on transactions, residential property benefits from transparent and complete data on crucial variables of transaction price, floor area and income data to model the dynamics of affordability.  

Our approach is a meticulous analysis of the systematic drivers of return and the regular and often predictable patterns generated in long cycles. For a first-time buyer that can choose a property between small and expensive and larger but cheaper, the right data could help the most appropriate choice and its impact on the future property ladder progression.    

Is modelling in a property-related application fairly unique?   

Although Seven Dials primarily advises institutional clients on large portfolios, some of the most exciting opportunities are in delivering quantitative insights to homebuyers and in particular high net worth investors. We see important synergies or at least significant overlaps between institutional and retail.   

For many, buying their property is one of the most significant financial decisions they will make. Imagine if data science could be used to support decision making in line with their mortgage in the future. The housing market has generally gone up since the key ‘Price Paid’ dataset appeared in 1995, however in 2008 we saw falls of 15-20% nationwide, and in some areas prices have only recently regained 2007 highs.  Both the relative returns and risks can be tracked, modelled and managed. Of course institutions have models for property risk and return, and had sophisticated models back in 2007 which to some extent failed in the crash.  Technology has moved on considerably, aided by t-copulas, non-parametric bootstrap and stress-testing. What our team has done is not to copy others, but to start from the ground up with the best repeat sales indices we can construct, factor risk models, and forecasting consistent with those foundations.   

And how are data science models used for residential property investors now?   

There are some prototypical models on the major portals, and one of the most popular is automated valuation models (AVM).  We don’t do that, for all kinds of reasons, but it’s very appealing for individuals to get updated valuations on their homes and maybe on others, including those that are not on the market.     

What will your talk focus on and what might be the key take aways from your talk? 

My specific contribution to modelling at Seven Dials is projecting relative return within sectors of residential real estate to an investment horizon, using factors. The first factor is the overall market direction and is the sort of macroeconomic variable that is quite hard to predict, so for example an unforeseen pandemic did not hold back the market – to the surprise of many. However the relative price performance is more foreseeable since it is essentially driven by microeconomic forces, and in particular by affordability.   

In addition to the models’ straightforward price-forecasting applications for homebuyers the same analytical framework will be familiar to institutional investors and lenders, and can provide strategies for risk-controlled portfolio management.    

I’ll take you on a highly focused and structured trip through a stack of three models and show how they relate both to familiar ideas like the ‘ripple effect’ but also give precise insights into a long cycle driving relative returns both locally and nationally.  Everything is in R, and I’ll link it to some of my package choices for getting both coding and analysis done fast and accurately, or at least I can answer questions about that.  

Using R to Model UK Residential Property by Giles Heywood 

Will you be joining us at LondonR ? Giles Heywood who works as Chief Data Scientist at Seven Dials Fund Management uses model-driven strategies to support residential property investment. In his talk, discuss how both the relative returns and risks in property investment can be tracked, modelled, and managed.  Join us at LondonR  

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After another fantastic EARL Conference held online this September, we are delighted to share that we were able to donate £8,000 to DataKind UK.

The aim of the Enterprise Applications of the R Langauge Conference is to inform, educate and inspire, and we certainly feel inspired by the great work DataKind UK have done this year and plan for the next.

Suzy from the DataKind UK team kindly sent us the statement below to share with the community:

At DataKind UK, we are looking ahead to ensure that we continue to provide what the sector needs to make full use of responsible data science. This year, we have heard the ideas, requests, and feedback of charities, our volunteer community, our staff team, our partners, and others in the sector, and distilled these insights into a new five year strategy. This generous donation from The EARL Conference will support us in our work to engage nonprofit leaders with data, to help our social sector data communities to flourish and grow, and to provide that crucial data support to social sector organisations through our DataDive, DataCorps projects as well as our soon-to-be launched mentoring programme.

Thank you Suzy! We look forward to reading about DataKind’s work over the next year.

We’re excited to tell you that the EARL Conference will be back in-person from the 6-8th September 2022 at the Tower Hotel, London. The call for abstracts will open in January – stay up-to-date and sign up to the mailing list here.

 

 

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You may remember that we launched a competition last month to celebrate the EARL Conference taking place. The competition was to win a free online training course for a team on either ‘Introduction to R for Analytics’ or ‘Introduction to Python for Analytics’.

We were thrilled to receive lots of brilliant entries and it was difficult to pick a winner. But after much deliberation the chosen winner of the competition is…..

Kirsten McMillan from Dogs Trust! 

Congratulations to Kirsten and her team. The Dogs Trust mission is to bring about the day when all dogs can enjoy a happy life, free from the threat of unnecessary destruction. They are a British animal welfare charity and humane society which specialises in the well-being of dogs. They are the largest dog welfare charity in the United Kingdom, caring for over 15,000 animals each year.

When asked why Kirsten would like to win this training for her team she said:

‘They are all extremely hard working and have proved hugely focused and flexible during the pandemic. They are all dedicated to improving canine welfare, which has become a significant issue during lockdown, due to the increased purchasing of dogs.’

We also asked Kirsten as part of her competition entry what her teams analytical objects are:

‘Our projects are very varied – so our analytical objectives are constantly changing. However, one of our aims is to become the go-to place for all UK dog statistics. Consequently, we are currently focusing on automating the collection, cleaning, and analysis of big data, along with the production of powerful datviz to be made available both internally and externally.’ 

On the team win Kirsten said;

‘We are so pleased and excited to have won this amazing prize! We are very much looking forward to the ‘Introduction to R for Analytics’ training with Mango Solutions, which will undoubtedly help us to help our much-loved dog population!

We are excited to support Dogs Trust move forward with their analytical journey, and perhaps see them present at a future EARL Conference!

EARL is back in 2022 in-person – the conference will be hosted from the 6th to the 8th of September in London. Abstracts will open for talks in January 2022 – sign up here to receive all the latest news.

managed service
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In a recent webinar, we provided an overview of our Managed RStudio platform and demonstrated how modern technology platforms like RStudio gives you the ability to collect, store and analyse data at the right time and in the right format to make informed business decisions.

The Public Health Evidence & Intelligence team at Herts Country Council demonstrated how they have benefitted significantly from the Managed RStudio – enabling collaborative development, empowerment and productivity at a time when they needed it most. In turn, they have been able to scale their department.

Many of the questions from the webinar focused on the governance and security aspects of Managed RStudio. In this blog, we’ve taken all your questions and have for further clarity attached a document that can help with any further questions regarding architecture, data management and maintenance.

Many of the questions asked were aligned to the management of data in the platform from the process of working with data on local drives, user interfaces to the management of large datasets.

There are several methods of getting data in and out of the Managed RStudio. These methods will largely depend on the type and size of the data involved.

For data science teams to work productively and deliver effective results for the business, the starting point is with the data itself. Data that is accurate, relevant, complete, timely and consistent are the key criteria against which data quality needs to be measured. Good data quality needs disciplined data governance, thorough management of incoming data, accurate requirement gathering, strict regression testing for change management and careful design of data pipelines. This is over and above data quality control programmes for data delivery from the outside and within.

Can you please elaborate on getting data into and out of the Managed RStudio platform?

Working with small data sets (< 100Mb)

For smaller data sets, we recommend using RStudio Workbench’s upload feature directly from the IDE. To do this, you can simply click on ‘upload’ in the ‘file’ panel. From here you can select any type of file from either your local hard disk, or a mapped network drive. The file will be uploaded to the current directory. You can also upload compressed files (zip),. which are automatically decompressed on completion. This means that you can upload much more than the 100Mb limit.

Working with large data sets (>100Mb)

For larger data sets or real-time data, we recommend using an external service such as CloudSQL or BigQuery (GCP), Azure SQL Database or Amazon RDS. These can be directly interfaced using R packages such as bigrquery,  RMariaDB or RMySQL.

For consuming real-time data, we recommend using either Cloud Pub/Sub or Azure Service Bus to create a messaging queue for R or python to read these messages.

Sharing data between RStudio Pro/Workbench, connect and other users

Data can easily be shared via ‘Pins’, allowing data to be published to Connect and shared with other users, across Shiny apps and RStudio.

Getting data out of Managed RStudio

As with upload, there are several methods to export data from Managed RStudio. RStudio Connect allows the publishing on Shiny Apps, Flask, Dash and Markdown. It also allows the scheduling of e-mail reports. For one-off analytics jobs, RStudio also allows you to download files directly from the IDE.

The Managed Service also allows uploading to any cloud service such as Cloud storage buckets.

Package Management

R Packages are managed and maintained by RStudio Package Manager giving the user complete control of which versions are installed.

RStudio Package Manager also allows the user to ‘snapshot’ a particular set of packages on a specific day to ensure consistency.

The solution to disciplined data governance

Data that is accurate, relevant, complete, timely and consistent are the key criteria against which data quality needs to be measured. Good data quality needs disciplined data governance and thorough management of incoming data, accurate requirements gathering, strict regression testing for change management and careful design of data pipelines. This all leads to better decisions based on data analysis but also ensures compliance with regulation.

As a Product Manager at Mango, Matt is passionate about data and delivering products where data is key to driving insights and decisions. With over 20 years experience in data consulting and product delivery, Matt has worked across a variety of industries including Retail, Financial Services and Gaming to help companies use data and analytical platforms to drive growth and increase value.

Matt is a strong believer that the combined value of the data and analytics is the key to success of data solutions.

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To celebrate EARL taking place this September we launched a competition to win a free online training course and the competition closes today at midnight – Submit your competition entry here.

You have the chance to win a 2-day training course for you and up to 9 other attendees from your company. The winner can select either ‘Intro the R for analytics’ or ‘Intro to Python for analytics’. The workshop will be delivered online on UK time – so you can enter from any location!

To enter you just need to complete this form and answer a few questions about you and your team. The closing date is the 30th of September 2021, the winner will be contacted in early October. Please read the full terms and conditions here.

 

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Thank you to everyone who joined us for EARL 2021 – especially to all of the fantastic presenters! We were pleased to receive lots of really positive feedback from the online event and there are plenty of highlights to share.

Branka Subotic, NATS

It was great to kick off EARL 2021 with our first keynote of the day from Branka. She has worked for NATS since 2018 and is currently their Director of Analytics. Branka shared with us interesting ways to help teams to work together and also some unusual ways to upskill! Her talk was peppered with some videos showing us flight data and the impacts of Covid.

Chris Beeley, NHS – Stronger together, making healthcare open- building the NHS-R Community

We are always delighted to hear from the NHS at the EARL Conference and this year was no exception. We were treated to a passionate talk from Chris on how the NHS-R community has been built up over the years and how their conference has gone from strength to strength. We all know how supportive the R community can be, so it is great to see this in action.

Amit Kohli – Introduction to network analysis

Amit gave us an introduction to the principles of network analysis and shared several use-cases demonstrating their unique powers. Amit also included a fun way to interact with his talk with the use of a QR code  – we can always rely on Amit to entertain us! Our team thought it was a really interesting topic and it felt accessible to those who perhaps don’t know much on the subject.

Emily Riederer, Capital One – How to make R packages part of your team

We loved Emily’s fun concept of making R packages a real part of your team and her use of code, and the choices she made along the way. Her talk examined how internal R packages can drive the most value for their organisation when they embrace an organisation’s context, as opposed to open source packages which thrive with increasing abstraction. Read our interview with Emily here.

Dr. Jacqueline Nolis, Saturn Cloud

We closed the day with our final keynote talk from Jacqueline Nolis. She is a data science leader with over 15 years of experience in managing data science teams and projects, at companies ranging from DSW to Airbnb. She currently is the Head of Data Science at Saturn Cloud where she helps design products for data scientists. Jacqueline spoke to us about taking risks in your career and shared with us the various risks she has taken over her career and how they went! It was inspiring to hear from an experienced data scientist that it’s ok to take a risk every now and then  – and refreshing to hear her honesty about what could have gone better – and how she has ultimately learned and grown from this.

These are just a few of the brilliant talks from a fantastic conference day. It was a delight to have speakers and attendees joining us from across the world – so thank you again to all that came along.

We are hoping to be back in London next year to host EARL in-person again. We are tentatively holding the 6th-8th of September 2022 as our conference dates. If you’d like to keep up-to-date on all things EARL please join our mailing list. We will open the call for abstracts in January 2022.

 

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Mango’s ‘Meet-Up’ at Big Data London on 22nd September features guest speaker Adam Hughes, Data Scientist for The Bank of England, whose remit involves working with incredibly rich datasets, feeding into strategic decision-making on monetary policy. You can read about Adam’s incredibly interesting data remit and his team’s journey through Covid-19, in this short Q&A.

Can you tell us about your interest in data and your role at Bank of England?

Working at the Bank it’s hard not to be interested in data! So much of what we do as an organisation is data driven, with access to some incredibly rich datasets enabling interesting analysis. In Advanced Analytics, we leverage a variety of data science skills to support policy-making and facilitate the effective use of big, complex and granular data sets. As a data scientist, I get involved in all of this, working across the data science workflow.

What’s the inspiration for your talk  – effectively data science at speed?

As with so much recently – Covid. With how fast things have been moving and changing, traditional data sources that policymakers were relying on weren’t being updated fast enough to reflect the situation.

Can you tell us about your data team’s journey through covid-19 and the impact it has had?

In a recent survey, the Bank of England sought to understand how Covid has affected the adoption and use of ML and DS across UK Banks. Half of the banks surveyed reported an increase in the importance of ML and DS as a result of the pandemic. Covid created a lot of demand for DS skills and expertise within the Bank of England too. Initially this led to some long hours, but it was motivating and generally rewarding to work on something so clearly important. Working remotely 100% of the time was a challenge at first, but generally the transition away from the office has been remarkably smooth in terms of day-to-day working (though there are still disadvantages due to the lack of face-to-face contact). As outputs have subsequently been developed and shared widely in the organisation, they have been an excellent advert for data science, showing the value it can add. In particular, it’s been great to see the business areas we worked with building up their local data science skills as a consequence.

What’s the talk about and what are the key takeaways?

The talk will cover some of the techniques we used to get, process and use new data sources under time pressure, including what we’ve learnt from the process. The key takeaways are:

  • Non-traditional datasets contain some really useful information – and can form part of the toolkit even in normal times;
  • Building partnerships is key;
  • A suite of useful building blocks, such as helper packages or code adapted from cleverer people helps speed things up;
  • Working fast doesn’t mean worse outcomes.

We look forward to seeing you at Mango’s Big Data London, Meet Up, 22nd September 6-8pm, Olympia ML Ops Theatre. You can sign up here.

Guest speaker, Adam Hughes is one of The Bank of England’s Data Scientists, https://www.linkedin.com/in/adam-james-hughes/

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We are launching a competition to celebrate the Enterprise Applications of the R Language Conference taking place from the 6-10th of September 2021.

You have the chance to win a 2-day training course for you and up to 9 other attendees from your company. The winner can select either ‘Intro the R for analytics’ or ‘Intro to Python for analytics’. The workshop will be delivered online on UK time – so you can enter from any location!

To enter you just need to complete this form and answer a few questions about you and your team. The closing date is the 30th of September 2021, the winner will be contacted in early October. Please read the full terms and conditions here.

EARL is a cross-sector conference focusing on the commercial use of the R programming language. The conference is dedicated to the real-world usage of R with some of the world’s leading practitioners. If you use R in your organisation, the EARL Conference is for you and your team. Whether you’re coding, wrangling data, leading a team of R users, or making data-driven decisions, EARL offers insights you can action in your company.

This year there are four online workshops you can join for £90 each and also a final day full of presentations on using R in enterprise, which is just £9.99.

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The opening keynote at the Enterprise Applications of the R Language Conference presentation day will be Dr Branka Subotić. Branka has over 15 years of experience in the aviation industry and she has worked for NATS for 12+ years. Branka will be joining Jacqueline Nolis as our second keynote speaker at EARL. The presentation day will run on Friday the 10th of September all-day – tickets to this event are just £9.99!

Branka made her start as the Senior/Principal Human Factors Specialist at the Directorate of Safety, working mostly on the implementation of the new enroute electronic system for air traffic control (iFACTS) into live operation at Swanwick Area Control (the UK’s largest air traffic control centre).

In November 2018, Branka joined the CIO team to lead the development and implementation of the enterprise-wide Data Strategy for NATS; working with a range of colleagues from across the business. This led to Branka becoming Director of Analytics, leading a team of 80+ analysts including a Data Science team focused on the implementation of advanced analytics and AI/ML. Branka’s analytics team is responsible for enhanced data-driven customer insights, tools, and services. The team brings together the data analytics functions and delivers insight and data-driven solutions to NATS operation, corporate functions, and customers around the world.

Branka holds a PhD in air traffic management from Imperial College London (UK), MSc in aeronautical science from Embry Riddle Aeronautical University (USA) and MEng in air transport engineering from the University of Belgrade (Serbia). She is also a Chartered Engineer.

And if you needed any more information, Branka is from Belgrade (Serbia) and has been living in few countries – Bosnia, France, USA, Germany and the UK!

Join other Rstat users and find how out other people are using R in enterprise – get EARL tickets today and get inspired!