data-analytics

In this article, we interview two speakers from the upcoming London Data Fest, taking place on 16th and 17th November. Eleftherios Diakomichalis, head of data (science and engineering) at SoundCloud, who is speaking at the Big Data & Analytics Innovation Summit, and Paul McDonagh-Smith, digital capability leader at Massachusetts Institute of Technology, who is speaking at the Data Visualisation Summit.

SoundCloud’s head of data on the biggest game-changers for analytics professionals

Eleftherios Diakomichalis currently leads the data science and engineering teams at music streaming service SoundCloud. He joined the company in 2011 as a data analyst, helping the company grow from 30 employees and 2 million users to more than 300 employees and a reach of 175 million people every month. We sat down with him ahead of his presentation at the Big Data & Analytics Innovation Summit.

How did you get started in analytics?

I was curious about data and math at high school, so I started engaging with answering questions analytically early on. When it comes to my career, it came naturally after I enrolled in my stats undergrad.

Are there any recent innovations or technologies that you see as a game changer for analytics professionals?

I think the rise of cloud computing is the biggest game changer as it enabled us to really have the conversation about big data and AI in a meaningful way for the society. Also, deep learning and the ability to generalise from unstructured data is a big deal.

What are the unique challenges facing you in your current role at Soundcloud that you are looking to solve with analytics?

Most of my challenges today are organisational challenges – basically how to realise the potential of the technology we have available and our resources in the most optimal way. Analytics around organisations and people are, unfortunately, a bit behind.

What will you be discussing in your presentation?

I will be sharing my learnings from six years of hyper-growth at SoundCloud. You can see an intro here, but I will be going more in depth talking to an audience that understands the domain.

You can hear from Eleftherios, along with other experts in data analytics, at the Big Data & Analytics Innovation Summit. View the full agenda here and secure £200 off with the code TCN200 by registering here.

How data visualisation supports MIT’s online learning experiences

Paul McDonagh-Smith, digital capability leader at Massachusetts Institute of Technology, has led teams to imagine, build, and bring to market innovative and groundbreaking collaboration and education platforms.

In his work with MIT Sloan’s Office of Executive Education, McDonagh-Smith partners with internal and external stakeholders to design, deliver and embed technology based education solutions to complex challenges, through a collaborative blend of technology, systems thinking, research, rapid prototyping and experimentation which strengthens creativity, productivity, and digital capabilities. We sat down with him ahead of his presentation at the Data Visualisation Summit.

What role does data visualisation play in your role at MIT?

In essence, data visualisation supports two crucial aspects of our online learning experiences: sense-making and communication. Advances and evolutions in the diversity and depth of data sets that sit behind Visualisation bring us nearer to an understanding of key dynamics of online teaching and learning. Clear, concise data visualisation provides an evidence-based analysis of educational experiences that can be a powerful catalyst for change and improved outcomes. Interestingly, they also provide an opportunity to capture insights that have the potential to improve in-person learning experiences.

What are the biggest data visualisation challenges you currently face in your role?

Data visualisation provides the opportunity to identify areas where we can improve teaching and learning experiences and outcomes. In order to secure this opportunity we need to be mindful of:

  • Context of the data
  • Visualising what matters
  • Ensuring data quality
  • Relevance of outlier data
  • Building visualisation into improvement process

What will you discuss in your presentation at Data Visualisation London?

The objective of the presentation will be to provide real world examples of how we are currently using data visualisation to enhance online teaching and learning experiences. I will aim to show how data visualisation enables the creation, capture and delivery of new educational value. An effort will be made to address key challenges/future ambitions.

Are there any approaches or technologies you see impacting data visualisation the most in the next five years?

In the near term (0-24 months) we might reasonably suspect that a range of approaches and technologies could significantly impact data visualisation, including:

  • AI enhanced simulations/scenario planning
  • Mobile data visualisation toolkits
  • Personal data visualisation interfaces and management
  • Video display of data visualisation insights

You can hear more from Paul, along with other industry leaders, at the Data Visualisation Summit. You can view the full agenda here and secure £200 off with the code TCN200 by registering here.

The London Data Fest returns this November, featuring both the Big Data & Analytics Innovation Summit and the Data Visualisation Summit, as well as the Chief Data Officer Summit. Visit the website for more information.  

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