The Value of Data Analytics and the Impact it Brings upon Organisations – Interview with Alteryx’s Product Strategy Director Nick Jewell

This blog post is part of the Big Data Week Speaker interviews series. We sat down with Alteryx’s Director of Product Strategy, Dr. Nick Jewell, and discussed the importance and value of data analytics and the impact it brings upon organisations.

Nick will speak at the upcoming Big Data Week London Conference, on October 5, about “Bridging the Gap: Key Lessons to Grow an Advanced Analytics Culture across Business, Technology and Data Science Teams“.  Reserve your seat today!

  1. What departments have the least to do with analysing big data yet whose resistance limit the benefits of big data for a company?

It can still be a battle to convince Information & Security Risk departments about the benefits of big data when applied to other departments and their bottom-line revenues. Over time, and by adopting governed analytics (as opposed to an analytic free-for-all) it’s possible to deploy analytics on top of big data in a way that ensures a company’s most valuable data and information assets can be shared with the right individuals to make the greatest organizational impact.

2. Could you give a few industry examples of how big data analytics have made a major bottom-line impact? 

I see huge impacts for global organisations on a regular basis! One particular industry that makes great use of big data analytics is commercial air travel. With over 4000 flights per day for a specific customer, they used big data analytics to improve their data analysis pipeline from a three-day process into an activity that takes only 10 minutes! The implications were enormous: analysts moved from a painful monthly forecasting process to being able to forecast up to 12-months at a time, with an associated 70% increase in fuel forecasting accuracy as a result. This was only possible due to enhanced collaboration between their analysts (with deep business domain expertise) and their data science teams by ensuring an easy transition from code-free drag-and-drop exploration to a code-friendly data science environment in R and Python.

We see organisations in the energy sector making huge strides towards modelling and managing parts failure in their vast supply chains and IOT (Internet of Things) sensor devices in the field. Optimisation and logistics are also huge drivers of profitability for these leading companies – analytics over a division’s complete stock catalogue resulted in greatly-improved warehousing stock levels and six-figure savings by holding the right amount of parts to meet their demand. Without a leading analytics platform working closely with a scalable big data solution, these bottom-line impacts would never have been attempted, let alone delivered.

  1. For non-technical executives, what’s the best way to communicate the value of big data and analytics to achieve organizational goals?

Big Data is really all about the enormous opportunity that comes from bringing together data from activities across today’s digital sources. A well-designed Big Data platform means that executives don’t have to wait for transactions, events or user behaviour to be delivered, summarized or massaged before critical questions can be answered: across multiple business channels and processes.

Analytics over Big Data provides insights at both the large and the small scale. We can track the pulse of an entire country through the payment transactions network at the point of sale. We can also personalize a recommendation or make a next-best-offer for an individual customer at exactly the moment that we think it’ll make the biggest difference. This capability used to be restricted to the few – the data scientists or statisticians working for large organisations. Now, we regularly see analysts emerging as ‘citizen data scientists’ – wielding powerful code-free technology to develop descriptive or predictive models without writing a single line of technical code. This grass-roots enablement will change many companies perspective over the art of the possible with analytics over the coming years.

  1. What’s your favourite story about the power of what you’ve seen big data analytics do when insights were applied meaningfully? 

Personally, I’m always excited to apply data science and analytic techniques for charitable or non-profit causes! In conjunction with DataKind UK, I’ve worked with some extremely talented data scientists and data journalists from Global Witness to deploy a large graph database analytics system in order to understand the beneficial ownership of UK companies. This information is provided through open data at Companies House, but only when it’s transformed into a network of individuals and connected companies do the relationships really start to ‘pop’ out. Large-scale graph analytics helps to answer questions related to fraud, tax evasion and other nefarious activities, and is a great example of using a broad range of analytic skills to follow the data science process for a worthy cause!


Nick is a Director of Product Strategy at Alteryx. In this role, he works within the company’s Product Management team to build and present its end-to-end platform vision with customers; acting as a product evangelist with analysts, data science communities and the wider public. Nick also holds a Ph.D in Information Science from the University of Sheffield and has been recognised in the dataIQ100 list as one of the most influential people in data-driven business in 2018.

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