{"id":1953,"date":"2019-09-16T03:11:09","date_gmt":"2019-09-16T03:11:09","guid":{"rendered":"http:\/\/kusuaks7\/?p=1558"},"modified":"2024-04-08T09:17:10","modified_gmt":"2024-04-08T09:17:10","slug":"how-to-help-a-non-technical-audience-understand-their-readiness-for-data-science","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/bigdata-cloud\/how-to-help-a-non-technical-audience-understand-their-readiness-for-data-science\/","title":{"rendered":"How to help a non-technical audience understand their readiness for Data Science"},"content":{"rendered":"\t\t
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\n\t\t\t\t\t\t\t\t\tLast week I had the pleasure of working with the\u00a0University of South Wales (USW)<\/a>\u00a0to help non-technical people\u00a0understand Data Science<\/a>.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tMore specifically, I was running a Masterclass entitled \u201cEveryday Data Science<\/em>\u201c. The brief was to demystify this topic for a diverse audience. It was clearly popular as it drew a good crowd.\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tThe delegates who attended my Masterclass varied from data analysts to directors. However, most worked in some branch of public sector services.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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What do you cover when you get such a brief?<\/h2><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tMy first challenge was what to include. It is always tempting when dealing with a topic like this to rush into evidencing ones technical credentials. But all\u00a0speakers<\/a>\u00a0should start by focussing on \u2013 what does your audience need?\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tIn this case, I decided they needed an overview and specifically the ability to assess whether or not\u00a0Data Science<\/a>\u00a0was relevant for them. To achieve the second half of that, I sought to focus on enabling them to assess their\u00a0readiness for Data Science<\/a>.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tIt was a good session with great involvement from those who participated. So, I would encourage those who work in South Wales to consider attending one of\u00a0USW\u2019s masterclasses<\/a>. Further down this post, I have also shared the slides that I used via SlideShare.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tThe point of this blog post is to share the content choices that I made to answer this challenge. I hope it helps you if you need to\u00a0communicate<\/a>\u00a0about\u00a0Data Science<\/a>\u00a0to a non-technical audience within your business.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Make it personal, even for Data Science and AI<\/h2><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tThe first challenge for all speakers is the WIIFM of your audience. That\u2019s \u201cWhat\u2019s In It For Me?<\/em>\u201d So, I chose to focus on them all as UK citizens.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tI engaged them personally by sharing just an excerpt of\u00a0some\u00a0Data Science stories<\/a>\u00a0from the news. As well as one that was timely, this was deliberately a mixed diet of potentially positive and negative implications.\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tFor instance, on the positive side, I shared about how\u00a0Data Science<\/a>\u00a0has helped with reducing bias in marking at university, improving the energy efficiency of power stations and training the UK Womens\u2019 World Cup football team.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tTo get delegates thinking about the potential downsides, I shared on the Brexit referendum, Crime Prediction & potentially racist search algorithms. It\u2019s surprising how people relate to the risks to them even better than they engage with positive opportunities.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Understanding Data Scientists are different<\/h2><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tOne of the goals expressed by delegates at the start of my Masterclass was to understand how Data Scientists differ from Analysts. As\u00a0we have shared before on this blog<\/a>, many commercial businesses are also still confused about which they need.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\t\nTo bring this to life, I shared both the inevitable Venn Diagram definitions of\u00a0Data Science<\/a>\u00a0and why they thus need a wide range of skills.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\t\nThis section gave me the opportunity to emphasise both the range of\u00a0technical skills<\/a>\u00a0and\u00a0softer skills<\/a>\u00a0needed. I have shared before on the benefits of having a\u00a0competency framework<\/a>. So, I shared the EDISON framework to understand the breadth of technical skills needed. This was complemented by my own\u00a0Softer Skills 9 Step Model<\/a>.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\t\nFinally, I wanted to alert delegates as to the ways that\u00a0Data Scientists<\/a>\u00a0need to work differently. So, in this section, I shared both some of the popular\u00a0Data Science methodologies<\/a>\u00a0and the relevance of\u00a0Agile Working<\/a>.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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What are others doing with their Data Science applications?<\/h2><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tThese days everyone seems to want use-cases. To learn from other applications & avoid being \u201cbleeding edge<\/em>\u201d innovators. So, I shared some\u00a0applications<\/a>\u00a0that have impressed me.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tThis was a useful opportunity to highlight several of the case studies that I have heard eloquently outlined at other events. So, I drew on the following conferences:\n