32: Dean Marchiori: Going full circle
cindytonkin's podcast
Dean Marchiori is my guest this week. If you're after something to do while you're self-isolating, working from home or panicking about your supplies of printer toner, have a listen.
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31: Moha Ganji: planning, mentors, reflection
cindytonkin's podcast
Moha Ganji and I had a lovely time talking about being one of the IAPA Top 25 leaders, the importance of planning and reflection time, where she finds mentors, and more.
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30: Lori Silverman: not just decisions: Actions!
cindytonkin's podcast
My guest today is Lori Silverman. Lori is not a data person as such: she specialises in getting organisations to shift. And she has some fascinating things to say around how data stories are told.
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29: Chris Crook: Targeted curiosity
cindytonkin's podcast
Chris Crook from Nature Research is my guest today. Nature Research just won a B&T, and the award itself looks quite beautiful, quite casually hanging out with the mags in their foyer.
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28: Gabe Mach: Nothing you can't fix with numbers
cindytonkin's podcast
Gabe Mach is my guest on this podcast. Gabe is one of IAPA's top 25 leaders in 2019. He's entertaining, interesting and thought-provoking.
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27: Nate Watson: Math is the cultural equalizer
cindytonkin's podcast
Nate Watson talks about how urgent it is for organisations to start using their data for decisions.
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26: Tony Savides: the Magnificent So What
cindytonkin's podcast
Tony Savides was recently honoured as one of the top 25 Leaders in Analytics by the Institute of Analytics Professionals
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25: Satya Upadhyaya: Marketing Technologist
cindytonkin's podcast
Satya Upadhyaya is a Marketing Technologist.
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24: Maura Church: Life work harmony
cindytonkin's podcast
Maura Church makes data into insights at Patreon.
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22: Vin Vashishta - interesting and useful
cindytonkin's podcast
Vin Vashishta is a big name in data science.
info_outlineShailendra Kumar is the author of Making Money out of data. It's not an analytics book, it's a business book.
Shaily is a keynote speaker on data analytics. In this podcast he talks about the "everyone does analytics" phenomenon, the importance of articulating the business problem before anything else, and what makes a real data scientist.
Here's a summary:
- How he prospers in a world where "everyone does analytics"
- Analytics as a business or strategic function, not an IT function
- the importance of creating the need first
- What problem are you solving?
- no one thinks about the problem - you need to articulate a business problem. Tell me in plain English the business problem, devoid of technical terms
- what if the client doesn't have a business problem?
- how much money will the business problem save when the problem is fixed?
- people tend to mix up analytics, data science, pattern recognition, machine learning, AI, predictive.
- sales people throw buzzwords around and they don't know what's underpinning it - it's important that they use the right terminology, or they'll deliver things which aren't the thing you've sold in; and then the client blames the function
- with 23 million Australians and 250,000 people on linked in saying they do data science - is that true? there are really only 20 people who can really do analytics: someone who was writing SQL has now "become" a data scientist
- skills of a good data analyst: must have stats and problem solving
- analytics is a creative field
Get more at https://consultantsconsultant.com.au/podcast/5-shailendra-kumar/