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Episode 028 - Negotiating Big Data with Bill Schmarzo

6/2/2020

 
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Using big data effectively can be game-changing for a business. In this episode, Bill Schmarzo talks about how to leverage big data to add value to your business. Data is an asset to be exploited and help drive organization and business initiatives. 
Bill Schmarzo is regarded as one of the top Digital Transformation influencers on big data and data science. His career spans over 30 years in data warehousing, BI and advanced analytics. Before joining Hitachi Vantara, Bill served as CTO of Big Data at Dell EMC and VP of Analytics at Yahoo! He is the author of “The Art of Thinking Like a Data Scientist,” “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science.” Bill has a Bachelor's degree in math, computer science and business administration from Coe College and his MBA from the University of Iowa. He is an avid blogger and in 2019 was ranked the #4 Big Data influencer, #4 Data Science, and #6 Digital Transformation influencer worldwide by Onalytica.
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Bill is a fascinating and really insightful guy. We had a great conversation. He shares steps and practical advice you can use to integrate big data into your business and make huge transformations. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment.


Show Notes:
  • [00:28] Bill Schmarzo is the Chief Innovation Officer for Hitachi Vantara. 
  • [00:43] This episode is really going to be focused on big data, what you do about it, and how you get people’s heads wrapped around it. 
  • [01:17] Most organizations don’t have an appreciation for data as a source of innovation. 
  • [02:47] Bill’s turning point for his appreciation of data was when he was at Yahoo. 
  • [04:25] Big data has allowed organizations to change their role as business leaders. 
  • [05:41] Data is an asset to be exploited and help drive organization and business initiatives. 
  • [07:10] The value of data is how you use it. Start with your company’s business and strategic initiatives for the next 12 months. 
  • [07:43] How can the data I have help accomplish what is important in our business?
  • [09:23] When you bring the data science process into it the decisions haven’t changed, but the answers have changed. 
  • [10:07] The first mistake companies make is not focusing on what is important for the business. 
  • [10:43] Empower the front lines people that are close to the action. 
  • [13:14] They build their analytic solution cores one use case at a time. They go through a process to decide the data sets they need for that particular case. 
  • [16:06] Analytic modules are an asset that don’t depreciate with use, instead they actually appreciate in value.  
  • [18:21] Companies want analytic modules that they can quickly deploy and that learn and grow with their unique data. 
  • [20:07] Gain organizational consensus on the high-priority use cases to go after. 
  • [21:14] Next they do a proof of value, proving they can actually deliver value and solve the problem. 
  • [22:42] The digital media marketing, financial services and retail have big opportunities. Healthcare and industrial companies are trying to catch up as well. 
  • [23:16] If you don’t have a culture of collaboration this doesn’t work. 
  • [23:35] Don’t overcomplicate it. Keep it simple. It will get complicated enough. 
  • [24:01] At the end of the day, the only people that are actually creating value are the customers and the customer’s customers. 
  • [24:36] Don’t be afraid to make mistakes. You have to be fearless. Fear is only failure if you don’t learn from it. If you’re not failing enough, you're not pushing the edges or trying hard enough. 

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Links and Resources:
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State of the CIO Podcast Website
State of the CIO Podcast on Apple Podcasts
Dan on LinkedIn
Hypothesis Development Canvas
Bill on Twitter
Bill on LinkedIn
Big Data MBA: Driving Business Strategies with Data Science
Big Data: Understanding How Data Powers Big Business
The Art of Thinking Like a Data Scientist

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