Executives who rely on data analytics face a squeeze from two directions. On one hand, analytics continues to be ever more important in making business decisions – if you're not getting the most from your analytics solution, you're likely falling behind.
Yet on the other hand, data analytics continually grows more complex, as advances in software and methodology enables greater insight, but also greater operational challenge.
To shed light on the rapidly growing data analytics sector, I’ll speak with two leading experts: Andi Mann, Chief Technology Advocate at Splunk, and Bill Schmarzo, CTO, IoT and Analytics, Hitachi Vantara.
Scroll down to see an edited transcript of highlights from"Data Analytics 2020."
Download the podcast:
Andi Mann, Chief Technology Advocate, Splunk
Bill Schmarzo, CTO, IoT and Analytics, Hitachi Vantara
In this webinar you will learn:
- What does it mean to "think like a data scientist?"
- How might a possible economic recession affect data analytics practices?
- Which the many forecast data trends for 2020 will be the most influential?
- How can you use your analytics solution to get the greatest competitive advantage?
Edited Highlights from the Recorded Video:
What does it mean to think like a data scientist?
Bill Schmarzo recently published a book “The Art of Thinking like a Data Scientist."
Shmarzo: "Art is a very important part of that, because what we find in a lot of our data science engagements is there's a lot of exploration of what might be possible, the realm of what's possible. So, we tried to empower the power of ‘might,’ right?
"That might be a good idea, that might be something, because if you don't have enough might ideas, you never have anything, any breakthrough ideas.
"And so, this art of thinking like a data scientist, this kind of says, 'Yeah, there's a data science process.' But think about it as guardrails, not railroad tracks. And we're going to bounce in between these things.
"And oh, by the way, it's really important that your business stakeholders, your subject matter experts, also understand how to think like a data scientist in this kind of non-linear creative kind of fashion, so you come up with better ideas.
"Because we're all in search of variables and metrics that might be better predictors of performance, right? And the data science team will have some ideas from their past experience. But it's really about: 'how do we get the business users to really start thinking more creatively and to unleash those creative juices?'”
Mann: "Humans are really good at imagination. Pictures, ideas, thoughts, leaps of faith, if you will. So thinking like a data scientist, to me at least, is starting to understand that we're not that good at these hardcore mathematical pattern algorithmic operations, but we are really good at imagination, creativity.
"So look for the right data, look for the correlations in the connections in the data. Let the algorithms do the hard work, but keep asking questions, because that's the role of the human being in this number-crunching world.
"We have the insight to ask the right questions, and when we get more data back, we ask more questions. And this inquisitiveness, I think is the role of humanity in this machine learning AI-driven world."'
Pundits say 2020 might bring a recession. How will this affect the practice of data analytics?
Mann: "I recently gave a presentation on what's on the mind of transformational CIOs. And one of the tools I used to look into that mindset is automation and skillsets. So when you don't have enough people to fill the skills yet, you start to use tools and automation to do it instead. So for data analytics, maybe that means more and better tools to do data analytics.
"The other way it could go is maybe it means we cut back because we're not proving success enough. And there's a lot of opportunity to be successful in data analytics and we see it all the time, but there's a lot of people who are not seeing this, and like I said, not trusting the algorithms, not getting the results they want, believing that their opinion is better than the analytics they've got. And so maybe we end up going away from that because of the cost aspects.”
Schmarzo: "I actually think a recession would be great for data science and big data. Because I think what would happen is we would see organizations forced to focus on the value creation aspects of data and analytics.
"They would look at what they're trying to achieve in, during this recession, and try to really focus on: 'how do data and analytics help us to survive, maybe even prosper in a situation?'
"I think we're going to see the separation, the divide between organizations who during recession are gonna hunker down, just try to survive and ride it out, which is the common mentality. But I think there are going to be wolves out there. Companies are going to see this opportunity, as other companies are backing down – they're going to increase their spend and their use of data and analytics to improve their target marketing, to improve their customer acquisition, to improve their way to build out new channels and ecosystems.”
For data analytics in 2020: what key piece of advice would you give to managers and executives?
Mann: “Look, it's a tagline but I really believe it's true. ‘Bring data to everything.’ And what I mean by that is, to every device, to every business decision, to every operational change, use the data you've got to make it better.
"You can start small, I advise people to start small. Find a data set that tells you something. Maybe it's the weblogs out of your web store that tell you what your customers are buying. Maybe it's the fuel utilization on your part and equipment.
"It can be a really simple small data point that gets you started down this road of making data-driven decisions. Question the basis for your decision-making. Is it opinion? Is it data? Is the data good? And how does it match up or contradict the opinion?
"So I would just say: start by bringing data to every decision. Start small, look for data that matters, find the data points that will help you decide something and keep iterating on that."
Schmarzo: "I think for organization to be successful, it just needs to become a business mandate. It can't be the CIO trying to push the role, right? We need to have a business mandate for an organization that really seeks to go out and derive and drive new sources of customer product operational value – measurable, meaningful, value.
“Think about this. As a company, you have all this data you've already paid for, how many hundreds of millions of dollars for your ERP systems and supply chain systems and web systems and mobile? You've got all this data and you ain't doing crap with it, from a business monetization perspective.
"So to me, it's almost befuddling that a company would turn around and look and see all these gold nuggets piled up here, and wonder, ‘Hmm, how are we gonna ride out this recession? We don't have the answers here.’ You've got gold sitting back here, fool. Yeah, I pity the fool who doesn't see that.
"So to me, I see CIOs really trying to push this agenda. It's hard. They can be the advocate but at some point in time, the business leadership needs to step up and say, 'We need to change the game by changing the frame about how we think about data as an asset.'"