datarobot

Chris Riley serves as President of Worldwide Field Operations of DataRobot, where he is responsible for accelerating the company’s revenue growth and global footprint, bringing DataRobot to organizations across all industries and geographies. Riley previously served as Chief Revenue Officer for Robotic Process Automation (RPA) leader Automation Anywhere, where he led global sales in over 90 countries and managed an ecosystem of over 1,900 partners. Prior to Automation Anywhere, Riley served as President of Global Sales at Dell Technologies, where he was responsible for a multi-billion dollar route to market. Riley also served as Vice President and General Manager for HP’s storage business at HPE. Riley lives in Naples, FL with his family.

In this conversation with John McMahon, Chris discusses the importance of understanding the culture and processes of a new organization when stepping into a leadership role. He emphasizes the need for leaders to be adaptable and willing to learn from their teams. Chris also highlights the significance of metrics and productivity in managing a sales organization, as well as the importance of hiring the right people and providing them with the necessary training and development. He shares insights on building trust with the sales team, prioritizing pipeline generation, and the role of mentors, coaches, and godfathers in a leader's career.

HERE ARE SOME KEY SECTIONS TO CHECK OUT:

[00:01:51] Overview of what DataRobot does and its applications

[00:15:13] The importance of work ethic, coachability, and aptitude in hiring

[00:23:47] Characteristics of successful leaders and the consequences of failure

[00:38:48] The most critical step in the sales process and the importance of a champion

[00:47:26] Navigating a sluggish economy and advice for salespeople

[00:54:15] The importance of hard work, generating pipeline, and following the process

HIGHLIGHT QUOTES

[00:22:02] "A mentor is somebody you can speak openly without fear of judgment." - Chris Riley

[00:36:35] “A good leader builds trust with the team and shows genuine interest in their success.” - Chris Riley

Learn more about Chris through this link:
https://www.linkedin.com/in/chrisriley3/

Check out John McMahon’s book here: https://www.amazon.com/Qualified-Sales-Leader-Proven-Lessons/dp/0578895064

Чи виправданим є страх перед штучним інтелектом? Чому нейромережа програє людині? Та що стане глобальною проблемою для покоління зумерів? З'ясовували з IT-фахівцем Борисом Дрожаком

At the end of every year, you’re probably asking the same questions we are. What are the big changes coming next year? How do I stay ahead of them? And what’s separating real trends from the hype?

To answer these questions, we are excited to bring together some of the top minds in the industry. In this special episode, we’ll pick their brains and dig into what you need to know to thrive in the year ahead. 

You’ll hear from three incredible guests -- all of whom are building and shaping the future of data and analytics:

• First, Ben Taylor, the Chief AI Evangelist at DataRobot
• Then, the Global Field CTO of Databricks, Chris D’Agostino.
• And finally, Bruno Aziza, the Head of Data & Analytics at Google Cloud.

Nothing is off the table. So whether you want to hear about augmented everything, dig into the debate around different cloud platforms, or learn why analytics has become more impactful than ever, this is the episode for you.

Key Takeaways

• CDOs must deliver simplicity but contend with complexity: As the data ecosystem continues to introduce new innovation at an ever increasing rate, data leaders must grapple with all these new capabilities. At the same time, however, the rising need for access to this innovation from nontechnical, business professionals means CDOs must simultaneously deliver simple, intuitive experiences that empower the rest of the business
• Is the data warehouse on the way out? D’Agostino makes a bold prediction that within 10 years, the traditional data warehouse won’t exist. That begs the question: what will replace it? The lakehouse, data mesh, and data fabric are all contenders, but require organizational changes, not just the introduction of new technologies, as Aziza points out. 
• Preventing bias within models: A consistent problem in the industry - one that we’ve touched on several times this year - is the potential for machine learning and AI to scale bias in unprecedented ways. As we enter 2022, it will become even more imperative that you and your team are able to answer questions like “how will this model potentially amplify basis,” “how can we prevent biases,” or “what biases exist in our data sets?” 
• Creating an ecosystem of data sharing: The rise of analytics exchanges creates massive opportunity for businesses for two reasons. First, it allows users to share data across platforms at a faster rate. And second, users are now able to share more than just data, but actual assets at an improved rate.
• In 2022, AI, ML, and data products must prove value: For years, companies have experimented with AI and ML, but as Taylor points out, the disillusionment with the impact of these experiments is at an all time high. So whether you’re building data products or launching new AI use cases, data leaders need to lead with the value they will deliver, not only imagine the art of what’s possible.

--

The Data Chief is presented by our friends at ThoughtSpot. Searching through your company’s data for insights doesn’t have to be complicated. With ThoughtSpot, anyone in your organization can easily answer their own data questions, find the facts, and make better, faster decisions. Learn more at thoughtspot.com. 

1. Full conversation video recording with Colin Priest.
2. Related guide from Quanton - 2020 Guide to Intelligent Automation
3. Summary article published to blog site.
4. Russell on LinkedIn