I recently spent a week in Las Vegas at Think 2018 to better understand where Data Science is today and where it could take your business moving forward. I walked away with a much better understanding of what my clients, and ultimately, your stakeholders, might expect from a Data Science solution. I believe Data Science Experience is going to change how we manage and lead our organizations forever.
What do I think data scientists expect from their data science platform?
Let’s see if I can influence you to why there might be a benefit to look into the IBM Data Science Experience for your team. These are my opinions, some backed by years of experience and others by some hands-on exposure to the tool being operated by people who do not work for IBM. I bring my own tech testers who can only be bribed by going out and seeing Las Vegas the way it should be explored!
I’m looking for three capabilities in my Data Science Experience. I want better, faster decision-making processes, a platform that can grow as my teams’ capabilities do, and a tool that lets me leverage my team’s experience and inexperience as a manager. Would that match you Data Science Experience wish list?
I’m a strong people developer, but my technical skills have never set me apart from my peers. I’ve been offered several senior technology executive roles in Fortune 20 organizations. I believe that I’m very good at getting the best out of teams, because the tools I use empower me to help my people leverage their own strengths, life experiences, and technical capabilities to solve their problems and challenges.
I’m very good at standardizing process and workflow while allowing for increasing flexibility and agility through the solutions development and its many iterations. I see my job as a manager and executive is to remove obstacles from my teams’ paths. I’m very good at putting a strong foundation under special projects that must succeed.
Seldom do I find two people in data science with similar skills, so the collaboration platform must provide increasing flexibility for my team members. I do not expect my people to be robotic, I do expect them to use process and workflow to get better results faster. I want to have the ability to store their solutions where other team members can build on them. A library of our best solutions provides a foundation for the future.
I expect my people to use the scientific method when exploring problems. I believe people get better by doing more projects, not through book leaning or training alone. Using good science is the foundation to extraordinary outcomes over the longer term. This also allows me to coach my people when they get stuck, a shared framework allows me and other team members to help them improve. When mentoring others, we all improve exponentially.
The second capability I want is tools flexibility. I’m a tool agnostic. Many of my manufacturing clients are using databases almost as old as I am. Good people can choose different tools, and both get great results. The question is when to standardize tool selection. I say it’s still too early. I believe we have just scratched the surface on what will be possible. My Data Science Experience will grow and change as technology continues to evolve and change. Data Science Experience allows me to track progress throughout a project’s life cycle.
Later this week we will share the third breakthrough capability for IBM’s Data Science Experience. We will also share several hard trends that may disrupt your data science program’s success or failure. See You on Thursday at Market Leadership Journal where I share What Are The Barriers To Your Data Science Teams’ Success?
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