Skip to content

Data Science Process Alliance

  • Training for Individuals
    • Courses
    • Student Testimonials
    • Alumni Interviews
    • Register
  • Team Coaching
    • Private Group Courses
    • Agile Transformation
    • Implement Best Practices
    • Project / Team Launch
  • Frameworks
    • Ad Hoc
    • Life Cycles
      • Waterfall
      • KDD and Data Mining
      • SEMMA
      • CRISP DM
      • Microsoft TDSP
      • Domino Lifecycle
      • Others
    • Agile Coordination
      • Scrum
      • Kanban
      • Data Driven Scrum
    • Hybrid Approaches
      • Bimodal: Agile-Waterfall
      • Research & Develop
  • Blog
    • Agile
    • Team
    • Life Cycle
    • Project Management
  • About
    • About Us
    • Testimonials
    • Our Research
  • Contact
Register

Data Science Process Alliance

  • Training for Individuals
    • Courses
    • Student Testimonials
    • Alumni Interviews
    • Register
  • Team Coaching
    • Private Group Courses
    • Agile Transformation
    • Implement Best Practices
    • Project / Team Launch
  • Frameworks
    • Ad Hoc
    • Life Cycles
      • Waterfall
      • KDD and Data Mining
      • SEMMA
      • CRISP DM
      • Microsoft TDSP
      • Domino Lifecycle
      • Others
    • Agile Coordination
      • Scrum
      • Kanban
      • Data Driven Scrum
    • Hybrid Approaches
      • Bimodal: Agile-Waterfall
      • Research & Develop
  • Blog
    • Agile
    • Team
    • Life Cycle
    • Project Management
  • About
    • About Us
    • Testimonials
    • Our Research
  • Contact

Data Science Process Alliance

Category: Life Cycle

A picture showing a team discuss data science agility.
December 31, 2022Last Updated: January 19, 2023Life CycleBy Nick Hotz

OSEMN Data Science Life Cycle

Different data scientists have different processes for conducting their projects. And different types of projects require different steps. However, most data science projects flow through a similar workflow. One popular representation of this workflow is called OSEMN (pronounced “awesome”). Whether you use this or another life cycle, understanding the basic […]

Read more
July 28, 2022Last Updated: August 23, 2022Agile, Life CycleBy Jeff Saltz

The Data Science Maturity Model

A data science team’s process is a key driver to their projects’ success. However, as will be discussed below, there is not an existing AI / data science maturity model that is focused on how to evaluate (and improve) a team’s process. Hence, after reviewing several Analytics / Data Science […]

Read more
data science product management
June 25, 2022Last Updated: June 29, 2022Agile, Life CycleBy Nick Hotz

What is a Data Science MVP?

By their nature, data science products are risky. Building a Data Science MVP can reduce that risk by focusing the early development life cycle on discovery and learning. The onset of a data science project has a lot of unknowns – on the data, algorithm, systems, and business side. You […]

Read more
machine learning life cycle
May 31, 2022Last Updated: June 14, 2022Agile, Life Cycle, Project ManagementBy Jeff Saltz

The Machine Learning Process

The machine learning process defines the flow of work that a data science team executes to create and deliver a machine learning model. In addition, the ML process also defines how the team works and collaborates together, to create the most useful predictive model. A High Level Machine Learning Process […]

Read more
February 22, 2022Last Updated: August 1, 2022Agile, Life CycleBy Nick Hotz

What is the Data Science Process?

A data science process can make or break a team. Indeed, we see time and time again that many of the reasons behind data science project failures are not technical in nature but rather stem from process-related issues. Simply throwing compute power and PhDs at the problem doesn’t work. Rather, […]

Read more
January 26, 2022Last Updated: June 1, 2022Life CycleBy Jeff Saltz

What is a Machine Learning Life Cycle?

Explore what is a Machine Learning Life Cycle, and how it compares with a Data Science Life Cycle (by looking at OSEMN and CRISP-DM)…

Read more
March 21, 2021Last Updated: January 31, 2023Life CycleBy Nick Hotz

What is SEMMA?

The SAS Institute developed SEMMA as the process of data mining. It has five steps (Sample, Explore, Modify, Model, and Assess), earning the acronym of SEMMA. You can use the SEMMA data mining methodology to solve a wide range of business problems, including fraud identification, customer retention and turnover, database […]

Read more
March 21, 2021Last Updated: January 19, 2023Life CycleBy Nick Hotz

KDD and Data Mining

What Is the KDD Process? Dating back to 1989, the namesake Knowledge Discovery in Database (KDD) represents the overall process of collecting data and methodically refining it. The KDD Process is a classic data science life cycle that aspires to purge the ‘noise’ (useless, tangential outliers) while establishing a phased […]

Read more
data science life cycle
February 28, 2021Last Updated: September 5, 2022Life CycleBy Nick Hotz

What is a Data Science Life Cycle?

A data science life cycle is an iterative set of data science steps you take to deliver a project or analysis. Because every data science project and team are different, every specific data science life cycle is different. However, most data science projects tend to flow through the same general […]

Read more
most popular data science processes
November 30, 2020Last Updated: May 2, 2022Life CycleBy Jeff Saltz

CRISP-DM is Still the Most Popular Framework for Executing Data Science Projects

During the past few months, we conducted a poll to see what project management framework teams used to help execute their data science projects. Based on our survey of 109 respondents, nearly half of the respondents most commonly use CRISP-DM. This was followed by Scrum, Kanban and “My Own”. See results below. […]

Read more

Posts navigation

1 2 3 Next

Courses

Individual
Private Group
Testimonials
Alumni Interviews
Register

Frameworks

All Frameworks

Life Cycles
- CRISP-DM
- Microsoft TDSP
- SEMMA

Agile Data Science
- Kanban
- Scrum
- Data Driven Scrum

Blog

Latest
- DS Agility: A Benchmark
- Managing a Data Science Team
- Achieving Responsible AI
- The DS Project Manager

Popular
- Why Do Data Sci Projects Fail?
- DS Document Best Practices
- Data Sci Project Checklist
- Data Sci vs Software Engineering

About DSPA

The Data Science Process Alliance helps individuals and teams apply effective project management techniques and frameworks to improve data science project outcomes.

About Us
Terms of Service
Privacy Policy
Contact Us

Get Monthly Tips

Keep up-to-date on our research, data science project management insights, and course offerings.

Copyright 2023 @ Data Science Process Alliance. All rights reserved.

COURSE REGISTRATION

Thank you for your interest in a DSPA course!

Please fill out the form below as a first step towards course registration.

Finally… A Field Guide for Managing Data Science Projects

Data science projects are unique. It’s time to start managing them as such.

Get the jumpstart guide to better manage your next project.

Thanks for Your Interest!

 

We do not share your email address with anyone

We do not share your email address with anyone