By using tdwi.org website you agree to our use of cookies as described in our cookie policy. Learn More

DATA QUALITY

Explore Data Quality Content

Upside Articles

Research & Resources

Webinars

Team Training

  • Data Preparation for Predictive Analytics

    This one-day session will expose analytics practitioners, data scientists, and those looking to get started in predictive analytics to the critical importance of selecting, transforming, and properly preparing data ahead of model building. more

  • Hands-on Data Manipulation and Cleaning in Python

    Data manipulation and cleaning in machine learning is estimated to take more than 50% of the time allotted for any given machine learning project. This course will cover topics important in handling structured and unstructured data, scraping data in Python, including using key packages such as Pandas, NumPy, and Matplotlib. more

  • Introduction to Data Wrangling

    This course addresses how to translate the problem statement, identifying data sources, exploring the data for relationships and recognize patterns, identifying the starting inputs for the model, preparing data, and validating it for the model fitting process. more

  • Supervised Machine Learning: Preparing Data & Deploying Analytic Models for Classification & Prediction

    Regression, decision trees, neural networks—along with many other supervised learning techniques—provide powerful predictive insights. These data-driven insights inform the forces shaping your organization’s outcomes. more

Upcoming Event Courses

  • Data Preparation for Predictive Analytics

    This one-day session will expose analytics practitioners, data scientists, and those looking to get started in predictive analytics to the critical importance of selecting, transforming, and properly preparing data ahead of model building. more

  • Hands-on Data Manipulation and Cleaning in Python

    Data manipulation and cleaning in machine learning is estimated to take more than 50% of the time allotted for any given machine learning project. This course will cover topics important in handling structured and unstructured data, scraping data in Python, including using key packages such as Pandas, NumPy, and Matplotlib. more

  • TDWI Data Quality Management: Techniques for Data Profiling, Assessment, and Improvement

    The only proven path to sustainable data quality is through a comprehensive quality management program that includes data profiling, data quality assessment, root cause analysis, data cleansing, and process improvement. more

  • TDWI Data Science Bootcamp Day 2:
    Supervised and Unsupervised Modeling

    You will learn how to explain models and model accuracy to business stakeholders. Model interpretation strategies and metrics for complex algorithms will be also be described, equipping you with the communication techniques needed to generate business value. more

  • TDWI Data Quality Management

    This course is designed to help your organization better understand and successfully tackle your data quality challenges. more

  • Introduction to Data Wrangling

    This course addresses how to translate the problem statement, identifying data sources, exploring the data for relationships and recognize patterns, identifying the starting inputs for the model, preparing data, and validating it for the model fitting process. more

  • DataOps: How to Deliver Analytics Better and Faster

    DataOps brings together data managers and data consumers through agile data management processes that account for data engineering, integration, data quality, and governance on an open platform that streamlines efficient development, continuous delivery, and overall data unification. While this may sound daunting, this half-day course will help you understand the efficiencies DataOps can deliver for your organization and how to focus on the next steps of your journey. more

  • Data Science Bootcamp // Data Sourcing and Preparation for Data Science

    In this session, we will provide an overview of sourcing and preparing data for data science and predictive analytics projects. We will use a motivating example from the speaker’s work and also touch on how Python, SQL, and Hadoop can be used in the data preparation workflow. more

  • Data Engineering, Integration, and Unification Essentials

    Data unification is a critical facet in data-centric organizations that empower their people with data, and data unification strategies accelerate cloud adoption and increase confidence for BI development, self-service data analytics, and data science projects. more

  • TDWI Data Quality Management: Techniques for Data Profiling, Assessment, and Improvement

    The only proven path to sustainable data quality is through a comprehensive quality management program that includes data profiling, data quality assessment, root cause analysis, data cleansing, and process improvement. more

Online Learning Courses