TDWI: Data Transformation Techniques

Explore Data Transformation and Integration Content

As data sources grow in size, number, and complexity, your enterprise must learn how to get the most from all its data. This section focuses on techniques and best practices for unifying and integrating your data. It also explains techniques for creating, maintaining, and automating extract/transform/load (ETL) and other data munging processes.

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Webinars

Making Your Data and AI Ready for Business Transformation
Join us to hear James Kobielus, TDWI senior research director for data management, explore how AI is driving digital business transformation initiatives the world over and how enterprises are accelerating this push by using AI to automate, accelerate, and enhance their data pipelines. June 18, 2024 learn more
Drive Faster Insights from Your Data
Register today to learn how your organization can solve data integration challenges, increase data engineering productivity, and enable cross-functional collaboration. April 16, 2024 learn more
Using Your Lakehouse as a Customer Data Platform
Join TDWI’s senior research director James Kobielus on this webinar to explore the importance of the data lakehouse as the foundation of the enterprise customer data stack. April 10, 2024 learn more
Reducing Time to Insight and Maximizing the Benefits of Real-Time Data: Research Insights from the Latest TDWI Best Practices Report
Register today to attend this TDWI Webinar and be the first to hear the latest TDWI research into current trends, challenges, and solutions for reducing time to insight and taking advantage of real-time data. March 25, 2024 learn more
Simplifying Orchestration, Observability, and Control Over Hybrid Data Pipelines
Join us to hear James Kobielus, TDWI senior research director for data management, and Peter Baljet, Stonebranch CTO, as they explore best practices for simplifying orchestration, observability, and control over hybrid enterprise data pipelines and demonstrate Stonebranch’s offering. March 6, 2024 learn more
Expert Panel: Responsible Cloud Migration
To ensure data integrity and the privacy of the data moving to the cloud, you’ll need a responsible approach, which our TDWI expert panel will describe in this fact-filled webinar. March 4, 2024 learn more

TDWI Webinars

Research & Resources

Digital Dialogue | Using AI to Develop and Optimize Pipelines
In a recent webinar, TDWI VP and senior research director, Fern Halper, Ph.D., spoke to Matillion’s VP of products, Gwendal Vaz Nunes, about using AI to help develop pipelines. learn more
Checklist Report | Unifying Transactional and Analytical Data to Drive Modern Applications and Analytics
This TDWI Checklist focuses on how organizations can gain advantage from unifying data on modern cloud data platforms. learn more
Composable Customer Data Platform (CDP) Market 2023
Discover the future of CDPs in this new guide. Evaluate your current options for composable CDPs and figure out which one is right for your organization. learn more
Build Vs Buy Is Dead: Compose Your Customer Data Platform (CDP) in 2023
Download this white paper now to navigate the shifting landscape of CDPs in 2023 and implement a platform that will scale for your future needs. learn more
TDWI Checklist Report | Six Best Practices for Harnessing Real-Time and Streaming Data Pipelines
This TDWI Checklist Report examines six important considerations and best practices for managing streaming data for real-time use. learn more
How Organizations Can Achieve ESG Data Mastery
Download this white paper now to prepare your organization for robust ESG reporting. learn more

TDWI Research

Podcasts

What's Ahead in 2024 with Fern Halper and David Stodder December 18, 2023
Part Two | Achieving Success with Modern Analytics with Teresa Letlow and Jason Yeung July 24, 2023
DataOps & MLOps Pipeline Integration with James Kobielus April 25, 2023
Strategies for Overcoming Data Silos with David Stodder March 13, 2023

TDWI Podcasts - Speaking of Data

Upside Articles

Reducing Time to Insight with Kevin Bohan
How can improving data management result in faster data access and sharper insights? April 18, 2024 read more
Four Tips to Modernize Legacy ETL Processes
Modernizing ETL, especially the underlying infrastructure that supports it, across all your lines of business is vital for enhancing downstream analytics and decision-making. April 11, 2024 read more
How a Universal Semantic Layer Enables Consistent Answers to Business Questions
The proliferation of data models and business logic across different tools has become problematic. The beauty of a universal semantic layer is that it supports many data sources and many BI systems and data applications so teams can continue to use their preferred tools. April 1, 2024 read more
How to Eliminate Data Silos in Start-Ups
Navigating the challenges of data silos is paramount for start-ups aiming at seamless scalability. This guide draws inspiration from professional experience and case studies, offering start-up leaders a comprehensive step-by-step strategy to eliminate silos. March 18, 2024 read more
Changing Organizational Needs Are Driving Integration Changes
Enterprise spending on integration solutions continues to climb. What’s driving this growth and how is it impacting your organization? February 9, 2024 read more
Data Management and the Next Generation of AI
James Kobielus, TDWI’s senior director of research for data management, talks about how to update your data management practices to prepare for the next generation of AI. February 6, 2024 read more

TDWI Data Transformation and Integration Articles

Team Training

TDWI Data Virtualization: Solving Complex Data Integration Challenges
The data integration landscape has changed radically the past few years. What was once a relatively manageable problem of blending and unifying data from enterprise transaction systems has grown to encompass external data, Web data, clickstream data, end-user data, big data, cloud data, and more. learn more
TDWI Data Quality Management: Techniques for Data Profiling, Assessment, and Improvement
Data quality is one of the most difficult challenges for nearly every business, IT organization, and BI program. The most common approach to data quality problems is reactive—a process of fixing problems when they are discovered and reported. learn more
TDWI Data Quality Management: Techniques for Data Profiling, Assessment, and Improvement
Data quality is one of the most difficult challenges for nearly every business, IT organization, and BI program. The most common approach to data quality problems is reactive—a process of fixing problems when they are discovered and reported. learn more
TDWI Data Virtualization: Solving Complex Data Integration Challenges
The data integration landscape has changed radically the past few years. What was once a relatively manageable problem of blending and unifying data from enterprise transaction systems has grown to encompass external data, Web data, clickstream data, end-user data, big data, cloud data, and more. learn more

TDWI Team Training

TDWI Transform 2024 Chicago

Data Science Bootcamp // Data Sourcing and Preparation for Data Science
This course provides an overview of the data sourcing and preparation activities in data science and predictive analytics projects, highlighting key principles and practices and providing business examples to reinforce each concept. learn more
DataOps: Best Practices for Agile Data Management
DataOps is a process-focused and automated methodology for delivering data for machine learning and AI that concentrates on reducing cycle time and improving the quality of advanced analytics deliverables. DataOps builds on the concepts of DevOps, continuous integration and delivery (CI/CD), and agile. learn more
Modern Data Engineering for Tomorrow's Enterprise Landscape
This half-day course delves into cutting-edge practices to sculpt and refine robust data pipelines. Immerse yourself in the intricacies of data engineering for data meshes, data warehouses, data lakehouses, and data virtualization. learn more
TDWI Data Virtualization: Solving Complex Data Integration Challenges
Get ready to expand your data integration capabilities, deliver business-speed information, and make the most of recent advances in data integration technology. Through a combination of lecture, exercises, and case study review you will learn how data virtualization works and how to position it in your data integration architecture and processes. learn more
Decision Trees in Machine Learning: Building Explainable Models
This half-day session will dedicate half of its time to translating the business problem into a form that the algorithms can support and preparing data for optimal performance during modeling. The second half of the course focuses on different decision tree algorithms for classification and regression. Participants may consider “Predictive Modeling with Ensembles” as a natural follow-on to this course. learn more
Unsupervised Machine Learning: Preparing Data & Deploying Analytic Models for Clustering & Association
This course will demonstrate a variety of examples starting with the exploration and interpretation of candidate models and their applications. Options for acting on results will be explored. You will also observe how a mixture of models including business rules, supervised models, and unsupervised models are used together in real-world situations for various problems like insurance and fraud detection. learn more

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TDWI Transform 2024 San Diego

TDWI Data Virtualization: Solving Complex Data Integration Challenges
Get ready to expand your data integration capabilities, deliver business-speed information, and make the most of recent advances in data integration technology. Through a combination of lecture, exercises, and case study review you will learn how data virtualization works and how to position it in your data integration architecture and processes. learn more
Modern Data Engineering for Tomorrow's Enterprise Landscape
This half-day course delves into cutting-edge practices to sculpt and refine robust data pipelines. Immerse yourself in the intricacies of data engineering for data meshes, data warehouses, data lakehouses, and data virtualization. learn more
Data Science Bootcamp // Data Sourcing and Preparation for Data Science
This course provides an overview of the data sourcing and preparation activities in data science and predictive analytics projects, highlighting key principles and practices and providing business examples to reinforce each concept. learn more
DataOps: Best Practices for Agile Data Management
DataOps needs to deliver consistent and meaningful data which means automating the data lifecycle of acquisition, understanding, integration, transformation, and deployment. This course will address best practices that contribute to consistent and automated analytics results. learn more
Modernizing Master Data Management to Effectively Support Business Processes
In this course, you will learn how to modernize your program for effective results. By examining the root causes of missed expectations for MDM, we will learn how business data consumers depend on corporate information assets such as customer or product information. learn more

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Upcoming TDWI Seminar Courses

Building Your Company’s Data Governance Roadmap
In this class, Evan Levy will review the business drivers for a data governance program and show you how to identify and prioritize program goals and objectives, identify teams and team members (along with their roles and responsibilities), and identify an agenda and process that delivers business value. learn more
Building Your Company’s Data Governance Roadmap
In this class, Evan Levy will review the business drivers for a data governance program and show you how to identify and prioritize program goals and objectives, identify teams and team members (along with their roles and responsibilities), and identify an agenda and process that delivers business value. learn more
Building Your Company’s Data Governance Roadmap
In this class, Evan Levy will review the business drivers for a data governance program and show you how to identify and prioritize program goals and objectives, identify teams and team members (along with their roles and responsibilities), and identify an agenda and process that delivers business value. learn more

Upcoming TDWI Seminars