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TDWI Chicago Update

At TDWI, we have been working hard to navigate this ever-changing landscape in the face of COVID-19, and we want to assure you that the health and well-being of our employees, customers, and vendor partners is our top priority. Therefore, due to the growing concern around the coronavirus (COVID-19), and in alignment with the guidelines laid out by the CDC and WHO, we have decided to merge this year’s TDWI Chicago Conference (May 10-15) with TDWI Orlando 2020 (November 8-13), where it can be a successful experience for everyone. The Chicago 2020 agenda will be replicated at TDWI Orlando 2020.

Our registration team will be in contact with individual registrants and sponsors directly.

Course Description

Modern Data Management, Onsite, CBIP Certification, TDWI Foundations

TH1 TDWI Data Quality Management: Techniques for Data Profiling, Assessment, and Improvement

May 14, 2020

9:00 am - 5:00 pm

Duration: Full Day Course

Level: Intermediate to Advanced

Prerequisite: None

Mark Peco

CBIP

Analytics Consultant and Instructor

Preview Course Materials Course Outline

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. But reactive data quality methods are not quality management; they are simply quality maintenance—a never-ending cycle of continuously fixing defects but rarely removing the causes. 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.

You Will Learn

  • Techniques for column, table, and cross-table data profiling
  • How to analyze data profiles and find the stories within them
  • Subjective and objective methods to assess and measure data quality
  • How to apply OLAP and performance scorecards for data quality management
  • How to get beyond symptoms and understand the real causes of data quality defects
  • Data cleansing techniques to effectively remediate existing data quality deficiencies
  • Process improvement methods to eliminate root causes and prevent future defects

Geared To

  • BI, MDM, and data governance program and project managers and practitioners
  • Data stewards and data curators
  • Data warehouse designers and developers
  • Data architects and data modelers
  • Data quality professionals