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Simplifying and Centralizing Universal Data Quality in SSIS

Sponsored by - MelissaData

Webcast Abstract

There are many solutions and techniques for employing common forms of data cleansing, such as proper casing, abbreviations, search and replace patterns, and expressions. In SSIS however, it becomes tedious and complicated to achieve such routines as they typically involve the use of multiple components, and require some form of coding through script components. This is especially true when dealing with data types that require several cleansing rules that are specific for that domain and where data quality solutions are not readily available. In this webinar, we will see how Melissa Data simplifies and centralizes data quality, that can be applied to universally any type of data.

Learn different techniques in generalized data cleansing and how they can be easily implemented in SSIS, including:

- Proper Casing
- Punctuation Handling
- Abbreviations
- Expressions
- Search and Replace Tables

Speaker - Joseph Vertido

Joseph Vertido is a Data Quality Analyst at Melissa Data, Joseph Vertido is an expert in the field of data quality. He has worked with numerous clients in understanding their business needs for data quality, analyzing their architecture and environment, and recommending strategic solutions for how to successfully integrate data quality within their infrastructure. He has also written several articles for implementing data quality solutions and techniques. Joseph holds a degree in Computer Science from the University of California, Irvine.

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