An Overview of SQL

Throughout his career as a management consultant, Timothy Valihora has acquired a wealth of experience in software development, information technology, and data warehousing. Timothy Valihora also possesses significant experience with Structured Query Language (SQL), a popular special-purpose programming language designed to manage data in relational database management systems.

Initially released by Oracle Corporation nearly 35 years ago, SQL helps users request information from databases in a highly efficient manner. In 1986, the American National Standards Institute established SQL as a standard query language. One year later, the International Organization for Standards followed suit. Since then, the two organizations have updated the standards with features and extensions.

For many years, SQL has served as the preferred query language for databases operating on mainframes and minicomputers. In recent years, PC database systems have begun to support SQL on distributed databases, which allow users on a local area network to use the database at the same time.

Timothy Valihora: IBM QualityStage

Timothy Valihora is an IBM Information Server certified consultant fluent in numerous areas of information technology. He graduated from Carleton University in Ottawa, Canada, where he studied computer science, math, film, and commerce. To serve his clients, Timothy Valihora uses a wide array of software, server tools, and operating systems such as IBM’s InfoSphere platform, which includes QualityStage.

QualityStage is a powerful but accessible tool designed for enterprise users such as companies involved in gathering and examining business intelligence. In particular, QualityStage places users in control of a graphical user interface (GUI) where they can effortlessly implement automated processes. For example, sets of data can be matched according to user-specified rules and analyzed according to a diverse set of metrics.

One of QualityStage’s most powerful features is data cleansing, the ability to pull data from a source, measure it, clean it, consolidate it to eliminate redundancy, and upload it to a target system. Data cleansing occurs over five stages, each providing users with total data visibility. QualityStage also provides address verification, which verifies postal codes and other address information for over 240 countries.