data cleanse

While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.

While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.

This white paper describes the seven steps you need to develop a plan for data quality – one that scales to your growing business needs.

What are the long-term costs of bad data? This white paper gives you the answers and tells you how to fix it.

Learn what a Web Service is and how it works, the advantages of using a Data Quality Web Service, the technology assessment for implementation, and several case studies (Saab and other real world case studies) to demonstrate real life successes.

Tom Brennan and John Nydam explain the Melissa Data and Stalworth partnership, discuss the business problems caused by bad data, and describe how DQ*Plus provides a complete data quality solution for enterprise applications and commercial databases.

For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility. SAS adheres to five data management best practices that support advanced analytics and deeper insights: • Simplify access to traditional and emerging data. • Strengthen the data scientist’s arsenal with advanced analytics techniques. • Scrub data to build quality into existing processes. • Shape data using flexible manipulation techniques. • Share metadata across data management and analytics domains.

This white paper describes the seven steps you need to develop a plan for data quality – one that scales to your growing business needs.

What are the long-term costs of bad data? This white paper gives you the answers and tells you how to fix it.

While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.

Learn how email verification technology helped to minimize Party City's hard bounces at point-of-sale by allowing data to be cleansed and verified in real time, which greatly reduced the amount of human error.

Learn how email verification technology helped to minimize Magento's hard bounces at point-of-sale by allowing data to be cleansed and verified in real time, which increased their email deliverability rates by 25%.