Abstract: Informatica Corporation’s Informatica PowerCenter 5 is a platform for integrating data to be deployed in e-Business applications, analytic applications and data warehouses, including a wide range of data sources, from enterprise resource planning (ERP) systems such as SAP R/3 and PeopleSoft, to web logs and Siebel applications. Market validation of its offerings is shown in a record Q4 of 2000, with a 150% increase in revenue over the previous year.

Abstract: Data leakage and data breach are two disparate problems requiring different solutions. Data leakage prevention (DLP) monitors and prevents content from leaving a company via e-mail or Web applications. Database activity monitoring (DAM) is a data center technology that monitors how stored data is accessed. Learn why DAM complements DPL, and how you can benefit by making it part of your overall data security strategy.

Abstract: Sybase® (NASDAQ: SYBS) has signed a worldwide OEM agreement with Informatica Corporation (NASDAQ: INFA) to resell Informatica’s extract/transform/load tool PowerMart® along with Sybase’s new vertical application suite known as Industry Warehouse Studio®. This is yet another move by a database vendor to supply complete analytic solutions to customers, particularly e-businesses.

Abstract: Informatica Corporation (Nasdaq: INFA) announced products that enable resellers and distributors around the world to convert Informatica software to any major language for resale in their local markets.

Abstract: Informatica Corporation (Nasdaq: INFA), a major extract/transform/load tool vendor, today announced the general availability of MX2 1.6, the latest version of its Metadata Exchange (MX2) application programming interface (API). Informatica bills MX2 1.6 as the first object-oriented metadata exchange facility to support XML, a text-based programming language standard for integrating and managing bi-directional metadata exchange.

Abstract: Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.

Abstract: To derive maximum value from your data, you need a strong data governance program that helps develop and manage data as a strategic business asset. The success of a data governance program thus hinges upon a robust data integration technology infrastructure. Developing the right technology infrastructure is critical to your ability to automate, manage, and scale your data governance program.

Abstract: Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

Abstract: Rising data volume is not the only reason companies are concerned with issues of data integration and data quality. The growing numbers of disparate systems that produce and distribute data add to the complexity. But in many companies, data quality management has not kept pace with the growth of data integration projects, and its use is immature. Find out how moving toward a single data services architecture can help.

Abstract: You can blame your sales people all you want, but if the lead data is bad, they’re not going to bring in business. You can blame your product managers for ineffective promotions, but if the target lists are redundant, the pitches fall on deaf ears. You can blame your customer service representatives for low satisfaction scores, but if customer data is missing, then no wonder the complaint resolution pipeline is backed up. Think it’s your customer resource management (CRM) system? Think again. It’s bad data, and it’s costing you millions. Request your copy of The Bottom Line on Bad Customer Data that delivers detailed advice from Jill Dyche, partner and co-founder of Baseline Consulting, about what you can do to address the impact of bad data on your company. The report gives you insight into how bad data is impacting your company and what you can do about it. How to identify where the bad data is and quantify its impact, and different approaches to determine the sources and causes of bad data are all offered in this paper.

Abstract: Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you.

Abstract: Want to really frighten someone? Invite the poor soul to a meeting titled “Marketing Integration Planning.” Because when marketers hear “integration” they imagine the goal is total, perfect integration, and lose heart—not realizing smaller victories can be achieved along the way with big payoffs. Demystify integration: discover what’s really achievable based on the needs and capabilities of your company and suppliers.

Abstract: Small and medium businesses (SMB) generally purchase integration solutions that conform to plans of their larger business partners. Their decisions are reactive, rather than proactive. Understanding the SMB market can help integration solution providers better understand SMB needs. This white paper addresses integration in the SMB market in two parts: the first deals with understanding the nature of the SMB market; the second deals with what SMB integration solutions should address.

Abstract: Data integration is a key enabler for supply chain modernization. Competition is driving increased integration of the supply chain, both due to direct cost pressures and to increased globalization. There can be little doubt that well implemented supply chain integration saves labor costs and improves inventory control. This has often been a complex and costly proposition. Standards, improved products and a common understanding of best practices for distributed systems are reducing the price of entry to supply chain automation. This will, in turn drive broader integration of manufacturing and distribution endpoints.

Abstract: There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.

Abstract: Data auditing is a form of data protection involving detailed monitoring of how stored enterprise data is accessed, and by whom. Data auditing can help companies capture activities that impact critical data assets, build a non-repudiable audit trail, and establish data forensics over time. Learn what you should look for in a data auditing solution—and use our checklist of product requirements to make the right decision.

Abstract: Siebel Systems is incorporating Informatica’s data integration platform into Siebel eBusiness Analytics 2000.3. The vendors hope to use the integrated product to consolidate data into a 'comprehensive e-business data warehouse'. Have the vendors found the e-business holy grail?

Abstract: Informatica Corporation, long an established vendor in the Extract/Transform/Load (ETL) market space, has morphed themselves into a vendor of solutions for the