Abstract: Integrated enterprise resource planning software normalizes the reporting requirements for a mining company’s various departments. This article loosely shows the parallels between the operations in a mining company and those of a manufacturer whose product is sold on store shelves.

Abstract: It is now imperative that businesses be prudent. With rising volumes of data, traditional analytical techniques may not be able to discover valuable data. Consequently, data mining technology becomes important. Here is a framework to help understand the data mining process.

Abstract: Microsoft released a new version of OLE DB (Object Linking and Embedding Database, based on Microsoft’s Component Object Model or COM) which supports a proprietary data mining specification. It is purported to extend the Structured Query Language (SQL) to allow easier and faster incorporation of data mining queries into existing data warehouse solutions.

Abstract: Data mining has emerged from obscure beginnings in artificial intelligence to become a viable and increasingly popular tool for putting data to work. Data mining is a set of techniques for automating the exploration of data and uncovering hidden truths.

Abstract: Mine evaluation studies, including those that support mine water management or environmental compliance, are rife with challenges. The biggest: to quantitatively evaluate alternative approaches for completing projects, and to identify and manage associated risks. Models must be accurate, and yet still take uncertainty into account. Learn how a simulation tool can you help forecast the behavior of complex mining systems.

Abstract: Software vendors and users often view advanced data visualization and dashboard capabilities as the “sizzle” that helps sell the product. This over-simplification misses the key point that ADV delivers the “steak” (i.e., the relevant information) users need to make accurate assessments that optimize business results. Discover how ADV and dashboards can help you keep your company focused on its core mission.

Abstract: Achieving operational excellence is fundamental for Yanacocha, the largest gold producer in South America. In 1999, Yanacocha decided it needed an online system linking its principal management areas (operations, maintenance, logistics, finance, and human resources), in order to optimize efficiency in administering its assets. It turned to Mincom Ellipse as its corporate management system, allowing standardization of its operations worldwide.

Abstract: SAS Institute has applied its data mining technology to the Internet. The company released products that will help companies analyze and predict the behavior of Web surfers. The target customer is one with large volumes of enterprise data that come from a variety of sources.

Abstract: As one of the world’s leading manufacturers of construction and mining equipment, Komatsu has enjoyed significant growth. In fact, 2004 marked the best business performance in the company’s history. Now the company is focused on accelerating product development by making better, faster decisions throughout the product lifecycle. The solution: PTC’s ProductView.

Abstract: Business performance management (BPM) includes setting key performance indicators, using data mining to discover data patterns and using software to help drive business decisions and develop corporate strategy. For an organization, there are many benefits to implementing a BPM solution.

Abstract: PEMCO Corporation, a manufacturer of high quality mining products for multinational original equipment manufacturers (OEMs), realized increased on-time delivery performance and reduced customer service costs while preventing product shortages through just-in-time material availability. The improved quality of information and improved flow of product through the plant has even resulted in revamped employee morale and job satisfaction.

Abstract: Orezone strikes gold with Microsoft Business Solutions - Great Plains. Orezone is a Canadian mining company that needed a more efficient means to track and store data sent from its African mines to its Canadian offices. Learn how it used MBS Great Plains to boost efficiency.

Abstract: Conventional business intelligence (BI) tools are often not available to decision makers and are typically designed for use by trained business analysts. Learn about software-as-a-service (SaaS) BI tools designed to help non-IT people who struggle with the task of mining Microsoft Excel spreadsheets and other unstructured data sources to make sales forecasts, plan for resource utilization, or service customer accounts.

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: 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: 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: 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.