Documents » case study of college system using data flow diagram.
Abstract: You have convinced upper management that
flow manufacturing will enable your company to leapfrog the competition. You have appointed a
flow process leader, and selected a line for your
flow pilot. Now it’s time to physically perform your first line implementation. The big question is, what exactly do you need to do to make the transition from discrete to
flow?
PubDate: 11/29/2006 1:41:00 PM
Abstract: Rhodes College, with about 1,700 students and a large support staff, wanted to optimize use of campus facilities to address a community need for meeting rooms. A single resource calendar was needed to merge curriculum schedules with other meetings and events. Discover how a schedule managing solution helped the college organize meetings from various departments and offices—and reduce overhead with a self-service tool.
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: The Nova Scotia Community College (NSCC) implemented Business Objects to create a financial reporting system that would run in real time, as opposed to taking weeks to generate reports. However, the NSCC environment presented its own unique set of challenges.
Abstract: While lean/flow leverages practices to stay ahead of actual demand, traditional approaches better coordinate secondary, back-office systems like accounting and HR. Moreover, flow should be a company-wide strategy that impacts more than manufacturing.
Abstract: Lean execution strategies within enterprises and across supply chains can dramatically reduce cycle times, improve quality, reduce waste, and improve bottom lines. In other words, lean is more than an advantage: it is a competitive necessity. Oracle’s Flow Manufacturing module capabilities in lean execution can enable the transition from a discrete, push-based manufacturing environment to a flow, pull-based one.
Abstract: Today’s critical cash-flow and liquidity concerns are demanding executive-level attention. Turmoil in the financial markets is leaving many companies struggling to ensure the cash flow and liquidity needed for normal operations. Learn about software solutions that can help your company protect its commercial cash flows, improve visibility into sources and uses of cash, and increase control over global cash balances.
Abstract: Lewis and Clark Community College in Illinois (US) was having a number of technology problems in its classrooms, leading to student attention issues. After installing a new software solution, teachers can now share their screens with students, provide remote assistance to students from a central console, and monitor classroom screens to ensure students are on task. Find out more about this workstation management solution.
Abstract: The desire to be environmentally responsible—and save money—led Howard Community College (HCC) to green its campus. Seeing that there was room for savings in its computing technology, HCC searched for an energy management solution that would make workstations available when system resources are required, while conserving power during productivity downtimes. Learn how the solution HCC chose offered energy savings and more.
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: 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: 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: Companies are fighting a constant battle to integrate business data and content while managing data quality. Data quality serves as the foundation for business intelligence (BI), enterprise resource planning (ERP), and customer relationship management (CRM) projects. Learn more about software that unifies leading data quality and integration solutions—helping your organization to move, transform, and improve its data.
Abstract: Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.
Abstract: Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources. But where does log data fit in? Historically, log data was reported on through slow legacy applications. But with today’s log data warehouse solutions, data is centralized, allowing users to analyze and report on it with unparalleled speed and efficiency.