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Contextual Workflow Modeling
Activity-based workflow modeling (AWM) is a common and useful modeling technique, whose fundamental drawbacks limit its effectiveness in modeling complex

data modeling tutorial  enterprise resources via standard data communication channels. Source : Macronetics Resources Related to Contextual Workflow Modeling : Workflow (Wikipedia) Contextual Workflow Modeling Data Environment is also known as : Data Environment Command , Data Environment Designer , Data Environment Instance , Data Environment Tutorial , Data Environment Variable , Data Environmental , Data Guard Environment , Data Intensive Computing Environment , Data Intensive Cyber Environments , Data Management Read More...
Recruitment and Staffing
Recruitment and Staffing functionality allows the user to select and hire the right people with the right skill sets, as well as track the information regarding their recruitment for later analysis...
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Documents related to » data modeling tutorial


SAP HANA-One Technology to Watch in 2012 (and Beyond)
Did you know that SAP HANA is much more than a high-speed analytic appliance? TEC principal analyst P.J. Jakovljevic reveals how HANA is a universal database

data modeling tutorial  of record and master data repository”, i.e., a general-purpose database of the future? For that reason, I initially confused HANA with SAP’s offerings that were touted by Hasso Plattner (SAP’s renowned co-founder and the current chairman of the supervisory board of SAP AG) a few years back. I am talking here about SAP BusinessObjects (BO) Explorer and SAP Business Warehouse (BW) Accelerator (see the related blog post series from 2009 ). Well, now I know that SAP BO Explorer is a tool for creating Read More...
Energy Innovator Implements a New Business Model with mySAP
Capstone Turbine Corporation, an energy innovator, needed to implement management, business model, and strategy changes. It also needed to improve product

data modeling tutorial  the portal into financial data and critical operational events. “We are now beginning to see the native controls inherent in mySAP Business Suite,” he says. SAP EP and SAP BI are indeed having a personal impact on executives and managers. “They can, through the cockpit, get a quick sense of what’s going on. And if they see something that pops out at them, they can drill down to understand what’s happening and take action,” says Pfaffinger. “For example, during a training session where we Read More...
Best Practices for a Data Warehouse on Oracle Database 11g
Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW

data modeling tutorial  are embedded in the data model itself rather than the data. This in part at least, this is what makes navigation of the model so straightforward for end users. There is often much discussion regarding the ‘best’ modeling approach to take for any given Data Warehouse with each style, classic 3NF or dimensional having their own strengths and weaknesses. It is likely that Next Generation Data Warehouses will need to do more to embrace the benefits of each model type rather than rely on just one - this Read More...
Computerized Maintenance Management Systems: A Tutorial Part One: Challenges and Features
Companies are looking for more areas to squeeze savings out of operations. One such area that may be fertile ground to explore is equipment maintenance. The

data modeling tutorial  materials. Through this automated data collection mechanism, we are creating a equipment history database that will form the basis for performance analysis. A CMMS should provide the tools to perform this analysis and be able to answer the question, How has our maintenance organization and equipment been performing? Some of the canned reports that should be available from a CMMS are: Equipment Utilization Equipment Downtime Equipment Mean Time Between Failure (MTBF) Equipment Mean Time To Repair (MTTR) Read More...
Unified Data Management: A Collaboration of Data Disciplines and Business Strategies
In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration

data modeling tutorial  Data Management: A Collaboration of Data Disciplines and Business Strategies In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts. Read More...
Metagenix Reverse Engineers Data Into Information
Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than depending on the data dictionaries

data modeling tutorial  Reverse Engineers Data Into Information Metagenix Reverse Engineers Data Into Information M. Reed - February 15, 2001 Event Summary Metagenix, Inc. has designed its flagship product, MetaRecon to, as they put it, Decipher Your Data Genome . The product reverse engineers all of the metadata ( data about data ) from data sources and generates information that is very helpful to developers in designing specifications for a new data store, and assists greatly in preparing for cleansing and Read More...
Tailoring SAP Data Management for Companies of All Sizes
The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are

data modeling tutorial  SAP Data Management for Companies of All Sizes The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are relying on manual operations, which are inherently error-prone, and time- and resource-intensive. Today's environment requires enterprise-class automation to overcome these challenges of data management. Learn about one solution that can help improve SAP data management. Read More...
Data Management Wish List: IT Is Open to Big Changes
Data management, access, and analysis haven’t always received the same amount of consideration, or respect, as the corporate applications that generate and

data modeling tutorial  Open to Big Changes Data management, access, and analysis haven’t always received the same amount of consideration, or respect, as the corporate applications that generate and consume the data. In recent years, however, information technology (IT) leaders have focused much more attention on their organizations’ data management platforms and capabilities. Download this white paper to get a better picture of the current data management landscape. Read More...
2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry

data modeling tutorial  Big Data Opportunities Survey While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unisphere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses Read More...
Governance from the Ground Up: Launching Your Data Governance Initiative
Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing

data modeling tutorial  Ground Up: Launching Your Data Governance Initiative Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing from philosophical questioning to hard-core tactics for data governance initiatives. This paper describes the components of data governance that will inform the right strategy and give companies a way to determine where and how to begin their data governance journeys. Read More...
Data Management and Analysis
From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it

data modeling tutorial  perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As). For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most Read More...
ESG - Riverbed Whitewater: Optimizing Data Protection to the Cloud
Riverbed Whitewater leverages WAN optimization technology to provide a complete data protection service to the cloud. The appliance-based solution is designed

data modeling tutorial  - Riverbed Whitewater: Optimizing Data Protection to the Cloud Riverbed Whitewater leverages WAN optimization technology to provide a complete data protection service to the cloud. The appliance-based solution is designed to integrate seamlessly with existing backup technologies and cloud storage provider APIs. Read this ESG Lab report on hands-on testing of the Riverbed Whitewater appliance for ease of use, cost-effective recoverability, data assurance, and performance and scalability. Read More...
Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations
While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as

data modeling tutorial  Data Analytics: Profiling the Use of Analytical Platforms in User Organizations While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as organizations seek to store and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers. This report examines the rise of big data and the use of analytics to mine that data. Read More...

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