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Software Functionality Revealed in Detail
We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.
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 data warehouse process etl

Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

Compare Now

Process Manufacturing (ERP)

The simplified definition of enterprise resource planning (ERP) software is a set of applications that automate finance and human resources departments and help manufacturers handle jobs such as order processing and production scheduling. ERP began as a term used to describe a sophisticated and integrated software system used for manufacturing. In its simplest sense, ERP systems create interactive environments designed to help companies manage and analyze the business processes associated with manufacturing goods, such as inventory control, order taking, accounting, and much more. Although this basic definition still holds true for ERP systems, today its definition is expanding. Today's leading ERP systems group all traditional company management functions (finance, sales, manufacturing, human resources) and include, with varying degrees of acceptance and skill, many solutions that were formerly considered peripheral (product data management (PDM), warehouse management, manufacturing execution system (MES), reporting, etc.). While during the last few years the functional perimeter of ERP systems began an expansion into its adjacent markets, such as supply chain management (SCM), customer relationship management (CRM), business intelligence/data warehousing, and e-Business, the focus of this knowledge base is mainly on the traditional ERP realms of finance, materials planning, and human resources. The old adage is "Such a beginning, such an end", and, consequently, many ERP systems' failures could be traced back to a bad software selection. The foundation of any ERP implementation must be a proper exercise of aligning customers' IT technology with their business strategy, and subsequent software selection. This is the perfect time to create the business case and energize the entire organization towards the vision sharing and a buy in, both being the Key Success Factors (KSFs). Yet, these steps are very often neglected despite the amount of expert literature and articles that emphasize their importance.    

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Documents related to » data warehouse process etl

The Evolution of a Real-time Data Warehouse


Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine if your organization needs this type of IT solution.

data warehouse process etl  Evolution of a Real-time Data Warehouse The Evolution of a Real-time Data Warehouse Jorge Garcia - December 23, 2009 Understanding Real-time Systems Today, real time computing is everywhere, from customer information control systems (CICSs) to real-time data warehouse systems. Real-time systems have the ability to respond to user actions in a very short period of time. This computing behavior gives real-time systems special features such as instant interaction: users request information from the system Read More

A Definition of Data Warehousing


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.

data warehouse process etl  technology management experience and data warehouse design expertise, and has published 36 books and more than 350 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing data warehouses and has been a keynote speaker for every major computing association. Before founding Pine Cone Systems, Bill was a co-founder of Prism Solutions, Inc. Ralph Kimball Ralph Kimball was co-inventor of the Xerox Star workstation, the first 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 performs and scales well, you need to get three things right: the hardware configuration, the data model, and the data loading process. Learn how designing these three things correctly can help you scale your EDW without constantly tuning or tweaking the system.

data warehouse process etl  Practices for a Data Warehouse on Oracle Database 11g Best Practices for a Data Warehouse on Oracle Database 11g If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Oracle has been helping customers like you manage your business systems and information with reliable, secure, and integrated technologies. Source : Oracle Resources Related to Data Warehouse : Data Warehouse (Wikipedia) Best Practices for a Data Warehouse on Oracle Database Read More

The Necessity of Data Warehousing


An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

data warehouse process etl  of products for a data warehouse effort is complex. The first and most important issue is to ensure that the Extract/Transform/Load tool that is chosen can effectively and efficiently extract the source data from all the required systems. The selection of the ETL tool requires an understanding of the source data feeds. The following issues should be considered: Many warehouses are built from legacy systems that may be difficult to access from the computer network. ETL tools often do not reside on the Read More

Distilling Data: The Importance of Data Quality in Business Intelligence


As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.

data warehouse process etl  opportunities. Even with a data warehouse that is well designed and equipped with the best tools for business intelligence (BI), users will encounter inefficiency and frustration if the quality of data is compromised. When embarking on a data warehousing or business intelligence project, it is essential for organizations to emphasize the quality of data that is used for analysis and subsequent decision making. As data captured from a multitude of sources makes its way to an enterprise data warehouse or Read More

The Fast Path to Big Data


Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

data warehouse process etl  Fast Path to Big Data Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise Read More

Data Pro Accounting Software


Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the corporation has always been to develop and market a full line of accounting software products for a wide range of market segments, on a broad spectrum of operating systems environments such as DOS, Windows and UNIX.

data warehouse process etl  Pro Accounting Software Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the corporation has always been to develop and market a full line of accounting software products for a wide range of market segments, on a broad spectrum of operating systems environments such as DOS, Windows and UNIX. Read More

New Data Protection Strategies


One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets.

data warehouse process etl  Data Protection Strategies One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets. Read More

Business Process Management in Free and Open Source: An Overview of the Demand and the Supply


Free and open source software (FOSS) has become a hot topic in the business process management (BPM) market. This article discusses the relevance between BPM and FOSS, and makes suggestions for BPM seekers that prefer FOSS.

data warehouse process etl  Technology Evaluation Centers'' (TEC) data on demand trends to explore the stats of end-user demand for FOSS BPM solutions as well as users''  requirements for deploying BPM solutions (be it FOSS or proprietary) in a FOSS environment. For the supply side, my findings are not as quantitative but still suggest that some vendors are addressing BPM users’ requirements in FOSS. The Demand Side Every year, thousands of users come to TEC’s BPM Evaluation Center looking for suitable BPM solutions. By answering Read More

Warehouse Advantage


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Meeting Process Manufacturing Challenges Through More Potent Functionality


The process manufacturing market remains one of the most competitive and dynamic segments of manufacturing. Process manufacturers must evolve to meet the challenges of changing market demands, the increasing commoditization of products, and the volatility of pricing in energy and raw materials.

A powerful enterprise resource planning (ERP) system with detailed functionality should help process manufacturers manage active ingredients throughout their operations by enabling them to buy raw materials and cost goods more precisely; scale formulas up or down, automatically; track lot inheritance; and define product sequencing, which is evaluated based on multiple characteristics, to reduce downtime and changeover costs in the production schedule.

data warehouse process etl  process manufacturing challenges, process ERP, Microsoft Dynamics AX 2012 R2, ERP for process manufacturers, complex process manufacturing, process manufacturing functionality Read More

Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Read this white paper to learn about a lean form of on-demand data integration technology called data virtualization. Deploying data virtualization results in business intelligence (BI) systems with simpler and more agile architectures that can confront the new challenges much more easily.

All the key concepts of data virtualization are described, including logical tables, importing data sources, data security, caching, and query optimization. Examples are given of application areas of data virtualization for BI, such as virtual data marts, big data analytics, extended data warehouse, and offloading cold data.

data warehouse process etl  think Data Integration: Delivering Agile BI Systems with Data Virtualization Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more Read More

Product Life Cycle Management (PLM) in Process Part 1 Proven in Discrete, Ready to Blossom in Process


Process industry companies could benefit from many of the PLM concepts that have accrued to discrete industries. But PLM has had minimum penetration into the process industries. Why?

data warehouse process etl  Design (CAD) and Product Data Management (PDM). Proven Value - But What About the Process Industries? Searching for users and reviewing the available case studies shows that few experiences are available that reflect the PLM value available to process companies. Some of the case studies that focus on process companies show the PLM products used to enable packaging design or plant engineering but few include the development of the basic recipes for products. The development of a food, chemical, Read More

Top 10 Evaluation Criteria for Copy Data Management & Data Virtualization


Data virtualization is becoming more important, as industry-leading companies learn that it delivers accelerated IT projects at a reduced cost. With such a dynamic space, one must make sure that vendors will deliver on their promises. This white paper outlines 5 qualification questions to ask before and during the proof of concept (POC), and 5 things to test during the POC.

data warehouse process etl  Evaluation Criteria for Copy Data Management & Data Virtualization Data virtualization is becoming more important, as industry-leading companies learn that it delivers accelerated IT projects at a reduced cost. With such a dynamic space, one must make sure that vendors will deliver on their promises. This white paper outlines 5 qualification questions to ask before and during the proof of concept (POC), and 5 things to test during the POC. Read More

Streaming Data and the Fast Data Stack


Big data is data at rest; fast data is streaming data, or data in motion. A stack is emerging across verticals and industries for building applications that process these high velocity streams of data. This new stack, the fast data stack, has a unique purpose: to grab real-time data and output recommendations, decisions, and analyses in milliseconds.

This white paper will look at the emerging fast data stack through the lens of streaming data to provide architects, CTOs, and developers with fundamental architectural elements of the new fast data stack: a LAMP stack for streaming data applications.

data warehouse process etl  Data and the Fast Data Stack Big data is data at rest; fast data is streaming data, or data in motion. A stack is emerging across verticals and industries for building applications that process these high velocity streams of data. This new stack, the fast data stack, has a unique purpose: to grab real-time data and output recommendations, decisions, and analyses in milliseconds. This white paper will look at the emerging fast data stack through the lens of streaming data to provide architects, Read More