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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 owb

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 owb

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 owb  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 Read More

Data, Data Everywhere: A Special Report on Managing Information


The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and extract useful information, is harder still. Even so, this data deluge has great potential for good—as long as consumers, companies, and governments make the right choices about when to restrict the flow of data, and when to encourage it. Find out more.

data warehouse process owb  Data Everywhere: A Special Report on Managing Information SAP NetWeaver Master Data Management (SAP NetWeaver MDM) is an enabling foundation for enterprise services and business process management. Working across heterogeneous systems at disparate locations, SAP NetWeaver Master Data Management ensures cross-system data consistency through interactive distribution. Source: SAP Resources Related to Data, Data Everywhere: A Special Report on Managing Information : Data (Wikipedia) Data, Data 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 owb  Data: The Importance of Data Quality in Business Intelligence Originally Published - October 20, 2008 The zeal to get as much business data to the user as soon as possible often prevails over the establishment of processes that control the quality of data. Low data quality standards can lead to bad business decisions and missed 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 Read More

Ask the Experts Question: Do Organizations Really Need a Physical Data Warehouse Structure?


We recently had a question from one of our readers (through our Ask the Experts page) discussing QlikView’s approach to data collection. Reader’s Question “QlikView says its innovative way of collecting data and not needing a physical data warehouse (DW) structure is the right thing to do in DW/business intelligence (BI) solutions. Can one expect to build a sustainable / scalable corporate

data warehouse process owb  Really Need a Physical Data Warehouse Structure? We recently had a question from one of our readers (through our Ask the Experts page) discussing QlikView’s approach to data collection. Reader’s Question “QlikView says its innovative way of collecting data and not needing a physical data warehouse (DW) structure is the right thing to do in DW/business intelligence (BI) solutions. Can one expect to build a sustainable / scalable corporate data warehouse through such an approach?” TEC Analyst Read More

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 owb  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

The Advantages of Row- and Rack-oriented Cooling Architectures for Data Centers


The traditional room-oriented approach to data center cooling has limitations in next-generation data centers. Next-generation data centers must adapt to changing requirements, support high and variable power density, and reduce power consumption and other operating costs. Find out how row- and rack-oriented cooling architectures reduce total cost of ownership (TCO), and address the needs of next-generations data centers.

data warehouse process owb  Rack-oriented Cooling Architectures for Data Centers The Advantages of Row and Rack-Oriented Cooling Architectures for Data Centers If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. In today''s always on, always available world where businesses can''t stop and downtime is measured in dollars, American Power Conversion (APC) provides protection against some of the leading causes of downtime, data loss and hardware damage: power problems 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 owb  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

Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security


Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace.

data warehouse process owb  Best Practices in Application Data Security Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace. Read More

Scalable Data Quality: A Seven-step Plan for Any Size Organization


Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor data quality isn’t an option—implementing a thorough data quality solution is key to your success. Find out how.

data warehouse process owb  Data Quality: A Seven-step Plan for Any Size Organization Melissa Data’s Data Quality Suite operates like a data quality firewall – instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer Read More

Reinventing Data Masking: Secure Data Across Application Landscapes: On Premise, Offsite and in the Cloud


Be it personal customer details or confidential internal analytic information, ensuring the protection of your organization’s sensitive data inside and outside of production environments is crucial. Multiple copies of data and constant transmission of sensitive information stream back and forth across your organization. As information shifts between software development, testing, analysis, and reporting departments, a large "surface area of risk" is created. This area of risk increases even more when sensitive information is sent into public or hybrid clouds. Traditional data masking methods protect information, but don’t have the capability to respond to different application updates. Traditional masking also affects analysis as sensitive data isn’t usually used in these processes. This means that analytics are often performed with artificially generated data, which can yield inaccurate results.

In this white paper, read a comprehensive overview of Delphix Agile Masking, a new security solution that goes far beyond the limitations of traditional masking solutions. Learn how Delphix Agile Masking can reduce your organization’s surface area risk by 90%. By using patented data masking methods, Delphix Agile Masking secures data across all application lifecycle environments, providing a dynamic masking solution for production systems and persistent masking in non-production environments. Delphix’s Virtual Data Platform eliminates distribution challenges through their virtual data delivery system, meaning your data can be remotely synchronized, consolidated, and takes up less space overall. Read detailed scenarios on how Delphix Agile Data Masking can benefit your data security with end-to-end masking, selective masking, and dynamic masking.

data warehouse process owb  Data Masking: Secure Data Across Application Landscapes: On Premise, Offsite and in the Cloud Be it personal customer details or confidential internal analytic information, ensuring the protection of your organization’s sensitive data inside and outside of production environments is crucial. Multiple copies of data and constant transmission of sensitive information stream back and forth across your organization. As information shifts between software development, testing, analysis, and 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 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 accurate data tools and systems in place to efficiently carry out their daily tasks. Data generation development, data quality, document and content management, and data security management are all examples of data-related functions that provide information in a logical and precise manner.

data warehouse process owb  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

Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise


While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help.

data warehouse process owb  Best Practices: Managing Sensitive Data in the Enterprise While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help. Read More

Data Quality: Cost or Profit?


Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and company policies that set expectations and establish data management procedures, we will explore applications and tools that help reduce the negative impact of poor data quality. Some CRM application providers like Interface Software have definitely taken data quality seriously and are contributing to solving some data quality issues.

data warehouse process owb  number of articles about data quality. ( Poor Data Quality Means A Waste of Money ; The Hidden Role of Data Quality in E-Commerce Success ; and, Continuous Data Quality Management: The Cornerstone of Zero-Latency Business Analytics .) This time our focus takes us to the specific domain of data quality within the customer relationship management (CRM) arena and how applications such as Interaction from Interface Software can help reduce the negative impact that poor data quality has on a CRM objective. CRM Read More

Data Visualization: When Data Speaks Business


For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages of IBM Cognos Business Intelligence for improving the data visualization and data delivery process.

data warehouse process owb  Visualization: When Data Speaks Business For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages Read More

Next-generation Data Auditing for Data Breach Protection and Risk Mitigation


Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation. Stolen laptops, hacking, exposed e-mail, insider theft, and other causes of data loss can plague your company. How can you detect (and respond!) to breaches and protect your data center? Learn about the functions and benefits of an automated data auditing system.

data warehouse process owb  generation Data Auditing for Data Breach Protection and Risk Mitigation Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation. Stolen laptops, hacking, exposed e-mail, insider theft, and other causes of data loss can plague your company. How can you detect (and respond!) to breaches and protect your data center? Learn about the functions and benefits of an automated data auditing system. Read More