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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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Visit the TEC store to compare leading software solutions by funtionality, so that you can make accurate and informed software purchasing decisions.
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 term data warehouse lists olap

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

Discrete 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, and human resources). Many systems include, with varying degrees of acceptance and skill, solutions that were formerly considered peripheral such as product data management (PDM), warehouse management, manufacturing execution system (MES), and reporting. 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 foundation of any ERP implementation must be a proper exercise of aligning customers'' IT technology with their business strategies, and subsequent software selection. 

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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.

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Why don’t the Potential Benefits of Spend Analysis Come Easily?




term data warehouse lists olap  UI with some key terms listed on each Web page, which users may want to link together (such as categories and commodities), and then the search engine finds all similarities, patterns, and trends in the data once users search on (or select) that term. And there have been successful spend analysis implementations by Endeca. For example, Euroffice , the UK''s largest online supplier of stationery and office supplies has been using Endeca to find out, e.g., all customers that have three times (and more) Read More

The Lexicon of CRM - Part 2: From J to Q


C.R.M. itself is an acronym, standing for Customer Relationship Management. This is part two of a three-part article to provide explanation and meaning for most of the common CRM phraseology. Here, in alphabetical order, we continue the Lexicon of CRM.

term data warehouse lists olap  Management . A new term that covers the area of field force automation and remote access to corporate information in real time. Such access is becoming more and more critical as economies move towards the service sector, and there are more people in the field working at client company sites who need access to corporate data. Metadata - Metadata is data about data. It''s often used when talking about XML (eXtensible Markup Language). In XML, two pieces of information are sent for one piece of data: one Read More

Contemporary Business Intelligence Tools


Tools under the business intelligence (BI) umbrella combine to convert data into information, and information into decisions for action. Dashboards and scorecards are two such tools. Though often confused, they have functional difference, especially in modern BI suites.

term data warehouse lists olap  BI is an umbrella term that denotes a combination of technologies and architectures. Some important BI tools that allow the storage, access, and analysis of data in data warehouses (DWs) and data marts include executive information systems (EIS), extract/transform/load (ETL) tools, reporting, query and analysis tools, data visualization, balanced scorecards, dashboard, on-line transaction processing (OLTP), on-line analytic processing (OLAP), data mining, and alerting and notification systems. It also Read More

What’s New in Microsoft SQL Server 2000


SQL Server 2000, the next major release of SQL Server 7, is Microsoft’s SQL 7 release of its database both re-architected and re-written. Microsoft has high hopes for the latest version in a market that was worth $8 Billion in 1999, an 18% increase over 1998. What remains to be seen is whether it will attract customers not already using SQL Server.

term data warehouse lists olap  Distributed Internet Architecture: Microsoft''s term (originally invented for Windows NT) to describe the components that make up its enterprise network architecture built into Windows 2000. It includes software that collectively provides a Web-enabled infrastructure for an organization. ActiveX: A software module based on Microsoft''s Component Object Model (COM) architecture. It enables a program to add functionality by calling ready-made components that blend in and appear as normal parts of the Read More

Developing a Universal Approach to Cleansing Customer and Product Data


Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.

term data warehouse lists olap  quality is a vague term that means different things to different people. Before data quality problems can be discussed in detail, data quality must be defined more precisely. What Is Data Quality? A useful definition of quality can be found in the ISO 8402 specification, which defines quality as, The totality of characteristics of an entity that bear on its ability to satisfy stated or implied needs. If we apply this definition to data, then it means that data quality is dependent not only the Read More

Considerations for Owning versus Outsourcing Data Center Physical Infrastructure


When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life expectancy, regulatory requirements, and other strategic factors. This paper discusses how to assess these key factors to help make a sound decision.

term data warehouse lists olap  for Owning versus Outsourcing Data Center Physical Infrastructure When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, Read More

Achieving a Successful Data Migration


The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

term data warehouse lists olap  Migration Professional Resource , Term Data Migration , Data Migration Pro , Data Migration Manager , Data Migration Steps , Data Migration Process , Data Migration Testing , Data Migration Plan , Migration Information Source , Transfers Database Schemas , Data Migration Techniques , Data Integration Server , Data Migration Importing Images , New Data Migration Manager , Data File Conversion , Database and Application Migration , Practical Data Migration , Database Migration Database Conversion , Data Read More

Demystifying Data Science as a Service (DaaS)


With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white paper to find out more about how data SaaS is set to become a vital part of business intelligence and analytics, and how India will play a role in this trend.

term data warehouse lists olap  Data Science as a Service (DaaS) With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white pa Read More

Don't Be Overwhelmed by Big Data


Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Data can be a Big Deal - read this white paper for some useful tips on ensuring secure, quality data acquisition and management.

term data warehouse lists olap  t Be Overwhelmed by Big Data Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Read More

The New Virtual Data Centre


Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward.

term data warehouse lists olap  New Virtual Data Centre Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward. Read More

How Companies Use Data for Competitive Advantage


Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage.

term data warehouse lists olap  Companies Use Data for Competitive Advantage How Companies Use Data for Competitive Advantage Today, many businesses find they are under siege dealing with an explosion of data. Yet the best performing companies are mastering their data—and using it for competitive advantage. How are they able to accomplish this? What best practices, approaches, and technologies are they employing? Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage . In this Economist Business Read More

Data Blending for Dummies


Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant.

Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data providers, department data stores, in-house databases, and more, and become faster at delivering better information and results to their organizations. In the past, the challenge for data analysts has been accessing this data and cleansing and preparing the data for analysis. The access, cleansing, and preparing data stages are complex and time intensive. These days, however, software tools can help reduce the burden of data preparation, and turn data blending into an asset.

Read this e-book to understand why data blending is important, and learn how combining data means that you can get answers to your business questions and better meet your business needs. Also learn how to identify what features to look for in data blending software solutions, and how to successfully deploy these tools within your business. Data Blending for Dummies breaks the subject down into digestible sections, from understanding data blending to using data blending in the real world. Read on to discover how data blending can help your organization use its data sources to the utmost.

term data warehouse lists olap  Blending for Dummies Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant. Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data 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.

term data warehouse lists olap  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 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.

term data warehouse lists olap  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. Read More