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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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 analysis services 2005 data


How Bar Codes Can Optimize Data Recording and Information Analysis
Bar code technology allows users to analyze information to develop more accurate maintenance, personnel, and financial planning. In particular it can hasten the

analysis services 2005 data  Data Recording and Information Analysis Introduction Traditionally, bar code technology is used in product distribution, courier services, and point of sales (POS). However, it can also be particularly useful in maintenance processes, though its application in some industries, such as aerospace is not as well known, especially in Mexico and Latin America. In order to better understand the application of bar code technology in maintenance processes, we must first understand that it is a form of automatic

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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.

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

CRM for Financial and Insurance Markets

Customer relationship management (CRM) focuses on the retention of customers by collecting data from all customer interactions with a company from all access points (by phone, mail, or Web, or in the field). The company can then use this data for specific business purposes by taking a customer-centric rather than a product-centric approach. CRM applications are front-end tools designed to facilitate the capture, consolidation, analysis, and enterprise-wide dissemination of data from existing and potential customers. This process occurs throughout the marketing, sales, and service stages, with the objective of better understanding one’s customers and anticipating their interest in an enterprise’s products or services.  

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Documents related to » analysis services 2005 data

Business Intelligence for SMBs: MBS Excel Applications and Competitive Analysis


Companies relying on an Excel or Excel-like system need to know that, while Excel might suffice for ad hoc analysis and data storage for individuals or small groups, the technological flaw of data and referential integrity prevents it from a corporate-wide, collaborative effort like planning and budgeting, not to mention product development and sourcing.

analysis services 2005 data  for business intelligence. Competitive Analysis Many believe that Microsoft ventured into the reporting sector of the broader BI market when it first unveiled Microsoft SQL Server Reporting Services in 2003, which has since forced competitors, such as Business Objects , former Crystal , and Cognos to make defensive moves. As a result, many renowned enterprise-level analytic and reporting vendors, such as Actuate, Business Objects, MicroStrategy, OutlookSoft , or ProClarity provide Excel add-in products, Read More

Server Platform Situational Analysis: IBM AS/400


Customers value IBM's AS/400's reliability, stability, and security. However, despite its impressive performance and use of independent software vendors to broaden its functionality, AS/400 suffers from the perception that its an ancient technology.

analysis services 2005 data  Analysis: IBM AS/400 Situational Analysis As outlined in The Blessing and Curse of Rejuvenating Legacy Systems , every independent software vendor (ISV) finds itself in a difficult position in terms of catering to existing and prospective customers. Existing customers seek updates in incremental and manageable sizes which will not disrupt current information technology (IT) processes. Potential customers want feature rich solutions that are rapidly implemented. For instance, customers typically want to Read More

Reporting Value of IT Services with Balanced Scorecards


A balanced scorecard is a measurement system for management that provides real insight into the status of a business or some part of it. Developed by Kaplan and Norton in the early 1990s, balanced scorecards provide a control system that helps ensure the right balance between different, and often times conflicting, perspectives. For example, an insurance company may increase profitability by offering incentives to claims assessors for taking a tough stance on payout, but will soon find dissatisfaction among its clients that may lead to lost business. Scorecards help ensure this balance and are an improvement over more traditional single dimension approaches that tend to be based purely on expense management and business growth.

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The Truth about Data Mining


It is now imperative that businesses be prudent. With rising volumes of data, traditional analytical techniques may not be able to discover valuable data. Consequently, data mining technology becomes important. Here is a framework to help understand the data mining process.

analysis services 2005 data  first tier. Advanced data analysis through predictive modeling and forecasting defines this tier—in other words, data mining. Data mining has a significantly broad reach and application. It can be applied in any situation where it is necessary to discover potential knowledge from vast amounts of data. Throughout this article, the word knowledge is used to refer to meaningful patterns derived through techniques in data mining that can stimulate an organization's goals (such as company revenue, Web site 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 of the existing legacy systems (which are often incorrect). Other unique Metagenix approaches include an "open book" policy, which includes publishing product price lists on their web site and complete access to company officials, including CEO and President Greg Leman. According to Mr. Leman, "we’re pathologically honest".

analysis services 2005 data  which provides profiling and analysis, transformation mapping, repository maintenance, reports, DDL and XML generation in a one client/one server license arrangement on Windows NT/2000 for $25,000 per year which competes directly with Evoke Axio on a feature-for-feature basis. Prior to the release of these products, the only solution was custom coding by in-house IT staff, an expensive and laborious task. Many IT shops still argue that they can do it better than an off-the-shelf solution, but IT Read More

Six Steps to Manage Data Quality with SQL Server Integration Services


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.

analysis services 2005 data  Improvement , Data Quality Analysis , Data Quality Articles , Data Quality Assessment , Data Quality Indicator , Data Quality Indicators , Data Quality Business Intelligence , Data Quality Initiatives , Data Quality Issues , Data Quality Management , Data Quality Measurement , Data Quality Measures , Data Quality Methodology , Data Quality Methods , Data Quality Metrics , Data Quality Model , Data Quality Objectives , Data Quality Plan , Data Quality Problems , Data Quality Process , Data Quality 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.

analysis services 2005 data  four broad fields: Multi-dimensional Analysis Tools: Tools that allow the user to look at the data from a number of different angles . These tools often use a multi-dimensional database referred to as a cube . Query tools: Tools that allow the user to issue SQL (Structured Query Language) queries against the warehouse and get a result set back. Data Mining Tools: Tools that automatically search for patterns in data. These tools are usually driven by complex statistical formulas. The easiest way to Read More

Big Data Comes of Age: Shifting to a Real-time Data Platform


New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support big data and the real-time needs of innovative companies.

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Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever


Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility.

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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.

analysis services 2005 data   Read More

Data Quality Trends and Adoption


While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers.

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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.

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Re-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 agile architectures that can confront the new challenges much easier.

analysis services 2005 data  BI, business intelligence, operational intelligence, Hadoop, NoSQL, self-service BI, data virtualization, big data, on-demand data integration, lean data integration, JBoss Data Virtualization Read More

Understanding the PCI Data Security Standard


The payment card industry data security standard (PCI DSS) defines a comprehensive set of requirements to enhance and enforce payment account data security in a proactive rather than passive way. These include security management, policies, procedures, network architectures, software design, and other protective measures. Get a better understanding of the PCC DSS and learn the costs and benefits of compliance.

analysis services 2005 data  the PCI Data Security Standard MessageLabs Hosted Web Security and Content Filtering service operates at the Internet level, intercepting viruses, and spyware. Source : MessageLabs | Now part of Symantec Resources Related to Understanding the PCI Data Security Standard : Payment Card Industry Data Security Standard (PCI DSS) (Wikipedia) Understanding the PCI Data Security Standard Data Security is also known as : Data Security Architecture , Data Security Articles , Data Security Audit , Read More