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Documents related to » bi data mart


Six Steps to Manage Data Quality with SQL Server Integration Services
Six Steps to Manage Data Quality with SQL Server Integration Services. Read IT Reports Associated with Data quality. 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.

BI DATA MART: Customer Data Quality | BI Data Quality | BI Data Quality Analysis | BI Data Quality Articles | BI Data Quality Assessment | BI Data Quality Business Intelligence | BI Data Quality Center | BI Data Quality Control | BI Data Quality Improvement | BI Data Quality Indicator | BI Data Quality Indicators | BI Data Quality Initiatives | BI Data Quality Issues | BI Data Quality Management | BI Data Quality Measurement | BI Data Quality Measures | BI Data Quality Methodology | BI Data Quality Methods | BI Data
9/9/2009 2:32:00 PM

Optimizing Gross Margin over Continously Cleansed Data
Optimizing Gross Margin over Continously Cleansed Data.Reports and Other Software System to Use In Your System for Optimizing Gross Margin over Continously Cleansed Data. Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards are automated data cleansing, systematic management of data processes, and margin optimization. Real dollars can be reclaimed in the supply chain by making certain that every byte of product information is accurate and synchronized, internally and externally.

BI DATA MART: 33% had failed to bill or collect receivables 20% had failed to meet a contractual or service level commitment Price Waterhouse Coopers “Addressing Data Quality”, IDEA February 8, 2006 You pay the wrong price. Cost increases and decreases are not correct in your back office system. Often your customer pricing system is based on a calculation involving costs. Margins can be misstated and additional costs are incurred to correct your system or the supplier invoices, and then reconcile financial
6/20/2006 9:23:00 AM

Data Quality: A Survival Guide for Marketing
Data Quality: a Survival Guide for Marketing. Find Free Blueprint and Other Solutions to Define Your Project In Relation To Data Quality. The success of direct marketing, measured in terms of qualified leads that generate sales, depends on accurately identifying prospects. Ensuring data accuracy and data quality can be a big challenge if you have up to 10 million prospect records in your customer relationship management (CRM) system. How can you ensure you select the right prospects? Find out how an enterprise information management (EIM) system can help.

BI DATA MART: of addresses (site location, billing address, and corporate headquarters) but only one address record per account. In order to capture all three addresses, the CRM analysts were duplicating account records. What they needed to do was extend their data model to hold three separate address records for each account, which impacted the data model of the new system being built. Had it not assessed its data beforehand, the manufacturer would not have discovered this problem until after the initial migration.
6/1/2009 5:02:00 PM

Developing a Universal Approach to Cleansing Customer and Product Data
Developing a Universal Approach to Cleansing Customer and Product Data. Find Free Proposal and Other Solutions to Define Your Acquisition In Relation 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.

BI DATA MART: Data Cleanse Summary About BI Research About Business Objects Data Quality: What’s The Problem? Data quality has always been an important issue for companies, and this is even more the case today. Business and legislative pressures coupled with the explosion in the amount of data created by organizations is leading to increased corporate attention on improving the quality and accuracy of business data. This paper reviews current industry problems concerning data quality, and takes a detailed look at
6/1/2009 5:10:00 PM

Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond
For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet the business impact can be significant and detrimental to business continuity when proper data management is not applied. By embracing the five phases of a data migration management methodology outlined in this paper, you can deliver a new system with quality data.

BI DATA MART: Costs with Lean Techniques Mobile Applications for Human Resources: The Future Is Here! ERP Implementation Best Practices: Manufacturers and the SaaS Delivery Model Three Keys to Better Data-driven Decisions: What You Should Know... Right Now Acronym-Related White Papers: Business Intelligence (BI) |  Customer Relationship Management (CRM) |  Enterprise Resource Planning (ERP) |  Human Capital Management (HCM) |  Information Technology (IT) |  Key Performance Indicators (KPIs) |  Return on
3/21/2011 11:21:00 AM

Data Quality: A Survival Guide for Marketing
Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge, particularly when you have thousands or even millions of prospect records in your CRM system and you are trying to target the right prospect. Data quality, data integration, and other functions of enterprise information management (EIM) are crucial to this endeavor. Read more.

BI DATA MART: White Papers: Business Intelligence (BI) |  Customer Relationship Management (CRM) |  Enterprise Resource Planning (ERP) |  Human Capital Management (HCM) |  Information Technology (IT) |  Key Performance Indicators (KPIs) |  Return on Investment (ROI) |  Software as a Service (SaaS) |  Total Cost of Ownership (TCO)
3/16/2011 1:15:00 PM

The Modern Virtualized Data Center
Data center resources are often underused while drawing enormous amounts of power and taking up valuable floor space. Virtualization has been a positive evolutionary step in the data center, driving consolidation of resources to maximize power saving and to simplify management and maintenance. Learn more about the benefits of virtualization, and the issues you need to consider when planning a consolidation project.

BI DATA MART: White Papers: Business Intelligence (BI) |  Customer Relationship Management (CRM) |  Enterprise Resource Planning (ERP) |  Human Capital Management (HCM) |  Information Technology (IT) |  Key Performance Indicators (KPIs) |  Return on Investment (ROI) |  Software as a Service (SaaS) |  Total Cost of Ownership (TCO)
8/15/2008 2:38:00 PM

Microsoft says OLE for Data Mining: Is it Bull?
Microsoft released a new version of OLE DB (Object Linking and Embedding Database, based on Microsoft’s Component Object Model or COM) which supports a proprietary data mining specification. It is purported to extend the Structured Query Language (SQL) to allow easier and faster incorporation of data mining queries into existing data warehouse solutions.

BI DATA MART: data mining tools and capabilities into line-of-business and e-commerce applications. A dozen leading data mining and business intelligence vendors announced their support for the new protocol, which will enable diverse data mining products to more easily exchange data and results and allow developers to more easily incorporate data mining technology into existing data warehousing solutions. Supporting vendors include ANGOSS Software Corp., Appsource Corp., Comshare Inc., DB Miner Technology Inc., Knosys
3/28/2000

Data Discovery Applications » The TEC Blog
our buyer’s guide for BI and data management, coming this October.) Data discovery applications can bring many benefits to an organization, enabling dynamic and versatile analysis of data, but to successfully meet the data analysis needs of your organization those applications need to be considered with the same rigor as you would employ in acquiring and implementing any other type of enterprise software. What do you think? Are you using one of these products or some other data discovery tool? Are you

BI DATA MART: analytics, bi, Business Intelligence, Cognos Insight, data discovery, data discovery applications, endeca, Inetsoft, Lyza, PowerPivot, QlikView, style intelligence, Tableau, TIBCO spotfire, visual intelligence, webfocus visual discovery, TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
17-08-2012

Meeting the Challenges of Product Traceability with Automated Data Collection
With a minimum of effort, learn all about Meeting the Challenges of Product Traceability with Automated Data Collection.Download our Free whitepaper and find the Software Information You're Looking for. An effective traceability system involves determining which product and manufacturing process attributes to collect and maintain—and deciding when during the manufacturing process to begin collecting those attributes. Do you begin with raw material attributes from the supplier, at inspection, at assembly, at shipping? Explore the many facets of meeting product traceability challenges using automated data collection.

BI DATA MART: the Challenges of Product Traceability with Automated Data Collection Meeting the Challenges of Product Traceability with Automated Data Collection Source: Radley Corporation Document Type: White Paper Description: An effective traceability system involves determining which product and manufacturing process attributes to collect and maintain—and deciding when during the manufacturing process to begin collecting those attributes. Do you begin with raw material attributes from the supplier, at
7/21/2009 12:59:00 PM

Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence
Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting requirements. This paper discusses the importance of data integration and helps you identify key challenges of integrating data. It also provides an overview of data warehousing and its variations, as well as summarizes the benefits and approaches to integrating data.

BI DATA MART: White Paper Description: Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting requirements. This paper discusses the importance of data integration and helps you identify key challenges of integrating data. It also provides an overview of data warehousing and its variations, as well as summarizes the benefits and approaches to integrating data. Data Integration: Creating a Trustworthy Data Foundation for
3/22/2011 10:17:00 AM


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