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Documents related to » bi tools reviews data


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 TOOLS REVIEWS DATA: Data Quality Tool | BI Data Quality Tools | BI Ensure Data Quality | BI Enterprise Data Quality | BI Examining Data Quality | BI Good Data Quality | BI Highest Data Quality | BI Improving Data Quality | BI Measure Data Quality | BI Online Data Quality | Business Data Quality BI | 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 Quali
9/9/2009 2:32:00 PM

Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g for Data Warehousing and Business Intelligence. Find RFP Templates and Other Solutions to Define Your Project In Relation To Oracle Database, Data Warehousing and Business Intelligence. Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

BI TOOLS REVIEWS DATA: replicating entire stacks of BI technologies is signifcant. Oracle Database provides a completely different approach. Oracle has implemented OLAP, Data Mining, and statistics inside of it database engine. Instead of moving data from a data warehouse to other analytic engines for further analysis, Oracle has instead brought the advanced analytic algorithms into its database, where the data resides. Moreover, Oracle provides SQL access to all of its analytics, so that they can be implemented with any
4/20/2009 3:11:00 PM

Achieving a Successful Data Migration
Achieving a Successful Data Migration. Solutions and Other Software to Delineate Your System and for 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.

BI TOOLS REVIEWS DATA: Costs with Lean Techniques Mobile Applications for Human Resources: The Future Is Here! ERP Implementation Best Practices: Manufacturers and the SaaS Delivery Model Achieving a Successful Data Migration If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Informatica s data migration solution decreases the risk and minimizes the errors inherent in data migration projects. At the same time, our solution reduces the costs of data migration
10/27/2006 4:30:00 PM

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 TOOLS REVIEWS 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. Data Quality: A Survival Guide for Marketing style= border-width:0px; />   comments powered by Disqus Related Topics:   Customer Relationship Management (CRM),   Marketing Automation,   Direct Marketing,   Enterprise Marketing Management
6/1/2009 5:02:00 PM

How to Comply with Data Security Regulations
The best-kept secrets of Data Security secrets revealed!Get and read our whitepaper for free! A remote data backup solution can be compliant with almost any international, federal, or state data protection regulation—and can be compliant with the common caveats of most data security laws by providing functionality like data encryption and secure media control. And, as some regulations require files to be archived for several years, you can create a routine that archives files you select for backup and storage.

BI TOOLS REVIEWS DATA: Data Security Regulations Source: BizDomainStore.com Document Type: Checklist/Guide Description: A remote data backup solution can be compliant with almost any international, federal, or state data protection regulation—and can be compliant with the common caveats of most data security laws by providing functionality like data encryption and secure media control. And, as some regulations require files to be archived for several years, you can create a routine that archives files you select for backup
7/13/2009 2:16:00 PM

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.

BI TOOLS REVIEWS DATA: Right Now 6 Reasons Big Data Requires Rethinking Your Middleware Big Data, Mobility, and Green IT: Innovations for Manufacturers and Distributors 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 Investment (ROI) |  Software as a Service (SaaS) |  Total Cost of Ownership (TCO)
2/3/2011 8:58:00 AM

More Data is Going to the Cleaners
WESTBORO, Mass., November 29, 1999 - Ardent Software, Inc. (Nasdaq: ARDT) today announced a strategic partnership with Firstlogic, Inc., the developer of i.d.Centric data quality software that helps companies cleanse and consolidate data in database marketing, data warehousing, and e-business applications. Under the partnership agreement Firstlogic will develop and support a link between its customer data quality tools and Ardent's DataStage Suite.

BI TOOLS REVIEWS DATA: extensive matching and consolidation capabilities inside the DataStage suite, the most comprehensive Business Intelligence (BI) Infrastructure solution available. As data has become increasingly strategic to corporate growth, monitoring and maintaining the highest level of data quality are essential, said Art Petty, Firstlogic vice president of marketing. Our customer data cleansing and matching tools work with Ardent s DataStage Quality Assurance solutions to provide powerful, complete data quality
12/1/1999

Customer Data Integration: A Primer
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a customer relationship management initiative can help provide organizations with a successful framework to manage data on a continuous basis.

BI TOOLS REVIEWS DATA: system. Since customers drive profitability, organizations need a way to provide their employees with a single view of the customer and to provide that customer with above-average customer service. Unfortunately, this is not always the case. Disparate applications such as billing and call center systems do not always feed into one another, and even when they do, lack of data cleansing and management can cause employees to see only a portion of a customer s history, interactions, or profiles. A widely
9/11/2009

Data Storage in the Cloud—Can you Afford Not To?
Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or avoided by using the cloud for backup and archive storage.

BI TOOLS REVIEWS DATA: 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)
7/12/2011 2:19:00 PM

Data Center Automation
With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands.

BI TOOLS REVIEWS DATA: must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands. Data Center Automation style= border-width:0px; />   comments powered by Disqus Related Topics:   Asset Management,   Enterprise Asset Management,   IT Asset Management (ITAM),   Application Development,   Data Cleansing,   Conversion,   or Modeling,   Business Intelligence and Data Management,  
10/30/2007 6:19:00 PM

The Why of Data Collection
Data collection systems work; however, they require a investment in technology. Before the investment can be justified, we need to understand why a data collection system may be preferable to people with clipboards.

BI TOOLS REVIEWS DATA: data collection systems is visibility. Simply put, we want to know more, and know it sooner. The right information, which is accurate, and made available at the right time is one definition of visibility. Accuracy Errors happen. For example, the Grocer Manufacturers Association (GMA) reported that 36% of all orders have errors. At minimum, this means that one line item had the wrong quantity or even the wrong product shipped. These errors happen because people are people. People will continue to misread
11/3/2005


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