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Four Critical Success Factors to Cleansing Data
Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment

data discrepancies  in the process. Dirty data manifests itself in many different anomalies, below are just a few: Discrepancies in the structure of the data items and specified format Irregularities Integrity constraint violations Contradictions Duplicates Invalid Missing values (part or whole records) Orphaned data Examples of data anomalies: Multiple addresses for IBM Same addresses for IBM 10005 Park Lane 10005 Park LN 1005 Park Lane Multiple ways to identify a vendor...Is it Coca Cola, Cocacola, CocaCola - Uppercase, Read More
Outsourcing, IT Infrastructure
The IT Infrastructure Outsourcing knowledge base focuses on the selection of companies who provide outsource services in the areas of information technology (IT) infrastructure. The typical type...
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Documents related to » data discrepancies


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

data discrepancies  result of having clean data ready for publication to other operational systems. CLEAN DATA….CHECK OUT THE BENEFITS! Customer Service Reduce the number of calls related to order or invoice discrepancies Save your salespeople’s time resolving disputes or communicating basic product information to customers Reduce time spent by customer service reps regarding basic product information Reduce the number of web site email questions regarding product data Enhance your customers’ service with timely and Read More
Project Costing for Maximum Profitability
By implementing timekeeping solutions for costing, organizations obtain valuable insight into project profitability. Project-oriented timekeeping data is also

data discrepancies  may still be gathering data from the last project. Automating Reduces Errors by 75% According to the Gartner Group, fully automating the timesheet process reduces errors and staff time by 75 percent or more. Automation technologies and practices reduce improper time tracking activities and associated costs by validating project/cost code lists and monitoring approval processes electronically. Additional savings are realized by eliminating paper costs, and policy and regulatory compliance is improved. Read More
Supplier Logistics Management (SLM) Part 2
Supplier Logistics Management (SLM) offers the opportunity for considerable improvement in efficiency as well as cost reductions. SLM enables companies and

data discrepancies  per year through incorrect data flows between suppliers and retailers (1) . Additionally, when European consumer goods and food retailers lost more than $17 billion in inventory last year, they could only explain about 41% of these losses (2) . Results like this point to the strategic advantage supply chain executives can obtain by focusing on improving their fragmented and complex supplier logistics networks. Through improved supplier logistics management, supply chain executives can provide senior Read More
AspenTech Releases AspenONE V8.5
AspenTech, a leading provider of software and services to the process industries, releases version 8.5 of aspenONE® manufacturing and supply chain software.

data discrepancies  Analytics for Plant Operations Data — aspenONE Process Explorer translates data collected by the Aspen InfoPlus.21 data historian into actionable operational insight, providing a better understanding of production, quality, and equipment availability via new capabilities for overall equipment effectiveness (OEE). Integrated Dock and Refinery Scheduling — Aspen Petroleum Scheduler allows customers to minimize losses from demurrage, re-blending, and product downgrades by providing the ability to Read More
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

data discrepancies  Data Integration: A Primer Originally published - August 22, 2006 Introduction Implementing a customer data management system can be the difference between success and failure in terms of leveraging an organization's customer relationship management (CRM) 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. Read More
2012 Business Data Loss Survey results
This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download

data discrepancies  Business Data Loss Survey results This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now. 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

data discrepancies  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
How to Comply with Data Security Regulations
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

data discrepancies  to Comply with Data Security Regulations BizDomainStore.com's Remote Data Backups is the most cost effective, secure, and convenient way to automatically back up your mission critical data Source: BizDomainStore.com Resources Related to How to Comply with Data Security Regulations : Data Security (Wikipedia) How to Comply with Data Security Regulations Data security is also known as : Remote Data , Federal Data , State Data , Most Data , Mirrored Data , Financial Data , Client Data , Enterprise Data Read More
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,

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

data discrepancies  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
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

data discrepancies  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
2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry

data discrepancies  Big Data Opportunities Survey While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unisphere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses 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

data discrepancies  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 Read More
The Teradata Database and the Intelligent Expansion of the Data Warehouse
In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role

data discrepancies  Intelligent Expansion of the Data Warehouse In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now. Teradata mixes rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives. In this report TEC Senior BI analyst Jorge Garcia looks at the Teradata Read More

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