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Software Functionality Revealed in Detail
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 data governance models


Lean IT Governance: The Most Realistic and Attainable Approach to IT Governance
The most realistic and attainable approach to IT governance is a

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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

Recruitment and Staffing

Recruitment and Staffing functionality allows the user to select and hire the right people with the right skill sets, as well as track the information regarding their recruitment for later analysis. It covers criteria such as Organization Structures and Modeling, Corporate Branding, Sourcing, Applicant Tracking, Assessment and Selection, Governance and Compliance, Vendor Management Systems (VMS) Portal, Recruitment Analytics and Reporting, and Product Technology. 

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Documents related to » data governance models

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.

data governance models  has well-defined and simple data structures, has simple keys and governance rules, is often standardized (U.S. state codes, for example), involves only a few applications, and is reasonably stable. Master business entity data, such as customer and product, on the other hand, is usually ill-defined, has complex data structures and relationships, requires compound and intelligent keys and complex governance rules, is not usually standardized, involves many applications, and changes frequently. Does this Read More

IT Governance and Project Portfolio Management: Vendor Delivers a Phase-based Approach


Although most vendors provide organizations with the project portfolio management tools to meet their objectives, few provide strategies to implement an IT governance framework successfully. Pacific Edge offers a three-stage approach to implementing IT governance, based on an organization's maturity.

data governance models  the exchange of granular data between active projects and its solution provides executives with a clear picture of their project investments. In addition, the Mariner solution delivers help desk capabilities to track work that is both project- and non-project-related. This is achieved with its pre-packaged Mariner Connectors , which link to various IT services applications (such as HP OpenView Service Desk and HP Service Center ). Furthermore, its core strength lies in managing resources, while Read More

Data Center Projects: Project Management


In data center design projects, flawed management frequently leads to delays, expense, and frustration. Effective project management requires well-defined responsibilities for every manager, tight coordination among suppliers, well-defined procedures for managing change, and consistent terminology. Learn how enforcing these requirements can help your company achieve an efficient process with a predictable outcome.

data governance models  Data Center Floor | Data Center Infrastructure | Project Plan | Project Template | Project Management | Project Planning | Project Software | Project Risk | Project Process | Project Risk Management | Project Evaluation | Project Construction | Project Development | Change Management | Project Management Governance | Process Management | Project Management Strategy | Project Management Methodology | Project Management Software | Project Management Process | Project Management Steps | Project Management Read More

The Data Warehouse Institute (TDWI) Conference in San Diego: The Agile Approach to Business Intelligence (BI)


Next month a TDWI World Conference will be taking place in San Diego, California. What’s so special about this conference anyway? The answer is simple:  the general topic is going to be “Creating an Agile BI Environment”. Progressively in the last four or five years, the agile software development methodology has been jumping from the software development area to the data warehouse

data governance models  look for: •    “ Data Governance for BI Professionals ” given by Jill Dyché, co-author of the book: “ Customer Data Integration: Reaching a Single Version of the Truth ” and Kimberly Nevala, senior consultant in Master Data Management (MDM). •      MDM for Practitioners: Deploying Your MDM Solution and MDM for Practitioners: Developing Your MDM Plan given by Evan Levy You can check the complete list of events on the 2010 TDWI World Conference in San Diego . {democracy:45} I also Read More

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.

data governance models  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. 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.

data governance models  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

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.

data governance models  Definition of Data Warehousing Biographical Information Bill Inmon Bill Inmon is universally recognized as the father of the data warehouse. He has over 26 years of database technology management experience and data warehouse design expertise, and has published 36 books and more than 350 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing data warehouses and has been a keynote speaker for every major computing 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.

data governance models  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

Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security


Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace.

data governance models  Best Practices in Application Data Security Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace. Read More

Data Enrichment and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics


Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident decisions and take the right actions, you need more than just software—you also need the right data. This white paper discusses a solution to help ensure that your applications process reliable data so that your spend analyses and supplier risk assessments are accurate, trustworthy, and complete.

data governance models  and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident decisions and take the right actions, you need more than just software—you also need the right data. This white paper discusses a solution to help ensure that your applications process reliable data so that your spend analyses and supplier risk assessments are Read More

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.

data governance models  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. Read More

The Necessity of Data Warehousing


An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

data governance models  Necessity of Data Warehousing The Necessity of Data Warehousing M. Reed - August 2, 2000 Why the market is necessary Data warehousing is an integral part of the information age . Corporations have long known that some of the keys to their future success could be gleaned from their existing data, both current and historical. Until approximately 1990, many factors made it difficult, if not impossible, to extract this data and turn it into useful information. Some examples: Data storage peripherals such Read More

ESG - Riverbed Whitewater: Optimizing Data Protection to the Cloud


Riverbed Whitewater leverages WAN optimization technology to provide a complete data protection service to the cloud. The appliance-based solution is designed to integrate seamlessly with existing backup technologies and cloud storage provider APIs. Read this ESG Lab report on hands-on testing of the Riverbed Whitewater appliance for ease of use, cost-effective recoverability, data assurance, and performance and scalability.

data governance models  - Riverbed Whitewater: Optimizing Data Protection to the Cloud Riverbed Whitewater leverages WAN optimization technology to provide a complete data protection service to the cloud. The appliance-based solution is designed to integrate seamlessly with existing backup technologies and cloud storage provider APIs. Read this ESG Lab report on hands-on testing of the Riverbed Whitewater appliance for ease of use, cost-effective recoverability, data assurance, and performance and scalability. Read More

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.

data governance models  Margin over Continously Cleansed Data Optimizing Gross Margin over Continously Cleansed Data If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Advanced functionality to manage costs, sell prices, promotions, discounts, chargebacks, and other key attributes while optimizing gross profits. Source : epaCUBE Resources Related to Optimizing Gross Margin over Continously Cleansed Data : Data cleansing (Wikipedia) Gross margin (Wikipedia) Read More