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Software Functionality Revealed in Detail
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 why data governance


The Path to Healthy Data Governance through Data Security
Companies today are challenged to maintain their data safe and secure from hackers and others with unauthorized access. In his article, TEC business

why data governance  to the right user. Why Is Data Security Important? Data is a valuable asset to an organization—for both corporate and individual purposes. And having the proper methods to maintain information secure at all times can have huge impact on the organization’s well being. This is particularly relevant when dealing with personally identifiable information (PII) as well as sensitive corporate data. From a corporate perspective, there are three main drivers for ensuring data security becomes a core component

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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.

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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 » why data governance

Why and How Outsourcing Management and Governance is Critical to Outsourcing Success


Organizations undertaking information technology and business process outsourcing typically are very focused on "doing the deal." This involves assessing service providers, determining geographies from which to source services, developing contracts, defining service levels, and a myriad of other tasks. Yet arguably the hardest part of outsourcing occurs only after the deal is done—performing ongoing outsourcing management and governance.

why data governance  like? The Details   Why Outsourcing Mamagement and Governance? Outsourcing management and governance (OM/G) is all about preserving and enabling the ...intent of an outsourcing effort, the reason an organization chooses to outsource selected processes. The overarching objective of the outsourcing effort often is to reduce costs while also enabling process improvement and transformation. The intent of the deal impacts everything from the structure of the contract, to the type of client-service provider Read More

The Challenges of Defining and Managing Governance, Risk Management, and Compliance


A broader, more structured approach is needed to effectively manage governance, risk management, and compliance (GRC). Enterprises will then be better able to guide their people, standardize their processes, and unify technology to embed GRC at all organizational levels.

why data governance  said than done. So why might a holistic approach to GRC be difficult to achieve? As discussed in SAP Solutions for Governance, Risk, and Compliance , much of the value creation and innovation within companies takes place as a consequence of the intricate relationships between people, processes, and systems—all of which are, as a rule, patchy across different organizations, functions, and geographies. This fragmentation can hold any enterprise back in a number of ways: Organizational fragmentation Read More

A Road Map to Data Migration Success


Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project teams encounter some very specific management and technical challenges. Minimizing the risk of these tricky migrations requires effective planning and scoping. Read up on the issues unique to data migration projects, and find out how to best approach them.

why data governance  NEEDS Business needs represent why you are migrating data. How many new applications go live but do not deliver the business value expected? You must articulate the business needs that are driving your project. In addition to ensuring that you are meeting the needs of the consumer, you are also controlling the scope of a data migration project, especially source systems analysis and mapping. At first glance, this may seem obvious, but consider as an example the full functionality of a customer Read More

Creating a Winning Data Transmission Service


Today’s data transmission departments are battling for budget and relevance. Moving files and ensuring delivery is getting tougher every day. To successfully deliver data to an increasing number of target platforms and meet rising customer expectations, leading companies are adopting service-oriented architectures (SOAs) and upgrading their file transfer departments into data transmission services. Find out more.

why data governance  control. And the reasons why are clear. Different FTP products across numerous platforms create a complex operating environment. It s not only unwieldy, but it s next to impossible to gain visibility into the huge number of files traversing the organization. FTP activity can typically only be determined by using rudimentary tools to view individual log files that contain a significant amount of noise. If you want true enterprise management of FTP, you ve got to have a central access point to manage the Read More

Data Quality Strategy: A Step-by-Step Approach


To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.

why data governance  Quality Strategy: A Step-by-Step Approach To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality. Read More

Data Management and Business Performance: Part 1-Data


Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a business intelligence (BI) solution. Two topics resounded: the use of BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of

why data governance  for this unanimous perspective? Why is data management still an issue? Turning data into valuable information has never been more important, as organizations today must be extremely cautious when managing information—its movement, analysis, presentation, and security—owing to local as well as global legal and economic considerations (new law regulations, new business models, etc.). Technologies and frameworks like the data mart and the data warehouse are addressing some of the back-end information Read More

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 to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.

why data governance  had several questions including: Why is data important now, it has been around forever? There aren't enough internal resources but how could outsiders/ contractors possible know their data well enough to cleanse it? How would you even know where to start? This article addresses how we all got here and what we can do about it. There are four critical success factors of 1) Scope, 2) Team, 3) Process and 4) Technology and this article will give you the stepping stones to be successful in cleaning your 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.

why data governance  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. Read More

Linked Enterprise Data: Data at the heart of the company


The data silos of today's business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, break down data walls, provide an open, secure, and long-term technological environment, and reduce complexity—read this white paper to find out how.

why data governance  Enterprise Data: Data at the heart of the company The data silos of today's business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, Read More

Governance from the Ground Up: Launching Your Data Governance Initiative


Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing from philosophical questioning to hard-core tactics for data governance initiatives. This paper describes the components of data governance that will inform the right strategy and give companies a way to determine where and how to begin their data governance journeys.

why data governance  from the Ground Up: Launching Your Data Governance Initiative Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing from philosophical questioning to hard-core tactics for data governance initiatives. This paper describes the components of data governance that will inform the right strategy and give companies a way to determine where and how to begin their data governance journeys. 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.

why data governance  - 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 as DASD (Direct Access Storage Device) were extremely expensive on a Read More

Data Masking: Strengthening Data Privacy and Security


Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you.

why data governance  Masking: Strengthening Data Privacy and Security Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you. Read More

Types of Prefabricated Modular Data Centers


Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and compares their key attributes, and provides a framework for choosing the best approach(es) based on business requirements.

why data governance  of Prefabricated Modular Data Centers Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and Read More

Tailoring SAP Data Management for Companies of All Sizes


The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are relying on manual operations, which are inherently error-prone, and time- and resource-intensive. Today's environment requires enterprise-class automation to overcome these challenges of data management. Learn about one solution that can help improve SAP data management.

why data governance  SAP Data Management for Companies of All Sizes The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are relying on manual operations, which are inherently error-prone, and time- and resource-intensive. Today's environment requires enterprise-class automation to overcome these challenges of data management. Learn about one solution that can help improve SAP data management. Read More