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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.
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 data governance program


How To Launch a Data Governance Program: Practical Guidelines for Technology Implementers
To derive maximum value from your data, you need a strong data governance program that helps develop and manage data as a strategic business asset. The success

data governance program  To Launch a Data Governance Program: Practical Guidelines for Technology Implementers To derive maximum value from your data, you need a strong data governance program that helps develop and manage data as a strategic business asset. The success of a data governance program thus hinges upon a robust data integration technology infrastructure. Developing the right technology infrastructure is critical to your ability to automate, manage, and scale your data governance program.

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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 program

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 intelligence (BI) analyst Jorge García looks the risks and issues that companies face with securing their data, the importance and advantages of data security, and outlines a path that companies can follow to achieve data security as part of an overall data governance initiative.

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How Midsize Businesses Can Reduce Costs, Secure Data, and Ensure Compliance with an Identity Management Program


A strong identity management platform plays dual roles: gatekeeper and guardian of business intelligence (BI) and data. Midsize businesses can’t operate effectively without the ability to control access to their networks and business systems. And, many midsize companies must report on this information for compliance purposes. Learn about the factors driving midsize companies toward stronger identity management systems.

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The Path to Healthy Data Governance


Many companies are finally treating their data with all the necessary data quality processes, but they also need to align their data with a more complex corporate view. A framework of policies concerning its management and usage will help exploit the data’s usefulness. TEC research analyst Jorge Garcia explains why for a data governance initiative to be successful, it must be understood as a key business driver, not merely a technological enhancement.

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Data Governance: Controlling Your Organization’s Mission-critical Information


Controlling your company’s key information through data governance is more than just good practice—it can make the difference between success and failure at meeting compliance requirements and at arming your organization with a competitive edge.

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Transactional Data: Driving Real-Time Business


A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more.

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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.

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Data Visualization: When Data Speaks Business


For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages of IBM Cognos Business Intelligence for improving the data visualization and data delivery process.

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Making Big Data Actionable: How Data Visualization and Other Tools Change the Game


To make big data actionable and profitable, firms must find ways to leverage their data. One option is to adopt powerful visualization tools. Through visualization, organizations can find and communicate new insights more easily. Learn how to make big data more actionable by using compelling data visualization tools and techniques.

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Master Data Management and Accurate Data Matching


Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process.

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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.

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