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Software Functionality Revealed in Detail
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 data governance methodology


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

data governance methodology  Path to Healthy Data Governance This article is based on the presentation, “From Data Quality to Data Governance,” by Jorge García, given at ComputerWorld Technology Insights in Toronto, Canada, on October 4, 2011. Modern organizations recognize that data volumes are increasing. More importantly, they have come to realize that the complexity of processing this data has also grown in exponential ways, and it’s still growing. Many companies are finally treating their data with all the necessary

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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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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.

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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.

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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.

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Lean IT Governance: The Most Realistic and Attainable Approach to IT Governance


The most realistic and attainable approach to IT governance is a "lean" approach via project portfolio management (PPM). The lean approach requires a light footprint life cycle, rapid implementation of proven practices, and centralized data. It is based on simplicity and achievability, building on what works while establishing headroom for continuous improvement.

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Streaming Data and the Fast Data Stack


Big data is data at rest; fast data is streaming data, or data in motion. A stack is emerging across verticals and industries for building applications that process these high velocity streams of data. This new stack, the fast data stack, has a unique purpose: to grab real-time data and output recommendations, decisions, and analyses in milliseconds.

This white paper will look at the emerging fast data stack through the lens of streaming data to provide architects, CTOs, and developers with fundamental architectural elements of the new fast data stack: a LAMP stack for streaming data applications.

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The Fast Path to Big Data


Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

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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.

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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.

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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.

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Data Storage in the Cloud--Can You Afford Not To?


In Data Storage in the Cloud Can You Afford Not To?

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