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Software Functionality Revealed in Detail
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 data governance benefits


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

data governance benefits  Path to Healthy Data Governance through Data Security The appropriate handling of an organization’s data is critically dependent on a number of factors, including data quality, which I covered in one of my earlier posts this year. Another important aspect of data governance regards the managing of data from a security perspective. Now more than ever, securing information is crucial for any organization. This article is devoted to providing insight and outlining the steps that will put you on the path

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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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Documents related to » data governance benefits

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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Establishing Enterprise Architecture Governance


This article discusses the issues around implementing architecture governance, and what constitutes viable approaches to establishing effective governance processes.

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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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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.

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Data Management Wish List: IT Is Open to Big Changes


Data management, access, and analysis haven’t always received the same amount of consideration, or respect, as the corporate applications that generate and consume the data. In recent years, however, information technology (IT) leaders have focused much more attention on their organizations’ data management platforms and capabilities. Download this white paper to get a better picture of the current data management landscape.

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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 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 and a discussion of the results.

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Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Read this white paper to learn about a lean form of on-demand data integration technology called data virtualization. Deploying data virtualization results in business intelligence (BI) systems with simpler and more agile architectures that can confront the new challenges much more easily.

All the key concepts of data virtualization are described, including logical tables, importing data sources, data security, caching, and query optimization. Examples are given of application areas of data virtualization for BI, such as virtual data marts, big data analytics, extended data warehouse, and offloading cold data.

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Achieving a Successful Data Migration


The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

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Data Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox


Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data warehouse.

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