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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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 google data center


Data, Data Everywhere: A Special Report on Managing Information
The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and

google data center  sites are entirely free. Google and an IBM website called Many Eyes let people upload their data to display in novel ways and share with others. Some data sets are best represented as a moving image. As print publications move to e-readers, animated infographics will eventually become standard. The software Gapminder elegantly displays four dynamic variables at once. Displaying information can make a difference by enabling people to understand complex matters and find creative solutions. Valdis Krebs, 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

Outsourcing, IT Infrastructure

The IT Infrastructure Outsourcing knowledge base focuses on the selection of companies who provide outsource services in the areas of information technology (IT) infrastructure. The typical types of activities that these providers perform include data center operations; network operations; backup/recovery services, data storage management services; system administration services; end user support of desktop PCs, laptops, and handheld devices; web site, or application hosting, etc.  

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Documents related to » google data center

APICS 2009 Convention: Day 4 (Last Day)


The last day of the conference is different in three ways: there is no general session today; we have plant tours in the afternoon; and the exhibitors are gone (which is too bad, because for IBM only you could spend hours talking with all the vendors in their booth). As usual, we had a hard time choosing which learning session to attend. Gabriel wanted to learn more about sustainable

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InfiniteKM: Knowledge Management for Sales Channels and Contact Centers


InfiniteKM, a cloud (and on-premise)-based sales and service enablement platform, helps organizations’ sales channels and contact centers run smoothly and optimally. The platform has been developed by Infinite Media, and has evolved over the 15 years of experience the vendor has amassed working with some of the best-known brands in the world, such as Xerox, GE Mabe, ScotiaBank, John Hancock

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Red Hat Heads for the Cloud with OpenShift


It would be an understatement to say that Red Hat is an interesting enterprise software company. Since its founding in 1994 and initial public offering (IPO) in 1999, the vendor has focused on businesses and divisions thereof that embrace open-source computing tools. In 2001, Red Hat introduced Enterprise Linux, a “frozen” mature version of Linux whose support and maintenance the vendor could

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Salesforce.com Expands into SAP’s Turf


Salesforce.com dreams of becoming a $1 billion software company, in Germany. The vendor is forging partnerships, expanding its territory, and fostering innovation.

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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 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.

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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.

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Enterprise Data Management: Migration without Migraines


Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an understanding of the entire ERP data lifecycle combined with industry-specific experience, knowledge, and skills to drive the process through the required steps accurately, efficiently, and in the right order. Read this white paper to learn more.

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Fundamentals of Managing the Data Center Life Cycle for Owners


Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and available over the course of its life span. For each phase of the data center’s life cycle, proper care and action must be taken to continuously meet the business needs of the facility. This paper describes the five phases of the data center life cycle, identifies key tasks and pitfalls, and offers practical advice to facility owners and management.

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Distilling Data: The Importance of Data Quality in Business Intelligence


As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.

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Metagenix Reverse Engineers Data Into Information


Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than depending on the data dictionaries of the existing legacy systems (which are often incorrect). Other unique Metagenix approaches include an "open book" policy, which includes publishing product price lists on their web site and complete access to company officials, including CEO and President Greg Leman. According to Mr. Leman, "we’re pathologically honest".

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Automate to Optimize: The Foundation for Data Center Efficiency


IT administrators need to simplify both complex and routine tasks to deliver increasing value with limited resources. Data center automation can help minimize the duties associated with maintaining the existing infrastructure. Learn about a solution that can enable automated batch processing for more efficient operations, and integrate the diverse application and platform environments often found in today’s data centers.

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Big Data Comes of Age: Shifting to a Real-time Data Platform


New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support big data and the real-time needs of innovative companies.

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Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio


Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the traditional ways to store and analyze large amounts of data are being replaced with new technologies and methodologies to manage the new volume, complexity, and analysis requirements. These include new ways of developing data warehousing, the

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