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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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 big data 2011


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

big data 2011  to face in doing big data management and analysis? Hadoop seems to becoming the de facto technology for “Big Data” processing. While the advantages may be clear (no license fees, open source, etc.), the barriers to entry can be large. Organizations considering Hadoop must realize that to implement a Hadoop environment and maintain its operation calls for a considerable engineering skill set and resource. Despite the need for this large engineering investment, many organizations are still willing to ta

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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

Field Service Management (FSM)

Field service management (FSM) software is a set of functionalities for organizations or departments within organizations that have as main focus the intallation, maintanance, reparing, and meter reading for industries relying heaviling on equipment. FSM workers require functionality for customer engagement management, service and asset management as well as workforce management. Since most activities in FSM take place outside of the office, mobility is a big component of the a FSM software solutions. Typically, FSM software is not used as a stand-alone solution, as it needs to integrate with Financials, ERP, CRM and EAM to ensure accurate data exchange. Even if its main purpose is to maintain and repair equipment, it can also be used to gather customer satisfaction and equipment performance feedback. To allocate human resources efficiently, workforce management is an integral part of an FSM system. 

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Documents related to » big data 2011

Jaspersoft 4 Goes Big Data


On January 11, 2011, Jaspersoft launched a new version of its business intelligence (BI) suite named Jaspersoft 4, and just a couple of weeks later, on January 25, the open source BI provider launched a new set of software tools that provides support for a wider variety of data sources in the “Big Data” space. This is a clear sign that BI applications will come to address a wider number of data

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Conference Note: 2014 HR Technology Conference Takes On HCM Big Data


This year’s HR Technology Conference was all about leveraging big data for improving HR practices, such as talent acquisition and employee retention. TEC HCM analyst Raluca Druta was there to capture all the details. Read her take on the conference’s major sessions—the welcome and opening keynotes, the ADP Workforce Vitality Report, the Sierra-Cedar 17th Annual Survey, the vendor presentations, and more.

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3 Big Trends in Data Visualization


The greatest value of a picture is when it forces us to notice what we never expected to see. —John W. Tukey. Exploratory Data Analysis. 1977. Data visualization is core to business intelligence (BI), as it’s the means by which data is communicated to the user. Results, alerts suggestions, or even more controlled guidance—all of these elements are passed through the data visualization

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About Big Data


There may not be a consensus with respect to just how big "big data" is, but not many people will disagree that managing these huge amounts of data represents a challenge. TEC research analyst Jorge Garcia discusses the key issues surrounding big data, the different ways to manage it, and the major vendors offering big data solutions.

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Scalable Data Quality: A Seven-step Plan for Any Size Organization


Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor data quality isn’t an option—implementing a thorough data quality solution is key to your success. Find out how.

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Customer Data Integration: A Primer


Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a customer relationship management initiative can help provide organizations with a successful framework to manage data on a continuous basis.

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MSI Data


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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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Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

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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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