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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 analysis


Role of In-memory Analytics in Big Data Analysis
Organizations today need to handle and manage increasingly large volumes of data in various formats and coming from disparate sources. Though the benefits to be

big data analysis  of In-memory Analytics in Big Data Analysis In a previous article , I discussed big data and the need for a big data solution to handle, manage, and derive valuable insight from large volumes of data in various formats and coming from disparate sources. Here I discuss the role that in-memory technologies plays in big data analysis and the potential of this technology to change the business intelligence (BI) landscape and the industry technology space. But first we need to understand the basics.   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

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 analysis

The SHL Talent Report: Big Data Insight and Analysis of the Global Workforce


There are a finite number of forces that influence business success. Most of these are driven by the abilities and motives of the people who make up our workforce. As such, the use of objective talent data to align your organization's talent with its strategic objectives yields a significant return. This is what SHL calls people intelligence. This report aims to provide a compass for organization's striving to improve their talent management initiatives.

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Actian and Pervasive Software: Big Merge for Big Data?


Actian Corporation, creator of the analytic database Vectorwise, and Pervasive Software, a provider of data management, integration, and analysis software, have entered into a final agreement in which Actian will acquire all of Pervasive shares. In a deal valued at $161.9 million (USD), Actian will acquire Pervasive’s ability to deal with the management of data in its many forms and

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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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Infor’s Acquisition of PeopleAnswers Foregrounds Big Data Behavioral Analysis of Employees


Infor has announced the acquisition of PeopleAnswers, a company specializing in predictive talent analytics. PeopleAnswers’ application maps the behavioral DNA of organizations by analyzing 39 behavioral traits to reveal behaviors that drive success—as understood by each company.

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Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations


While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as organizations seek to store and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers. This report examines the rise of "big data" and the use of analytics to mine that data.

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Sentiment Analysis: Movie Reviews


Sentiment analysis is the method of extracting subjective information from any written content. It is being widely used in product benchmarking, market intelligence, and advertisement placement. In this paper, we demonstrate the process by analyzing a movie review using various natural language processing techniques.

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Data Quality Strategy: A Step-by-Step Approach


To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.

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Data Quality Trends and Adoption


While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers.

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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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Data Center Projects: Advantages of Using a Reference Design


It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and shorten the planning and implementation process and reduce downtime risks once up and running. In this paper reference designs are defined and their benefits are explained.

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