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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


About Big Data
There may not be a consensus with respect to just how big

big data  Big Data There is no general consensus with respect to how big big data is—some companies deal with data volumes in the order of terabytes or even petabytes—but not many people will disagree that managing these huge amounts of data represents a challenge. It’s fair to say that we’re dealing with big data when traditional relational databases and systems are no longer sufficient. Things as simple as data storage and movement between repositories can have a big impact on the organization. Big

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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

What’s the Big Deal with Big Data?


{democracy:89} I won’t define big data here, but it’s clear for all the IT community to see that big data is the latest “big thing.” Just Google or Bing the term “big data” and you’ll get an idea of the amount of information and resources available (about 1,460,000,000 and 67,000,000 hits, respectively). But in our continuous research and talks with both software vendors and customers, we

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The Operational Data Lake: Your On Ramp to Big Data


Companies recognize the need to integrate big data into their real-time analytics and operations, but this poses a lot of technical and resource challenges. Meanwhile, those organizations that have operational data stores (ODSs) in place find that, while useful, they are expensive to scale. The ODS gives real-time visibility into operational data. While more cost-effective than a data warehouse, it uses outdated scaling technology, and performance upgrades require very specialized hardware. Plus, ODSs just can't handle the volume of data that has become a matter of fact for businesses today.

This white paper discusses the concept of the operational data lake, and its potential as an on-ramp to big data by upgrading outdated ODSs. Companies that are building a use case for big data, or those considering an upgrade to their ODS, may benefit from this stepping stone. With a Hadoop relational database management system (RDBMS), companies can expand their big data practices at their own pace.

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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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Revamping Data Management: Big Data Proves Catalyst to Updating Data Management Strategies


Data management plays a key role in helping organizations make strategic sense of their data and how to best use it. Organizations with data management maturity have ushered in clear data goals, but many obstacles persist. This white paper reports survey results that help to establish a clear picture of how organizations are capitalizing on data management today, as well as what challenges and opportunities remain.

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Backing up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices


This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions to the challenges of protecting distributed business data by establishing a private cloud/enterprise cloud. Learn which best practices can ensure business continuity throughout an organization with a distributed information technology (IT) infrastructure.

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Oracle Database 11g for Data Warehousing and Business Intelligence


Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

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Data Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses


Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and predictive analysis. Learn more.

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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 Enrichment and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics


Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident decisions and take the right actions, you need more than just software—you also need the right data. This white paper discusses a solution to help ensure that your applications process reliable data so that your spend analyses and supplier risk assessments are accurate, trustworthy, and complete.

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Four Critical Success Factors to Cleansing Data


Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.

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