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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 r...
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Documents related to » most data


Master Data Management: Extracting Value from Your Most Important Intangible Asset
In a 2006 SAP survey, 93 percent of respondents experienced data management issues during their most recent projects. The problem: many organizations believe

most data  management issues during their most recent projects. Data management was also identified as the root cause of problems in process improvement projects. The best way to manage data depends on the unique characteristics of the data. For instance, master data is reference data about key entities within the organization, such as customers, products, employees, and so on. Unlike transactional data '' for example, a sales order '' master data does not change frequently and typically involves a relatively small Read More
Data Management and Business Performance: Part 1-Data
Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a

most data  address them all. The most important thing we can do to ensure a more efficient data management process is stay attuned to the changing business priorities of the organization. As always, I welcome your thoughts—leave a comment below, and I’ll respond as soon as I can. Read More
Unified Data Management: A Collaboration of Data Disciplines and Business Strategies
In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration

most data  and Business Strategies In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts. Read More
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

most data  to focus on the most relevant and critical issues to be solved, otherwise you risk not delivering effective results. The identification process can potentially help you define the potential use case (i.e., initial objective) and initial scope of your strategy. You need to ask yourself some questions: What are the more relevant risks or critical issues regarding your information security? If you already have an ongoing data governance program, do you need to modify your ongoing initiative to meet this new Read More
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

most data  has advanced considerably, and most data integration platforms offer a variety of features tailored for most business scenarios. Validation checks if every data value follows specified business rules. If, for instance, the data format of a social security number is incorrect, or a mandatory data value is missing, a validation procedure can flag and even clean or correct the data value. Complex business rules specific to the business environment can also be built to validate permissible data values where Read More
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

most 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. Read More
Don''t Be Overwhelmed by Big Data
Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect

most data  t Be Overwhelmed by Big Data Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Read More
Demystifying Data Science as a Service (DaaS)
With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been

most data  Data Science as a Service (DaaS) With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white Read More
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

most data  wags the dog because most data problems are identified too late. Since there is little time left to fix the problem, most application projects wind up compromised in some way reduced functionality, budget overrun, or late delivery. For example, if the application is a new inventory management system that is supposed to reduce inventory by $20 million annually, then every day that application is late may be costing the business $55,000. Anecdotal evidence suggests that the data migration phase can Read More
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

most data  your view, the two most important advances to date in the data warehouse and BI space? The number one advance to date is massively parallel processing, or MPP. Without it we could not possibly cope with the ever-increasing data volumes and analytic complexity that business applications command. While Moore’s Law , which dictates that processing power doubles every two years, is still valid for most applications, it does not ring true in the data warehousing space, where data volumes double every year. Read More
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

most data  fit to use. The most important phase in a data migration project involves the tasks needed to understand the data content. You would not put dirty petrol in your new car—why would you map bad data into your new software application? It''s unlikely that anyone on your team really understands the current state of the data at the level of detail needed for your project. And even if the source data is pristine, that doesn''t mean that it is fit for the requirements of the new application. Experience shows Read More
Types of Prefabricated Modular Data Centers
Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod

most data  of Prefabricated Modular Data Centers Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and Read More
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

most data  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 Read More

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