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Software Functionality Revealed in Detail
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 analysis data

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

Core PLM--Product Data Management - Discrete RFI/RFP Template

Product Data Management (PDM), Engineering Change Order and Technology Transfer, Design Collaboration, Process and Project Management, Product Technology  

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Data Management and Analysis


From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As).

For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most accurate data tools and systems in place to efficiently carry out their daily tasks. Data generation development, data quality, document and content management, and data security management are all examples of data-related functions that provide information in a logical and precise manner.

analysis data  Management and Analysis From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As). For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users Read More

How Bar Codes Can Optimize Data Recording and Information Analysis


Bar code technology allows users to analyze information to develop more accurate maintenance, personnel, and financial planning. In particular it can hasten the data recording processes in a maintenance system, as seen in its use in the aircraft maintenance process.

analysis data  users to perform an analysis of the data records that will contribute to more accurate maintenance, personnel, and financial planning (maintenance budgets). About the author Juan Francisco Segura is an industrial engineer specializing in processes and automation. He has worked for the Universidad Iberoamericana, in Mexico City, as a computer technology consultant in the area of physics, arranging electronic and computing equipment for their labs. During the last six years, he has worked as a computer prof Read More

Benchmark Study - Embarcadero Technologies, Inc. CM/Data Competitive Analysis


Competitive testing analysis is a vital part of designing, evaluating, and marketing hardware and software products. National Technical Systems (NTS) tested two change management systems, measuring how quickly each compares selected datasets. Find out which solution proved to be twice as fast as the other in a local area network (LAN), and almost 24 times faster in a wide area network (WAN) environment. Learn more.

analysis data  Technologies, Inc. CM/Data Competitive Analysis Competitive testing analysis is a vital part of designing, evaluating, and marketing hardware and software products. National Technical Systems (NTS) tested two change management systems, measuring how quickly each compares selected datasets. Find out which solution proved to be twice as fast as the other in a local area network (LAN), and almost 24 times faster in a wide area network (WAN) environment. Learn more. Read More

Actionable Spend Analysis: From Data to Savings


Having realized the savings that can be generated by managing corporate spending, many organizations are now aiming to employ and leverage spend analysis to implement sourcing and procurement strategies. Is quality data the cornerstone of successful spend analysis? Most of us would say yes, without hesitation. However, if you dig deeper, you might be in for a surprise.

analysis data  employ and leverage spend analysis to implement sourcing and procurement strategies. Is quality data the cornerstone of successful spend analysis? Most of us would say yes, without hesitation. However, if you dig deeper, you might be in for a surprise. Read More

TCO Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center


Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30% compared with traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the two architectures, and illustrates the key drivers of both the capex and opex savings of the improved architecture.

analysis data  Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30% compared with traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the Read More

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.

analysis 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. Read More

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.

analysis data  the results of the analysis are used to build targeted data quality routines to correct, standardize, and validate customer data. Some main features of the DataFlux CDI Solution include data profiling, access to multiple data sources, connection and access to multiple data sources to allow for easy and timely analysis, and matching and de-duplication functionality. Conclusion CDI is the act of consolidating data from across the organization to create a centralized view of the customer. Vendors have Read More

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.

analysis data  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 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 migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

analysis data  a Successful Data Migration Achieving a Successful Data Migration If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Informatica''s data migration solution decreases the risk and minimizes the errors inherent in data migration projects. At the same time, our solution reduces the costs of data migration projects by automating processes, improving business-IT collaboration, and incorporating proven best practices. Source : Informatic Read More

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.

analysis data  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 Read More

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.

analysis data  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 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 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 paper to find out more about how data SaaS is set to become a vital part of business intelligence and analytics, and how India will play a role in this trend.

analysis data  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 paper to find out more about how data SaaS is set to become a vital part of business intelligence and analytics, and how India will play a role in this trend. Read More

Agile Data Masking: Mitigate the Threat of Data Loss Prevention


You may not be as protected from data loss as you think. This infographic looks at some ways in which an enterprise's data can be compromised and vulnerable to security breaches and data loss, and shows how data masking can mean lower security risk and increased defense against data leaks.

analysis data  Data Masking: Mitigate the Threat of Data Loss Prevention You may not be as protected from data loss as you think. This infographic looks at some ways in which an enterprise''s data can be compromised and vulnerable to security breaches and data loss, and shows how data masking can mean lower security risk and increased defense against data leaks. Read More

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.

analysis 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. Read More