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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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 analyzing statistical data


Captured by Data
The benefits case for enterprise asset management (EAM) has been used to justify huge sums in EAM investment. But to understand this reasoning, it is necessary

analyzing statistical data  find themselves recommending and analyzing activities of not only maintenance, but also other areas of asset management, namely those of asset modification and operations. Safety and environmental compliance play their part in creating the drive for this activity, particularly given the changing legal and regulatory frameworks around these two areas; in some industries they are even the principal drivers. However, for most businesses the goal remains that of maximum value from their investment. This

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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

Business Intelligence (BI)

Business intelligence (BI) and performance management applications enable real-time, interactive access, analysis, and manipulation of mission-critical corporate information. These applications provide users with valuable insights into key operating information to quickly identify business problems and opportunities. Users are able to access and leverage vast amounts of information to analyze relationships and understand trends that ultimately support business decisions. These tools prevent the potential loss of knowledge within the enterprise that results from massive information accumulation that is not readily accessible or in a usable form. It is an umbrella term that ties together other closely related data disciplines including data mining, statistical analysis, forecasting, and decision support. 

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The Art, Science & Software Behind (Optimal) Retail Pricing - Part 3


Part 1 of this blog post series expanded on some of TEC’s earlier articles about companies’ need for better pricing management and optimization practices. This series, which focuses on the complexity of pricing and promotions in retailing, was inspired by JDA Software’s recent “edu-nouncement” on leading retailers' consumer-centric pricing and promotions strategies and

analyzing statistical data  this by incorporating and analyzing factors such as localized merchandising categories, product distribution, assortment and complementarity, cannibalization, stockpiling by consumers, equivalent volumes and discrete events such as holidays. The software also includes an  activity-based costing (ABC)  model to quantify and forecast the store/item level margin impact caused by varying supply chain costs. Optimization and Rules Enforcement. While demand modeling is a powerful tool that can provide Read More

The Art, Science & Software Behind (Optimal) Retail Pricing - Part 4


Part 1 of this blog post series expanded on some of TEC’s earlier articles about companies’ need for better pricing management and optimization practices. This series, which focuses on the complexity of pricing and promotions in retailing, was inspired by JDA Software’s recent “edu-nouncement” on leading retailers consumer-centric pricing and promotions strategies and by Revionics’ recent (and

analyzing statistical data  the blog series by analyzing the pricing optimization vendor landscape and various vendors’ approaches to the next generation of pricing optimization solutions.  JDA's Price and Promotion Management Solutions There is hardly anything to disagree within JDA’s aforementioned well-crafted and educational press release (PR), except perhaps for the fact that JDA doesn’t necessarily cross my mind as a retail pricing optimization leader.  JDA’s Price and Promotion Management retail solution  is Read More

A Definition of Data Warehousing


There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.

analyzing statistical data  can assist companies in analyzing the impact of changes to database tables, tracking owners of individual data elements ( data stewards ), and much more. It is also required to build the warehouse, since the ETL tool needs to know the metadata attributes of the sources and targets in order to map the data properly. The BI tools need the metadata for similar reasons. Summary: Data Warehousing is a complex field, with many vendors vying for market awareness. The complexity of the technology and the Read More

Data, Data Everywhere: A Special Report on Managing Information


The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and extract useful information, is harder still. Even so, this data deluge has great potential for good—as long as consumers, companies, and governments make the right choices about when to restrict the flow of data, and when to encourage it. Find out more.

analyzing statistical data  Data Everywhere: A Special Report on Managing Information SAP NetWeaver Master Data Management (SAP NetWeaver MDM) is an enabling foundation for enterprise services and business process management. Working across heterogeneous systems at disparate locations, SAP NetWeaver Master Data Management ensures cross-system data consistency through interactive distribution. Source: SAP Resources Related to Data, Data Everywhere: A Special Report on Managing Information : Data (Wikipedia) Data, Data Read More

Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio


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analyzing statistical data   Read More

Data Storage in the Cloud-Can you Afford Not To?


Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or avoided by using the cloud for backup and archive storage.

analyzing statistical data  data storage in the cloud,cloud data storage,online data storage,offsite data storage,data storage cloud,data storage solution,data storage business,data storage,data storage internet,data storage service,best cloud storage,online data storage backup,microsoft cloud storage,cloud services,cloud storage providers 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.

analyzing statistical data  data quality solution,enterprise information management,enterprise information management strategy,enterprise information management definition,enterprise information management framework,enterprise information management software,data quality maturity,data quality software,open source data quality software,data quality,data quality tools,customer data quality,data quality metrics,data quality management,data quality objectives 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 business intelligence (BI) solution. Two topics resounded: the use of BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of

analyzing statistical data  are extremely useful for analyzing what problems need attention first because the taller bars on the chart, which represent frequency, clearly illustrate which variables have the greatest cumulative effect on a given system.” From the chart we can see that data management and business performance management (BPM) together make up nearly 60% of all responses. This means that these two topics are still of major concern for most organizations and represent the top priorities for companies in search for a Read More

Overall Approach to Data Quality ROI


Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI.

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Best Practices for a Data Warehouse on Oracle Database 11g


Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW performs and scales well, you need to get three things right: the hardware configuration, the data model, and the data loading process. Learn how designing these three things correctly can help you scale your EDW without constantly tuning or tweaking the system.

analyzing statistical data  Practices for a Data Warehouse on Oracle Database 11g Best Practices for a Data Warehouse on Oracle Database 11g If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Oracle has been helping customers like you manage your business systems and information with reliable, secure, and integrated technologies. Source : Oracle Resources Related to Data Warehouse : Data Warehouse (Wikipedia) Best Practices for a Data Warehouse on Oracle Database Read More

The Evolution of a Real-time Data Warehouse


Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine if your organization needs this type of IT solution.

analyzing statistical data  (gathering, integrating, cleaning, and analyzing this heterogeneous information), new software systems were developed. The data warehouse is its most important character. A collection of subject-oriented, integrated, time-variant, and non-volatile data is what we can call a data warehouse. This data is used to support the decision-making process of an organization's management team. A data warehouse is used to integrate all of an organization's historical data, and has the ability to store snapshots of Read More

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.

analyzing statistical data  customer data quality,data cleansing service,data integration system,data cleansing services,data profiling,data profiling software,data quality,data cleansing software,data governance,data integration 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.

analyzing statistical data  big data,innovation,data management,data platforms,data ecosystems Read More