X
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 solutions by funtionality, so that you can make accurate and informed software purchasing decisions.
Compare Now
 

 employs data reduction techniques factor analysis and principal components analysis


Running and Optimizing the Business of IT: The SAP Best-practices Approach
IT has long been seen as one of the best ways to address the challenges of the business environment. Yet the complexity and rigidity of IT infrastructure keep

employs data reduction techniques factor analysis and principal components analysis  for Adaptive Computing. T-Systems employs many tools to configure, control, and manage the IT infrastructure. According to Stohr, Having an environment with Adaptive Computing saves a lot by having it available from SAP. We do not have to develop it ourselves; we are system integrators, not developers. Indeed, T-Systems has experienced ongoing support and development cooperation from SAP with positive responses to requests for improvements to the Adaptive Computing Controller. Overall, T-Systems has fou

Read More


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. 

Evaluate Now

Documents related to » employs data reduction techniques factor analysis and principal components analysis

Making Big Data Actionable: How Data Visualization and Other Tools Change the Game


To make big data actionable and profitable, firms must find ways to leverage their data. One option is to adopt powerful visualization tools. Through visualization, organizations can find and communicate new insights more easily. Learn how to make big data more actionable by using compelling data visualization tools and techniques.

employs data reduction techniques factor analysis and principal components analysis   Read More

Operationalizing the Buzz: Big Data 2013


The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and use to explore why and how companies are utilizing Big Data. Download the report and get all the results.

employs data reduction techniques factor analysis and principal components analysis   Read More

Transactional Data: Driving Real-Time Business


A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more.

employs data reduction techniques factor analysis and principal components analysis   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.

employs data reduction techniques factor analysis and principal components analysis   Read More

Securing Data in the Cloud


When considering adopting cloud computing or software-as-a-service (SaaS), a question most potential customers ask vendors is “How secure will our data be in your hands?” Customers are right to ask this question and should closely examine any vendor’s security credentials as part of their cloud/SaaS evaluations. This document is intended to give a broad overview of one vendor’s security policies, processes, and practices.

employs data reduction techniques factor analysis and principal components analysis   Read More

Data Mart Calculator


Need a model to help calculate an estimate of manpower needs by role, timeline, and labor cost to build a data mart based on user-supplied variables? Here’s a calculator that provides two estimates. The first is based on using the traditional “develop by committee,” and the second on developing the same data mart at the developmental level. The model needs minimal input and can be changed to fit your needs. Find out more.

employs data reduction techniques factor analysis and principal components analysis   Read More

Enabling Real-Time Big Data Movement in the Constantly Connected World


Many forces in today's world of big data are driving applications to become more real-time. Data needs to go many places, be sorted and stored in different formats, and used in a wide variety of ways. Capturing high volume data streams inside and outside datacenters can be complicated and expensive using traditional software messaging middleware on general purpose servers. In order to realize the full value of “big data” some organizations are switching to real-time message-oriented middleware appliances that excel at the high-speed distribution of large volumes of data.

employs data reduction techniques factor analysis and principal components analysis   Read More

Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more agile architectures that can confront the new challenges much easier.

employs data reduction techniques factor analysis and principal components analysis   Read More

Enterprise Data Management: Migration without Migraines


Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an understanding of the entire ERP data lifecycle combined with industry-specific experience, knowledge, and skills to drive the process through the required steps accurately, efficiently, and in the right order. Read this white paper to learn more.

employs data reduction techniques factor analysis and principal components analysis   Read More

Data Center Automation


With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands.

employs data reduction techniques factor analysis and principal components analysis   Read More