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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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 ilm expensive data warehouse

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

Warehouse Management Systems (WMS)

A warehouse management system (WMS) should provide database and user-level tools in order for a company to optimize its storage facilities while at the same time providing user level task direction and activity support. The WMS should enable warehouse operators to optimize pick, put-away, and replenishment functions by employing powerful system logic to select the best locations and sequences. 

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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.

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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.

ilm expensive data warehouse  spend analytics,performance management software,spend analyses,supplier risk assessments,data enrichment and classification 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 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? Big Data can be a Big Deal - read this white paper for some useful tips on ensuring secure, quality data acquisition and management.

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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.

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Streaming Data and the Fast Data Stack


Big data is data at rest; fast data is streaming data, or data in motion. A stack is emerging across verticals and industries for building applications that process these high velocity streams of data. This new stack, the fast data stack, has a unique purpose: to grab real-time data and output recommendations, decisions, and analyses in milliseconds.

This white paper will look at the emerging fast data stack through the lens of streaming data to provide architects, CTOs, and developers with fundamental architectural elements of the new fast data stack: a LAMP stack for streaming data applications.

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Managing Small Data Centers: A Short Guide to Running Secure and Resilient Data Centers for Mid-sized Businesses


To keep your growing business competitive, your data center must be secure, protected against disaster, and available 24 hours a day, 7 days a week. But if managing IT is not your core competence, what are your options? A managed service provider (MSP) can help. Learn about the benefits of outsourcing data center management, and make sure your crucial business applications are always available when you need them.

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Warehouse Management Systems: Pie in the Sky or Floating Bakery?Part Two: The Pareto Principle, Processes, and People: Assessing Your Warehouse Management System Needs


To ensure your warehouse management system is implemented as painlessly as possible, you must assess your warehouse situation before you decide on a warehouse solution. Using the Pareto Principle, where a minority of inputs yields the majority results; examining your processes; evaluating your personnel; monitoring the progress of implementation; and testing are the best ways to ensure both a successful launch and long term return on investment.

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SAS/Warehouse 2.0 Goes Live


SAS Institute has announced the production availability of SAS/Warehouse Administrator software, Version 2.0. This new version provides IT the ability to proactively publish data warehouse information and track its usage, plus aggressively manage the process of change in the data warehouse.

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10 Errors to Avoid When Building a Data Center


In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you're going through the data center...

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The Data Warehouse RFP


If you don’t have a data warehouse, you’re probably considering drafting a request for proposal (RFP) to screen vendors and ensure that your receive satisfactory information about the features of various hardware and software and their price. Writing an effective RFP that is well structured and includes different metrics will ensure that you receive the information you need and will make you look good.

ilm expensive data warehouse   Read More

Reinventing Data Masking: Secure Data Across Application Landscapes: On Premise, Offsite and in the Cloud


Be it personal customer details or confidential internal analytic information, ensuring the protection of your organization’s sensitive data inside and outside of production environments is crucial. Multiple copies of data and constant transmission of sensitive information stream back and forth across your organization. As information shifts between software development, testing, analysis, and reporting departments, a large "surface area of risk" is created. This area of risk increases even more when sensitive information is sent into public or hybrid clouds. Traditional data masking methods protect information, but don’t have the capability to respond to different application updates. Traditional masking also affects analysis as sensitive data isn’t usually used in these processes. This means that analytics are often performed with artificially generated data, which can yield inaccurate results.

In this white paper, read a comprehensive overview of Delphix Agile Masking, a new security solution that goes far beyond the limitations of traditional masking solutions. Learn how Delphix Agile Masking can reduce your organization’s surface area risk by 90%. By using patented data masking methods, Delphix Agile Masking secures data across all application lifecycle environments, providing a dynamic masking solution for production systems and persistent masking in non-production environments. Delphix’s Virtual Data Platform eliminates distribution challenges through their virtual data delivery system, meaning your data can be remotely synchronized, consolidated, and takes up less space overall. Read detailed scenarios on how Delphix Agile Data Masking can benefit your data security with end-to-end masking, selective masking, and dynamic masking.

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Guidelines for Specification of Data Center Power Density


Conventional methods for specifying data center density don’t provide the guidance to assure predictable power and cooling performance for the latest IT equipment. Discover an improved method that can help assure compatibility with anticipated high-density loads, provide unambiguous instruction for design and installation of power and cooling equipment, prevent oversizing, and maximize electrical efficiency.

ilm expensive data warehouse  for Specification of Data Center Power Density Guidelines for Specification of Data Center Power Density If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. In today''s always on, always available world where businesses can''t stop and downtime is measured in dollars, American Power Conversion (APC) provides protection against some of the leading causes of downtime, data loss and hardware damage: power problems and temperature. Read More

Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations


While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as organizations seek to store and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers. This report examines the rise of "big data" and the use of analytics to mine that data.

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Data Center Projects: Advantages of Using a Reference Design


It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and shorten the planning and implementation process and reduce downtime risks once up and running. In this paper reference designs are defined and their benefits are explained.

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Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence


Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting requirements. This paper discusses the importance of data integration and helps you identify key challenges of integrating data. It also provides an overview of data warehousing and its variations, as well as summarizes the benefits and approaches to integrating data.

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