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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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Visit the TEC store to compare leading software solutions by funtionality, so that you can make accurate and informed software purchasing decisions.
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 huge data warehouse owb

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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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.

huge data warehouse owb  , Business Intelligence , Huge Data Warehouse , Data Warehouse Appliance . NOTE: The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole 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.

huge data warehouse owb  science that can provide huge returns to an organization. It 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 Read More

About Big Data


There may not be a consensus with respect to just how big "big data" is, but not many people will disagree that managing these huge amounts of data represents a challenge. TEC research analyst Jorge Garcia discusses the key issues surrounding big data, the different ways to manage it, and the major vendors offering big data solutions.

huge data warehouse owb  disagree that managing these huge amounts of data represents a challenge. It’s fair to say that we’re dealing with big data when traditional relational databases and systems are no longer sufficient. Things as simple as data storage and movement between repositories can have a big impact on the organization. Big data management is more than just working with an enormous data set; it has to do with the complexity of analyzing it and getting the most value from it— competitive advantage, performance Read More

Poor Data Quality Means A Waste of Money


Data quality sounds like a motherhood and apple pie issue, of course we want our data to be right. However, very few enterprises get serious about it. Maybe that's because the cost of data quality is hidden. That cost can be huge.

huge data warehouse owb  That cost can be huge. What Are The Costs? Data quality problems cost money. Internally, decisions based upon flawed data results in poor decisions. Fixing the problems caused by data quality takes time and money. Fixing the data itself is also expensive. Today, with extended supply chains and collaboration, the problems and the costs are shared by trading partners as well. Let''s look at some examples. A recent study by the Grocery Manufacturing Association (GMA) and the Food Marketing Institute (FMI) Read More

Four Critical Success Factors to Cleansing Data


Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.

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Warehouse Advantage


pdg group model 1270

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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.

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Six Steps to Manage Data Quality with SQL Server Integration Services


Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.

huge data warehouse owb  business data quality,customer data quality,data quality,data quality center,data quality control,data quality improvement,data quality analysis,data quality articles,data quality assessment Read More

Governance from the Ground Up: Launching Your Data Governance Initiative


Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing from philosophical questioning to hard-core tactics for data governance initiatives. This paper describes the components of data governance that will inform the right strategy and give companies a way to determine where and how to begin their data governance journeys.

huge data warehouse owb  data governance,data governance best practices,data governance model,data governance institute,what is data governance,data governance framework,data governance roles and responsibilities,data governance definition,data governance strategy,data governance software,data governance conference 2010,data governance maturity model,master data governance,data governance tools,data governance charter Read More

Next-generation Data Auditing for Data Breach Protection and Risk Mitigation


Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation. Stolen laptops, hacking, exposed e-mail, insider theft, and other causes of data loss can plague your company. How can you detect (and respond!) to breaches and protect your data center? Learn about the functions and benefits of an automated data auditing system.

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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-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 compares their key attributes, and provides a framework for choosing the best approach(es) based on business requirements.

huge data warehouse owb  DCIM, data center, data center infrastructure management, DCIM management, IT, IT infrastructure, APC by Schneider Electric, facility operations and maintenance, data center facility operations, data center PUE, PUE, prefabricated modular data center, data center systems Read More

How to Comply with Data Security Regulations


A remote data backup solution can be compliant with almost any international, federal, or state data protection regulation—and can be compliant with the common caveats of most data security laws by providing functionality like data encryption and secure media control. And, as some regulations require files to be archived for several years, you can create a routine that archives files you select for backup and storage.

huge data warehouse owb  bizdomain data storage security,database protection,research data security,online backup services,database encryption,security data protection,bizdomain enterprise data backup Read More

Warehouse Control Systems: Orchestrating Warehouse Efficiency


You’re probably already familiar with the role of a warehouse management system (WMS). But a warehouse control system (WCS)? In your warehouse, a WCS can play the role of a conductor by ensuring the individual pieces of material-handling equipment—such as conveyors and sorters—perform with harmony, precision, and efficiency. Find out how implementing a WCS execution system can complement your WMS’s planning abilities.

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