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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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 contains information on data warehousing olap

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

Human Resources (HR)

Human Resources encompasses all the applications necessary for handling personnel-related tasks for corporate managers and individual employees.  Modules will include Personnel Management, Benefit Management, Payroll Management, Employee Self Service, Data Warehousing and Health & Safety.  

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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.

contains information on data warehousing olap  broad field indeed, it contains technologies such as Decision Support Systems (DSS), Executive Information Systems (EIS), On-Line Analytical Processing (OLAP), Relational OLAP (ROLAP), Multi-Dimensional OLAP (MOLAP), Hybrid OLAP (HOLAP, a combination of MOLAP and ROLAP), and more. BI can be broken down into four broad fields: Multi-dimensional Analysis Tools: Tools that allow the user to look at the data from a number of different angles . These tools often use a multi-dimensional database referred to Read More

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.

contains information on data warehousing olap  Enterprise Data Warehousing | Contains Information on Data Warehousing | Building the Data Warehouse | Term Data Warehouse Lists | Expensive Data Warehouse | Data Warehousing Provides | Data Warehouse Appliance Consists | Data Warehouse Info | Implementing Data Warehouse | Data Warehouse Process | Implementing Real Time Data Warehousing | Data Warehouse System Complete | Data Warehouse EDW | Data Warehouse Architecture EDW | Data Warehouse Concepts EDW | Data Warehousing Information Center EDW | Data Read More

Open Source Business Intelligence: The Quiet Evolution


As organizations face a pressing need to rationalize the cost of enterprise software, open source business intelligence (BI) is fast becoming a viable alternative. Learn about the current state of open source BI, with particular focus on one vendor's products.

contains information on data warehousing olap  in a transformation and contains either predefined or custom logic that is applied to each row as it makes its way from the source to the target); slowly changing dimensions (SCDs); connectors for a multitude of data sources (access to proprietary databases such as Microsoft SQL Server and Oracle is via Java Database Connectivity [JDBC]); and the ability to execute and schedule jobs both locally and remotely. Scripting in Javascript as well as pure Java allows developers to add custom code in any step of Read More

Distilling Data: The Importance of Data Quality in Business Intelligence


As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.

contains information on data warehousing olap  If a record that contains an address is missing the state or province, but has the city and country, the most appropriate action would be to correct the record by inferring the state or province from the other two data items, rather than terminating or ignoring the error. Data cleansing functionality has advanced considerably, and most data integration platforms offer a variety of features tailored for most business scenarios. Validation checks if every data value follows specified business rules. If, Read More

Business Intelligence: A Guide for Midsize Companies


Business intelligence (BI) is not a new concept. What’s new is that BI tools are now accessible for midsize companies. Managers can use BI to analyze complex information to support their decision-making processes, combining data from a variety of sources to get an integrated, 360-degree view of the company. Find out how to select the right BI software, the right vendor, and the right approach to implementing BI.

contains information on data warehousing olap  A data warehouse usually contains data from many sources, and data integration software provides the enabling technology for loading the warehouse, while data-quality software helps ensure that the consolidated data is both accurate and consistent. Many organizations have attempted to build data warehouses that, for all practical purposes, were data dumps; the use of data-quality software would have prevented this. One of the oldest IT adages is garbage in, garbage out, and this applies to both data Read More

Big Data: Operationalizing the Buzz


Integrating big data initiatives into the fabric of everyday business operations is growing in importance. The types of projects being implemented overwhelmingly favor operational analytics. Operational analytics workloads are the integration of advanced analytics such as customer segmentation, predictive analytics, and graph analysis into operational workflows to provide real-time enhancements to business processes. Read this report to learn more.

contains information on data warehousing olap  big data, operational analytics, big data integration, big data strategy, analytical data platforms. hybrid data ecosystem Read More

Forrester TechRadar Report: Data Security


Data security is not just an IT issue these days but a business imperative, as data volumes explode and it is becoming a Herculean task to protect sensitive data from cybercriminals and prevent privacy infringements. As data volumes continue to rise, the burden of protecting sensitive data and preventing security breaches can be crushing. It is necessary to take a holistic, comprehensive, and long-lasting approach to data security that encompasses people, processes, and technology.

This Forrester TechRadar Data Security report provides a framework for developing a long-term approach to keeping your organization’s information secure. Data breaches and insider threats are becoming more common, and your organization needs to achieve compliance and secure privacy without affecting the bottom line. Most companies are also interested in adopting cloud, mobile, and other technologies, which can complicate data security matters even more.

This comprehensive and in-depth report evaluates 20 of the key traditional and emerging data security technologies. To make the report, Forrester interviewed over 40 experts, customers, and users, and drew from a wealth of analyst experience, insight, and research.

Use this report to get informed about what you need to consider to restrict and strictly enforce access control to data, monitor, and identify abnormal patterns of network or user behavior, block exfiltration of sensitive data, and render successful theft of data harmless.

contains information on data warehousing olap  TechRadar Report: Data Security Data security is not just an IT issue these days but a business imperative, as data volumes explode and it is becoming a Herculean task to protect sensitive data from cybercriminals and prevent privacy infringements. As data volumes continue to rise, the burden of protecting sensitive data and preventing security breaches can be crushing. It is necessary to take a holistic, comprehensive, and long-lasting approach to data security that encompasses people, Read More

The Scribe Solution for Salesforce and Microsoft Dynamics GP: Bridging the Gap Between On-demand CRM and On-premise ERP


For years, organizations have had to settle for inadequate approaches to front-office to back-office integration. However, with Scribe’s component architecture, when a new version of Dynamics GP or Salesforce comes out, you can plug in a new version of the Scribe Adapter for the upgraded application, and your existing Dynamics GP to Salesforce Template will experience little or no disruption.

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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.

contains information on data warehousing olap  outdated, fl awed, or contains one or more errors. And, in the typical enterprise setting, customer and transactional data enters the database in varying formats, from various sources (call centers, web forms, customer service reps, etc.) with an unknown degree of accuracy. This can foul up sound decision-making and impair effective customer relationship management (CRM). And, poor source data quality that leads to CRM project failures is one of the leading obstacles for the successful implementation of 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.

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Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security


Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace.

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The Fast Path to Big Data


Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

contains information on data warehousing olap  Fast Path to Big Data Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise Read More

Paperless Warehousing


Paperless Warehousing Pty Limited was incorporated in 1988 by two of the existing Directors with a vision to overhaul traditional warehousing operations by improving the logistics processes inside and outside the four walls of a warehouse thus providing Companies with a market advantage. Based in Sydney, Australia, Paperless Warehousing offers a wealth of experience, solidarity and dependability in Warehouse and Transport Management Systems. All our people are employees and are practitioners of the Logistics industry who know our products in depth and act as the quality control department for our developers. They are not outside consultants and are all housed in the same office in Sydney which creates an energy-filled atmosphere for the development and cross fertilisation of future enhancements. At Paperless Warehousing we have improved and modernised workflow by digitising the traditional paper based activities and replacing them with them with real time Radio Frequency Scanned or Interactive Voice Directed Tasks and/or RFID all within the same package. We have successfully implemented numerous major projects in various industry sectors across Australia and our software has been implemented in over 12 countries.

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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.

contains information on data warehousing olap  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

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.

contains information on data warehousing olap  is complete. Each address contains all of the necessary information for mailing, including apartment or suite number, ZIP Code and, if needed, carrier route and walk sequence. The data is not redundant. There is only one record per contact for every address in a mailing list. The data is standardized. Each record follows a recognized standard for names, punctuation and abbreviations. Every record that fails to meet the above standards of quality can lead to either lost revenue or unnecessary costs. This Read More