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
 

 bi data warehouse community

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) and Data Management

Get a shortlist of BI solutions based on your company’s needs and characteristics. It’s fast, free, and easy—and you’ll get the results immediately. 

Evaluate Now

Documents related to » bi data warehouse community

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.

bi data warehouse community  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 interactions between the various tools, and the high price points for the products require companies to perform careful technology evaluation before embarking on a warehousing project. However, the potential for enormous returns on investment and competitive advantage make data warehousing difficult to Read More

A Road Map to Data Migration Success


Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project teams encounter some very specific management and technical challenges. Minimizing the risk of these tricky migrations requires effective planning and scoping. Read up on the issues unique to data migration projects, and find out how to best approach them.

bi data warehouse community  4.0 Data Migration | BI Solutions and Data Migration Tools | CRM 4.0 Data Migration Manager | Data Migration Analysis | Data Migration Issues | Data Migration Cost | Data Migration Document | Data Migration System | Data Migration Methodology | Data Migration Project Plan | Data Migration Specialist | Data Migration Best Practices | Data Migration Strategies | Data Migration Utility | Free Data Migration | Practical Data Migration | Data Migration Download | Data Migration Guide | ETL | Strategies | 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.

bi data warehouse community  primary purpose of a BI solution is to provide a business with the necessary information to support better decision making. This requires the integration of data within and external to an enterprise. A sound data quality strategy protects an enterprise from inconsistencies and anomalies that arise from the complexity of integrating multiple systems and from hidden problems that are uncovered only through sophisticated analysis techniques. Data quality solutions provide organizations with the ability to Read More

Real-time In-memory Technologies Do Not Make Data Warehousing Obsolete


The benefits of well thought-out architecture for designing and implementing large-scale DW environments are well-documented. Perhaps the best known of the DW architectures is the Corporate Information Factory. Since the creation of this architecture, there have been many technological advances, making its implementation faster, more scalable, and better performing. The data warehouse is no longer “off limits” to the business community; self-service BI, more sophisticated types of analytics, and true experimental (data science) analyses can now be performed with ease, and an increase in productivity and agility and flexibility of overall BI deployments is the result. Learn more in this white paper authored by one of the co-developers of the corporate information factory DW architecture.

bi data warehouse community  and flexibility of overall BI deployments is the result. Learn more in this white paper authored by one of the co-developers of the corporate information factory DW architecture. Read More

Oracle Database 11g for Data Warehousing and Business Intelligence


Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

bi data warehouse community  and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data. Read More

The Value of Big Data


As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value.

bi data warehouse community  Value of Big Data As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value. Read More

Deploying High-density Zones in a Low-density Data Center


New power and cooling technology allows for a simple and rapid deployment of self-contained high-density zones within an existing or new low-density data center. The independence of these high-density zones allows for reliable high-density equipment operation without a negative impact on existing power and cooling infrastructure—and with more electrical efficiency than conventional designs. Learn more now.

bi data warehouse community  often uncertain about the capability of their existing data center and whether a new data center must be built to support higher rack densities. Fortunately, a simple solution exists that allows for the rapid deployment of high-density racks within a traditional low-density data center. A high-density zone, as illustrated in Figure 1, allows data center managers to support a mixed-density data center environment for a fraction of the cost of building an entire new data center. In this paper a Read More

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.

bi data warehouse community  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. Read More

Data Center Projects: Project Management


In data center design projects, flawed management frequently leads to delays, expense, and frustration. Effective project management requires well-defined responsibilities for every manager, tight coordination among suppliers, well-defined procedures for managing change, and consistent terminology. Learn how enforcing these requirements can help your company achieve an efficient process with a predictable outcome.

bi data warehouse community  a common language, avoid responsibility gaps and duplication of effort, and achieve an efficient process with a predictable outcome. This paper presents a framework for project management roles and relationships that is understandable, comprehensive, and adaptable to any size project. Introduction In a project to build or upgrade data center physical infrastructure, a structured and standardized process provides the essential foundation for efficient project execution and a successfully deployed system. Read More

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


In Data Storage in the Cloud Can You Afford Not To?

bi data warehouse community  are straining many companies'' abilities to keep pace. One obvious solution is storage in the cloud—but concerns regarding security, speed, and accessibility remain. Or do they? In Data Storage in the Cloud—Can You Afford Not To? , you''ll discover a cloud storage solution that offers you high-security dual-level encryption (SSLv3 and 256-bit AES) data accessibility from anywhere lower costs due to the economies of scale of cloud storage providers high availability due to the redundancy built into Read More

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.

bi data warehouse community  have buy-in from your biggest customers because ultimately you are trying to service those customers better than the competition. Evaluate Your Processes and Personnel In addition to uncovering your top twenty percent, you should also evaluate your processes and personnel. Get some more blank sheets of paper, write the name of each of your processes on top and document how they work. Include all processes such as receiving, picking, putaway, inventory control, will call, order entry, purchasing, and even Read More

How to Solve Your Warehouse Woes


Today’s manufacturers and distributors are under immense pressure to ensure their warehouse and supply chain activities are continually operating at peak performance. But before any improvements can be made, they must first develop a warehouse management improvement strategy.

bi data warehouse community  production planning, order-processing, or billing. But today, many manufacturers have come to rely on these solutions to help reduce stock levels and lead times, improve customer satisfaction, and optimize warehouse performance. In an ideal world, a WMS can bring tremendous benefits to your business: improved inventory visibility better warehouse space usage increased inventory and asset turns improved service and support quality a reduction in errors (thanks to the ability to identify, track, and solve 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.

bi data warehouse community  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. Read More

Master Data Management and Accurate Data Matching


Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process.

bi data warehouse community  Data Management and Accurate Data Matching Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process. Read More

Revamping Data Management: Big Data Proves Catalyst to Updating Data Management Strategies


Data management plays a key role in helping organizations make strategic sense of their data and how to best use it. Organizations with data management maturity have ushered in clear data goals, but many obstacles persist. This white paper reports survey results that help to establish a clear picture of how organizations are capitalizing on data management today, as well as what challenges and opportunities remain.

bi data warehouse community  Data Management: Big Data Proves Catalyst to Updating Data Management Strategies Data management plays a key role in helping organizations make strategic sense of their data and how to best use it. Organizations with data management maturity have ushered in clear data goals, but many obstacles persist. This white paper reports survey results that help to establish a clear picture of how organizations are capitalizing on data management today, as well as what challenges and opportunities remain. Read More