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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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 implementing real time 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

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. 

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Documents related to » implementing real time data warehousing olap

The Evolution of a Real-time Data Warehouse


Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine if your organization needs this type of IT solution.

implementing real time data warehousing olap  the technical difficulties of implementing a true real-time data warehouse, there are some advantages. It shortens information delivery times. It improves integration throughout the organization. It eases the analysis of future trends. Basic Principles to Consider With the growing popularity and increasing implementation of real-time data warehouses, it is important to consider some basic principles when considering a real-time data warehouse implementation. Data on Time, at the Right Time . The data 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.

implementing real time data warehousing olap  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 Integration Paper EDW | Data Warehouse Software EDW | Data Warehousing Analysis EDW | Data Warehouse Community EDW | Data Warehouse Automation EDW | Perspectives on Data Warehousing EDW | Data Warehousing OLAP EDW | Resource Data Warehouse EDW | Land and Resource Data Read More

Microsoft Takes A Shot at the Business Intelligence Market


Microsoft Business Scorecard Manager 2005 has allowed Microsoft to enter the business intelligence (BI) market by using its client base to expand its offering. Microsoft offers a complete solution with its SQL Server platform, OLAP, reporting analysis, and scorecarding capabilities.

implementing real time data warehousing olap  some cases, this means implementing various applications and vendor solutions based on the needs identified within individual departments. For example, an organization may implement a Cognos solution to manage its sales force performance, and a Hyperion solution because of its strong financial consolidation functionality within the finance department. As BI has changed to accommodate real-time data analysis, and to provide forward-looking business planning and strategies, the need to bring a single set 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.

implementing real time data warehousing olap  of its core projects, implementing open industry standards and establishing partnerships with vendors of data warehouse technology, such as InfoBright and ParAccel . BI has some of the most challenging technology problems among all enterprise software applications. These challenges include the design of very large databases; complex data integration between disparate and multiple data sources; the ability to search across a surfeit of information; and some of the most stringent performance and latency 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.

implementing real time data warehousing olap  of BI Approaches to Implementing BI Make Business Users Self- Sufficient BI Consumers Facilitate Analysis with a Data Warehouse What to Look for in a BI Product What to Look for in a BI Vendor Conclusion   Executive Summary Make Informed Decisions Across Your Company Furthermore, you need the ability to determine where to concentrate your efforts. You can''t check every detail, yet you would like to be able to monitor your operations and focus on quickly finding and resolving potential problems while Read More

Data Management and Business Performance: Part 1-Data


Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a business intelligence (BI) solution. Two topics resounded: the use of BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of

implementing real time data warehousing olap   Read More

Linked Enterprise Data: Data at the heart of the company


The data silos of today's business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, break down data walls, provide an open, secure, and long-term technological environment, and reduce complexity—read this white paper to find out how.

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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.

implementing real time data warehousing olap  Big Data,Big Data architecture,Big Data challenges,Big Data system,Big Data technology Read More

Considerations for Owning versus Outsourcing Data Center Physical Infrastructure


When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life expectancy, regulatory requirements, and other strategic factors. This paper discusses how to assess these key factors to help make a sound decision.

implementing real time data warehousing olap  DCIM, data center, data center infrastructure management, DCIM management, DCIM software, DCIM software tools, IT, IT infrastructure, APC by Schneider Electric, facility operations and maintenance, data center life cycle, data center facility operations, data center PUE, PUE, data center physical infrastructure, data center infrastructure outsourcing Read More

Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise


While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help.

implementing real time data warehousing olap   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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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.

implementing real time data warehousing olap  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

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.

implementing real time data warehousing olap  big data,data management,analytics,SAP Read More

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.

implementing real time data warehousing olap  any function related to implementing high density power or cooling. Ability to spread loads: The ability to spread IT equipment physically within a data center is a practical option for most IT equipment today, due to the wide use of fiber-optic cabling. It is not necessary or desirable in many cases to deploy equipment at the full density it is capable of. Blade servers and 1U servers are examples of high density IT equipment that can readily be spread out between racks in order to decrease density. Read More