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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

Attaining Real Time, On-demand Information Data: Contemporary Business Intelligence Tools


Demand for instant access to dispersed information is being met by vendors offering enterprise business intelligence tools and suites. Portlet standardization, enterprise information integration, and corporate performance management are among the proposed solutions, but do they really deliver real time information?

implementing real time data warehousing olap  feel somewhat better about implementing cumbersome ERP and other enterprise systems. Indeed, many enterprises have already deployed some BI products too, such as querying and reporting tools, planning and budgeting applications, analytic applications, incentive management systems, portals, dashboards, and scorecards, along with data warehousing technology, data models, and integration software, and whatnot. In fact, anyone stocktaking technology inventory will likely find some CPM components already in 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 Success, Lessons Learned


Is business intelligence (BI) an application that pays off? We have all heard mixed results but a 2003 extensive study on on-line analytical processing (OLAP) states that BI usually pays off over 60 percent of the time , explains where the value is found, and describes what’s required to get the pay off.

implementing real time data warehousing olap  19 percent of companies implementing BI claim they have met or exceeded their business goals. Over 60 percent state they have at least largely met their goals. As always, soft benefits were more easily obtainable than hard benefits. A detailed look at the types of benefits reveals the following: Benefit % Companies Realizing Benefit Faster, more accurate reporting 81 Improved decision making 78 Improved customer service 56 Increased revenue 49 Savings in non-IT costs 50 IT savings 40 When the statistics 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

Operationalizing the Buzz: Big Data 2013


The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and use to explore why and how companies are utilizing Big Data. Download the report and get all the results.

implementing real time data warehousing olap  Enterprise Management Associates, EMA, 9sight Consulting, big data, hybrid data ecosystem, real-time data, big data buzz, big data requirements, big data challenges, big data architecture 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.

implementing real time data warehousing olap  big data, operational analytics, big data integration, big data strategy, analytical data platforms. hybrid data ecosystem 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.

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Master Data Management: Extracting Value from Your Most Important Intangible Asset


In a 2006 SAP survey, 93 percent of respondents experienced data management issues during their most recent projects. The problem: many organizations believe that they are using master data, when in fact what they are relying on is data that is dispersed throughout the enterprise. Discover the importance of master data and how the ideal master data management (MDM) solution can help your business get it under control.

implementing real time data warehousing olap  of home appliances. By implementing MDM, it was able to reduce the time associated with new product launches and eliminate errors that occurred during the collation and creation of content for its consumer Web site. In fact, it cut in half the time needed to create Web content, and the number of content errors noticed on the Web site (usually by consumers) dropped from 20 to 25 per week to 5 to 8 per week. Overall, average error rates seen on the Web declined 67%, catalog team productivity improved 50%, a Read More

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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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.

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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.

implementing real time data warehousing olap  to reach its customers, implementing a thorough data quality solution is crucial to your success. To learn more about practical and affordable data quality solutions that can scale to your growing business needs, visit http://www.MelissaData.com or call 1-800-MELISSA CASE STUDY - A Shari''s Berries Sacramento-based Shari''s Berries ships chocolate-covered strawberries nationwide via FedEx, guaranteeing on-time delivery of its perishable product line. They accept as many as 200 orders per hour during peak ho 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. Whil 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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Transactional Data: Driving Real-Time Business


A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more.

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