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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 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

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 owb

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.

implementing real time data warehousing owb  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) analy 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.

implementing real time data warehousing owb  processes that they are implementing. Allow time in your planning for changes to the mapping, business rules, and re-loads. It is not uncommon for there to be confusion during beta testing and implementation as to where errors originate. It''s all too easy for bad data to be blamed for every test error. What can you do as part of your planning to avoid this? Implement the migration with as much metadata and reconciliation as possible. Not only are you ensuring the integrity of your data, you are creating Read More

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 owb  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 must Read More

Business Process Overview: Warehousing Solutions


Warehousing processes are critical for the success of a distribution business. These processes are highly visible to your customers, and have a direct impact on their opinion of your company. If you cannot get the goods to your customers in the most efficient way, you risk losing their business. Your warehousing and logistics operations must translate into reliability and service.

implementing real time data warehousing owb  customers and business partners. Implementing IBS’ solution for your warehousing needs can help you realise increased revenue, which helps the system pay for itself. Automated and more efficient routines, accurate control, process transparency, and faster time to market are just some of the benefits you can derive from IBS systems. IBS is designed to optimise the use of your warehousing operations through the full integration of information into the workflow. With IBS, you can help ensure that every asp 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 owb  will only deal with implementing S.A.M.E using a combination of hardware and ASM features. From the hardware perspective, build redundancy in by implementing mirroring at the storage subsystem level using RAID 1. Once the RAID groups have been create you can turn them over to ASM. ASM provides filesystem and volume manager capabilities, built into the Oracle Database kernel. To use ASM for database storage, you must first create an ASM instance. Once the ASM instance is started, you can create your ASM di Read More

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


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

implementing real time data warehousing owb  data storage cloud afford,data,storage,cloud,afford,storage cloud afford,data cloud afford,data storage afford,data storage cloud. Read More

Data Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses


Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and predictive analysis. Learn more.

implementing real time data warehousing owb   Read More

Streaming Data and the Fast Data Stack


Big data is data at rest; fast data is streaming data, or data in motion. A stack is emerging across verticals and industries for building applications that process these high velocity streams of data. This new stack, the fast data stack, has a unique purpose: to grab real-time data and output recommendations, decisions, and analyses in milliseconds.

This white paper will look at the emerging fast data stack through the lens of streaming data to provide architects, CTOs, and developers with fundamental architectural elements of the new fast data stack: a LAMP stack for streaming data applications.

implementing real time data warehousing owb  big data, data stack, fast data, fast data stack, streaming data applications, VoltDB Read More

Top 10 Evaluation Criteria for Copy Data Management & Data Virtualization


Data virtualization is becoming more important, as industry-leading companies learn that it delivers accelerated IT projects at a reduced cost. With such a dynamic space, one must make sure that vendors will deliver on their promises. This white paper outlines 5 qualification questions to ask before and during the proof of concept (POC), and 5 things to test during the POC.

implementing real time data warehousing owb  data management, data virtualization, proof of concept, POC, data center, provisioning, data security, copy data management, CDM Read More

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 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

A Roadmap to Data Migration Success


Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them.

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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.

implementing real time data warehousing owb  project management,internalize data centers,data center project management services,data center project management,virtual data center,data center knowledge,data center virtualization 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.

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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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New Data Protection Strategies


One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets.

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