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Software Functionality Revealed in Detail
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 etl implementing real time data warehousing

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 » etl implementing real time data warehousing

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.

etl implementing real time data warehousing  only in doing more ETL processes. The near real-time approach has some challenges such as increasing the downtime frequency; the pressure to decrease downtime period duration; and avoiding inconsistency in data results. If there is no actual need for a real-time data warehouse solution, a good option could be to implement a near real-time data warehouse. The Real-time Data Warehouse A real-time data warehouse enables data to be stored at the very moment it is generated and it is immediately captured, 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.

etl implementing real time data warehousing  Integration Services (SSIS) provides ETL capabilities. In addition, data can be transformed without the use of staging tables, thereby reducing data latency. Both structured and unstructured data can be extracted and converted between various types of data such as numeric and string (and so on), and data audits can be performed. Also, to account for slowly changing dimensions (SCDs), SSIS has a built-in wizard. Analysis Services provides data mining and OLAP capabilities to enable users to identify and 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?

etl implementing real time data warehousing  management approaches. EAI and ETL can be thought of as push technologies, and EII can be regarded as a pull mechanism that seeks and finds data, as needed and in near real-time, by creating an enterprise-wide abstraction semantic layer for standardized access to any corporate data source. The ability to provide appropriate BI without having to adapt a DW for specific decision support tasks is sometimes referred to by EII vendors as on-demand BI . Companies can certainly benefit from accelerating BI Read More

Optimizing Gross Margin over Continously Cleansed Data


Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards are automated data cleansing, systematic management of data processes, and margin optimization. Real dollars can be reclaimed in the supply chain by making certain that every byte of product information is accurate and synchronized, internally and externally.

etl implementing real time data warehousing  Data Product PDM | ETL Product Data | ETL Product Data Analyst | ETL Product Data Base | ETL Product Data Feed | ETL Product Data File | ETL Product Data Information | ETL Product Data Mastering | ETL Product Data Services | Read More

Access to Critical Business Intelligence: Challenging Data Warehouses?


There is a perception that if business users are given access to enterprise databases and raw query tools, they will create havoc in the system, which is a possibility—unless the business intelligence (BI) product developer understands the potential problem and addresses it as a business-critical factor.

etl implementing real time data warehousing  recent purchase of the ETL leader Ascential . In the meantime, the virtual data unification/EII preaching vendors must strive to educate the market and gain a critical mass of customers for the approach. The successful ones might, for the time being, be those that position their tools to complement, rather than replace, conventional data warehousing. Some recent surveys do cite a notable percentage of users mentioning the lack of centralized DW as a key reason for postponing the adoption of analytic Read More

Meet PCI DSS Compliance Requirements for Test Data with Data Masking


Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more.

etl implementing real time data warehousing   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.

etl implementing real time data warehousing  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

Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more agile architectures that can confront the new challenges much easier.

etl implementing real time data warehousing  BI, business intelligence, operational intelligence, Hadoop, NoSQL, self-service BI, data virtualization, big data, on-demand data integration, lean data integration, JBoss Data Virtualization 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.

etl implementing real time data warehousing   Read More

2013 Big Data Opportunities Survey


While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unisphere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses and a discussion of the results.

etl implementing real time data warehousing  big data,analytics,Unisphere Research,big data survey,data manager survey,big data challenges,big data initiatives Read More

Customer Data Integration: A Primer


Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a customer relationship management initiative can help provide organizations with a successful framework to manage data on a continuous basis.

etl implementing real time data warehousing  Data Integration: A Primer Originally published - August 22, 2006 Introduction Implementing a customer data management system can be the difference between success and failure in terms of leveraging an organization''s customer relationship management (CRM) system. Since customers drive profitability, organizations need a way to provide their employees with a single view of the customer and to provide that customer with above-average customer service. Unfortunately, this is not always the case. Read More

ESG - Riverbed Whitewater: Optimizing Data Protection to the Cloud


Riverbed Whitewater leverages WAN optimization technology to provide a complete data protection service to the cloud. The appliance-based solution is designed to integrate seamlessly with existing backup technologies and cloud storage provider APIs. Read this ESG Lab report on hands-on testing of the Riverbed Whitewater appliance for ease of use, cost-effective recoverability, data assurance, and performance and scalability.

etl implementing real time data warehousing  the cloud,data protection,cloud service,data assurance,data protection software,cloud computing service providers,service cloud,data quality assurance,cloud service providers,cloud storage service,data protection virus,in the cloud,cloud backup service,data protection manager,continuous data protection Read More

Data Masking: Strengthening Data Privacy and Security


Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you.

etl implementing real time data warehousing   Read More

Demystifying Data Science as a Service (DaaS)


With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white paper to find out more about how data SaaS is set to become a vital part of business intelligence and analytics, and how India will play a role in this trend.

etl implementing real time data warehousing  data science, big data, analytics, data SaaS, data scientist, India, data as a service, real-time data, data analytics 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.

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