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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

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

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

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

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.

etl implementing real time data warehousing  used to limit the ETL processes to nodes 1 and 2 in the cluster and Ad-hoc queries to node 3 and 4. Workload Monitoring In order to have an overall view of what is happening on your system and to establish a baseline in expected performance you should take hourly AWR or statspack reports. However, when it comes to real-time system monitoring it is best to start by checking whether the system is using a lot of CPU resources or whether it is waiting on a particular resource and if so, what is that Read More

Time and Expense Management Applications


Organizations of all sizes are tasked with increasing efficiency and revenues in a timely manner. Naturally, this leads them to consider automation. The critical question then becomes: is it more beneficial to build a time and expense management solution or to buy one? Overwhelmingly, organizations have proven that buying a solution results in greater value and success.

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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

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

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.

etl implementing real time data warehousing  Data Quality: A Seven-step Plan for Any Size Organization Melissa Data’s Data Quality Suite operates like a data quality firewall – instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer 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.

etl implementing real time data warehousing   Read More

Big Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone


Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and decision support.

etl implementing real time data warehousing  big data, predictive analytics, real-time analytics, embedded analytics, business analytics, IBM SPSS solutions, IBM SPSS predictive analytics tools, SPSS predictive software, predictive software Read More

Data Quality: Cost or Profit?


Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and company policies that set expectations and establish data management procedures, we will explore applications and tools that help reduce the negative impact of poor data quality. Some CRM application providers like Interface Software have definitely taken data quality seriously and are contributing to solving some data quality issues.

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Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever


Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility.

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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.

etl implementing real time data warehousing  Big Data,Big Data architecture,Big Data challenges,Big Data system,Big Data technology 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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