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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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 etl huge data warehouse

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

Warehouse Management Systems (WMS)

A warehouse management system (WMS) should provide database and user-level tools in order for a company to optimize its storage facilities while at the same time providing user level task direction and activity support. The WMS should enable warehouse operators to optimize pick, put-away, and replenishment functions by employing powerful system logic to select the best locations and sequences. 

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Documents related to » etl huge data warehouse

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 huge data warehouse  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

Epicor Acquires QuantiSense for Retail Analytics


Epicor acquires QuantiSense, a provider of cloud and on-premise packaged analytic solutions for the retail industry, in a deal that is expected to bolster Epicor's retail analytics capabilities.

etl huge data warehouse  and extract, transform, load (ETL) tools designed exclusively for retailers. On the other hand, QuantiSense Playbooks automates the process of identifying and prioritizing retail exceptions such as imminent stockouts and overstocks, allowing retailers to efficiently solve problems and capitalize on opportunities.   QuantiSense customers include about 30 leading global specialty and department store brands such as Hallmark Cards, Men''s Warehouse, Restoration Hardware, and Urban Outfitters. Moreover, the Read More

Informatica PowerCenter 5 Enables Enterprise Data Integration


Informatica Corporation’s Informatica PowerCenter 5 is a platform for integrating data to be deployed in e-Business applications, analytic applications and data warehouses, including a wide range of data sources, from enterprise resource planning (ERP) systems such as SAP R/3 and PeopleSoft, to web logs and Siebel applications. Market validation of its offerings is shown in a record Q4 of 2000, with a 150% increase in revenue over the previous year.

etl huge data warehouse  PowerCenter 5 Enables Enterprise Data Integration Informatica PowerCenter 5 Enables Enterprise Data Integration M. Reed - April 5, 2001 Event Summary Informatica Corporation (NASDAQ: INFA), a provider of e-Business analytic software, has announced the availability of Informatica PowerCenter 5 , an enterprise data integration platform for the deployment and management of analytic applications and data warehouses. The vendor states that the Informatica PowerCenter 5 suite is designed to be a Read More

FRx Poised to Permeate Many More General Ledgers Part Three: Market Impact continued


While there is an opportunity for FRx to become a main pillar within the entire Microsoft BI product strategy, there is not yet an overall cohesive BI/CPM strategy or architecture to guide the product plans to an integrated BI solution set.

etl huge data warehouse  extract, transform and load [ETL] tools, dashboards/executive information system [EIS]) to business process management (BPM) applications and scorecard products. Thus, CPM is the evolutionary combination of technology and philosophy, building on the foundation of technology and applications that many enterprises will have likely already implemented. The demand for these applications lies in the fact that they incrementally add value to already installed business applications, even the legacy ones, to a Read More

A Definition of Data Warehousing


There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.

etl huge data warehouse  are currently over 50 ETL tools on the market. The data acquisition phase can cost millions of dollars and take months or even years to complete. Data acquisition is then an ongoing, scheduled process, which is executed to keep the warehouse current to a pre-determined period in time, (i.e. the warehouse is refreshed monthly). Changed Data Capture: The periodic update of the warehouse from the transactional system(s) is complicated by the difficulty of identifying which records in the source have changed Read More

Data Visualization: When Data Speaks Business


For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages of IBM Cognos Business Intelligence for improving the data visualization and data delivery process.

etl huge data warehouse  data visualization, IBM Cognos Business Intelligence, business intelligence, data delivery, data visualization best practices Read More

Tailoring SAP Data Management for Companies of All Sizes


The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are relying on manual operations, which are inherently error-prone, and time- and resource-intensive. Today's environment requires enterprise-class automation to overcome these challenges of data management. Learn about one solution that can help improve SAP data management.

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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.

etl huge data warehouse  big data, operational analytics, big data integration, big data strategy, analytical data platforms. hybrid data ecosystem Read More

Overall Approach to Data Quality ROI


Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI.

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Warehouse Management Systems: Pie in the Sky or Floating Bakery?Part Two: The Pareto Principle, Processes, and People: Assessing Your Warehouse Management System Needs


To ensure your warehouse management system is implemented as painlessly as possible, you must assess your warehouse situation before you decide on a warehouse solution. Using the Pareto Principle, where a minority of inputs yields the majority results; examining your processes; evaluating your personnel; monitoring the progress of implementation; and testing are the best ways to ensure both a successful launch and long term return on investment.

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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.

etl huge data warehouse  big data,data management,analytics,SAP 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.

etl huge data warehouse   Read More

Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

etl huge data warehouse   Read More