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Documents related to » bi data warehouse architecture


The Data Warehouse Institute (TDWI) Conference in San Diego: The Agile Approach to Business Intelligence (BI)
Next month a TDWI World Conference will be taking place in San Diego, California. What’s so special about this conference anyway? The answer is simple:  the

bi data warehouse architecture  The Conference and Agile BI Besides the data warehousing and BI core concept courses, there will be an interesting myriad of events taking place in the conference to address possible ways to apply the agile methodology to BI solutions. It will begin with presentations from Wayne Eckerson (“ The Secrets of Creating an Agile, Adaptable BI Environment ”) and Ken Collier (“ Katabatic Winds of Business Intelligence ”), and there will be a promising set of training sessions given by Ralph Huges, an 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

bi data warehouse architecture  data warehouse solution for BI. This product''s features include data compression, partitioned tables, parallelism capabilities, and change data capture. The scalable integration services tools enable fast ETL operations and connectivity to non-SQL server data sources. Netezza Netezza Data Warehouse Appliances is a combination of software and hardware tools designed for analytical processing of very large amounts of data. Netezza''s architecture is massively parallel processing (MPP)-based and uses a Read More...
Distilling Data: The Importance of Data Quality in Business Intelligence
As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence

bi data warehouse architecture  primary purpose of a BI solution is to provide a business with the necessary information to support better decision making. This requires the integration of data within and external to an enterprise. A sound data quality strategy protects an enterprise from inconsistencies and anomalies that arise from the complexity of integrating multiple systems and from hidden problems that are uncovered only through sophisticated analysis techniques. Data quality solutions provide organizations with the ability to Read More...
Unlocking Hidden Value from Investments in SAP NetWeaver Business Warehouse
Extending the capabilities and value of SAP NetWeaver Business Warehouse is a concern for users. To improve data use and fact-based decision making, and reduce

bi data warehouse architecture  Data Warehousing Software | BI Data Warehousing | Data Warehousing Companies | Enterprise Data Warehousing | Data Warehousing Information | Data Warehousing Technology from SAP | Cognos Data Warehousing | Data Warehousing Consulting | SAP Netweaver White Paper | Technology Evaluation Software White Paper | TEC Evaluation | TEC BI Evaluation Software | Data Warehousing Best Practices | ETL in Data Warehousing | Data Warehousing White Papers | Data Warehousing Methodology | Data Warehousing Strategy | New Read More...
Ask the Experts Question: Do Organizations Really Need a Physical Data Warehouse Structure?
We recently had a question from one of our readers (through our Ask the Experts page) discussing QlikView’s approach to data collection.Reader’s Question

bi data warehouse architecture  approach to deliver in-memory BI and data analysis capabilities. Other vendors like SAP , Teradata , and even Microsoft with its Project Gemini , are catching up with in-memory technologies. We think it’s definitely possible to apply in-memory technologies to BI, and in the near future we will be seeing more and more use of this kind of technology. But data will still need a place where it can be loaded from (i.e., a data warehouse), and I’m not sure that loading it directly from the operational 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

bi data warehouse architecture  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. Read More...
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

bi data warehouse architecture  have buy-in from your biggest customers because ultimately you are trying to service those customers better than the competition. Evaluate Your Processes and Personnel In addition to uncovering your top twenty percent, you should also evaluate your processes and personnel. Get some more blank sheets of paper, write the name of each of your processes on top and document how they work. Include all processes such as receiving, picking, putaway, inventory control, will call, order entry, purchasing, and even Read More...
BI Maturity and Software Selection Perspectives
While new technology trends are invading the business intelligence (BI) space, technology shifts and hype do not necessarily equate to the ability to exploit

bi data warehouse architecture  To select a best-fit BI solution, an organization needs to be able to realistically assess the maturity of its BI infrastructure. This allows them to discover where they are, what their BI requirements are, and how to determine the best BI solution or strategy. Download the full report now. Read More...
MSI Data


bi data warehouse architecture  Data Read More...
Architecture Evolution: Service-oriented Architecture versus Web Services
Collaboration and interoperability are critical where multiple business units reside under one larger corporation, or where there is a requirement to integrate

bi data warehouse architecture  software vendor makes a big, expensive commitment to the technological underpinning it has to select at the beginning of the project (for example, programming language, operating system platform, and data access technology). Often, the selected language and the data access technology are tightly integrated and not easily separated later. If one does not count some open-source proponents and pioneers and IBM System i zealots (formerly AS/400 —see Server Platform Situational Analysis: IBM AS/400 ), there Read More...
A Solution to Data Capture and Data Processing Challenges
Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the

bi data warehouse architecture  Solution to Data Capture and Data Processing Challenges Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the right information to the right people at the right time—but is your data capture process as efficient as it could be? Learn about the issues surrounding data capture and data processing, and about a solution designed to help you address specific processing problems. Read More...
Simulation In The Warehouse
Simulation can remedy one time and ongoing problems in the warehouse. Learn about the technology of computer stimulation and how it can benefit senior

bi data warehouse architecture  storage,catalyst,simulation,management,logistic 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

bi data warehouse architecture  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. Read More...

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