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Discrete Manufacturing (ERP)
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Documents related to » olap data warehousing analysis


Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio
Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the

olap data warehousing analysis  create and populate physical OLAP cubes. The underlying data is held as low-level transactional data in standard relational structures, but to the application layer it appears as a “virtual cube.” By virtualizing the cube structures, organizations can still get a holistic view of their data but with zero latency given that large virtual cubes can be created within just seconds. Moreover, users can benefit from one single version of the truth; instead of contending with multiple physical cubes that 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

olap data warehousing analysis  of OLAP is that OLAP can only answer questions you know to ask, data mining answers questions you didn''t necessarily know to ask. Data Visualization Tools: Tools that show graphical representations of data, including complex three-dimensional data pictures. The theory is that the user can see trends more effectively in this manner than when looking at complex statistical graphs. Some vendors are making progress in this area using the Virtual Reality Modeling Language (VRML). Metadata Management: Read More...
Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and

olap data warehousing analysis  Database 11g for Data Warehousing and Business Intelligence Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data. Read More...
Customer Relationship Analysis Firm Extends Reach
thinkAnalytics signs a partnering agreement with one of the largest information technology services companies in North America. Why does CGI expect

olap data warehousing analysis  by Gentia Software, an OLAP (On-Line Analytical Processing) specialist, in 1998; thinkAnalytics was recently launched as a separate company. The company''s product suite comprises a variety of analytic tools that sit on top of common middleware and analysis functions. The middleware functions do not replace traditional ETL (Extract/Transform/Load) functions but rather augments them to provide intelligent data cleanup. Data cleanup encompasses such functions as null replacement, data scaling and deduping. Read More...
A One-stop Event for Business Intelligence and Data Warehousing Information
The Data Warehousing Institute (TDWI) hosts quarterly World Conferences to help organizations involved in data warehousing, business intelligence, and

olap data warehousing analysis  included online analytical processing (OLAP), dashboards, scorecards, and data mining, as well as analytic applications. This focus allows organizations to gain insight into areas within BI and the different aspects of insight that analytics can provide. Organizations that require a subset of BI can identify how their needs can be met, by identifying requirements based on the topics presented. Additionally, they can take advantage of the trade show to identify those vendors that meet their needs, or Read More...
Unified Data Management: A Collaboration of Data Disciplines and Business Strategies
In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration

olap data warehousing analysis  Data Management: A Collaboration of Data Disciplines and Business Strategies In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts. Read More...
Fundamentals of Managing the Data Center Life Cycle for Owners
Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and

olap data warehousing analysis  of Managing the Data Center Life Cycle for Owners Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and available over the course of its life span. For each phase of the data center’s life cycle, proper care and action must be taken to continuously meet the business needs of the facility. This paper describes the five phases of the data center life cycle, identifies key tasks and pitfalls, and Read More...
The Role of Cloud in Your Storage and Data Protection Strategy
Find out in Making Cloud an Integral Part of Your Enterprise Storage and Data Protection Strategy.

olap data warehousing analysis  Role of Cloud in Your Storage and Data Protection Strategy The Role of Cloud in Your Storage and Data Protection Strategy Cloud storage is gaining in popularity with companies seeking a more efficient, dynamic, and responsive IT environment. But what are the issues and challenges involved? And how do you make sense of a bewildering maze of cloud storage options? Find out in Making Cloud an Integral Part of Your Enterprise Storage and Data Protection Strategy . In this practical IDC report, you''ll learn Read More...
Addressing the Complexities of Remote Data Protection
As companies expand operations into new markets, the percentage of total corporate data in remote offices is increasing. Remote offices have unique backup and

olap data warehousing analysis  the Complexities of Remote Data Protection Because data protection is a concern for organizations of all sizes, IBM offers remote data protection for the enterprise, as well. This high performance and easy-to-use service delivers consistent and cost-effective data protection without increased network investment. Source: IBM Resources Related to Addressing the Complexities of Remote Data Protection : Continuous Data Protection (CDP) (Wikipedia) Addressing the Complexities of Remote Data Read More...
Beware of Legacy Data - It Can Be Lethal
Legacy data can be lethal to your expensive new application – two case studies and some practical recommendations.

olap data warehousing analysis  of Legacy Data - It Can Be Lethal Beware of Legacy Data It Can Be Lethal Featured Author - Jan Mulder - August 23, 2002 Introduction The term legacy is mostly used for applications. For example, according to the Foldoc dictionary, legacy is: A computer system or application program which continues to be used because of the cost of replacing or redesigning it and often despite its poor competitiveness and compatibility with modern equivalents. The implication is that the system is large, monolithic Read More...
Scalable Data Systems
Scalable Data Systems is one of APAC’s most experienced Microsoft Dynamics AX partners. The company manages a wide variety of implementations, from rapid fast

olap data warehousing analysis  Data Systems Scalable Data Systems is one of APAC’s most experienced Microsoft Dynamics AX partners. The company manages a wide variety of implementations, from rapid fast-track projects to complex integration and development projects. Scalable has over 25 years of experience developing best-practice industry solutions and individual horizontal modules. Scalable provides dedicated industry solutions for manufacturing and supply chain/distribution, with verticals for food and beverage, chemicals, Read More...
Don''t Be Overwhelmed by Big Data
Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect

olap data warehousing analysis  t Be Overwhelmed by Big Data Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Read More...
2012 Business Data Loss Survey results
This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download

olap data warehousing analysis  Business Data Loss Survey results This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now. Read More...
Garbage in, Garbage out: Getting Good Data out of Your BI Systems
Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems.

olap data warehousing analysis  in, Garbage out: Getting Good Data out of Your BI Systems Garbage in, garbage out. Poor quality data leads to bad business decisions. You need high quality data in your business intelligence (BI) system to facilitate effective analysis—to make the right decisions at the right time. But how do you achieve this? Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems . In this Focus Brief , you''ll learn about the steps in the data delivery cycle, the problems can occur at Read More...
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

olap data warehousing analysis  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. Read More...

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