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Documents related to » data warehousing analysis etl


The Necessity of Data Warehousing
An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding

data warehousing analysis etl  Necessity of Data Warehousing The Necessity of Data Warehousing M. Reed - August 2, 2000 Why the market is necessary Data warehousing is an integral part of the information age . Corporations have long known that some of the keys to their future success could be gleaned from their existing data, both current and historical. Until approximately 1990, many factors made it difficult, if not impossible, to extract this data and turn it into useful information. Some examples: Data storage peripherals such 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

data warehousing analysis etl  Definition of Data Warehousing Biographical Information Bill Inmon Bill Inmon is universally recognized as the father of the data warehouse. He has over 26 years of database technology management experience and data warehouse design expertise, and has published 36 books and more than 350 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing data warehouses and has been a keynote speaker for every major computing assoc 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

data warehousing analysis etl  relational databases and for data mining. They became skilled at working with masses of data and embedding data analysis into traditional applications. Purchased 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 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

data warehousing analysis etl  When embarking on a data warehousing or business intelligence project, it is essential for organizations to emphasize the quality of data that is used for analysis and subsequent decision making. As data captured from a multitude of sources makes its way to an enterprise data warehouse or data marts, a data quality framework creates a screening process that measures the purity of the data and corrects any inconsistencies found. This article walks the reader through a typical data quality strategy by 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

data warehousing analysis etl  for Business Intelligence and Data Warehousing Information The Data Warehousing Institute ( TDWI ) hosts its quarterly World Conference in cities across the US to help organizations involved in data warehousing, business intelligence (BI), and performance management, by giving them access to industry experts, and providing impartial classes related to topics pertinent to the industry. As the industry grows, organizations are faced with questions about how to best access their data to drive profits and mee Read More...
Data Pro Accounting Software
Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the

data warehousing analysis etl  Pro Accounting Software Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the corporation has always been to develop and market a full line of accounting software products for a wide range of market segments, on a broad spectrum of operating systems environments such as DOS, Windows and UNIX. Read More...
Data Quality Trends and Adoption
While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ

data warehousing analysis etl  of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers. Read More...
Rover Data Systems
Rover Data Systems, Inc. was founded with the express purpose of providing an Enterprise Software Solution to address the needs of small and medium-sized

data warehousing analysis etl  Data Systems Rover Data Systems, Inc. was founded with the express purpose of providing an Enterprise Software Solution to address the needs of small and medium-sized Manufacturers and Distributors. During the time that Rover Data Systems has been in business it has accumulated a satisfied customer base, all running their business functions on Millennium III (M3) software. These companies range from the small ( Read More...
Data Management and Analysis
From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it

data warehousing analysis etl  perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As). For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most Read More...
Considerations for Owning versus Outsourcing Data Center Physical Infrastructure
When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both

data warehousing analysis etl  for Owning versus Outsourcing Data Center Physical Infrastructure When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life Read More...
Data Enrichment and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics
Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident

data warehousing analysis etl  and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident decisions and take the right actions, you need more than just software—you also need the right data. This white paper discusses a solution to help ensure that your applications process reliable data so that your spend analyses and supplier risk assessments are 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

data warehousing analysis etl  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. Read More...
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

data warehousing analysis etl  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. Read More...
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

data warehousing analysis etl  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 Read More...

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