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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
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

data warehousing analysis etl  of products for deploying data warehousing solutions, such as Exadata Storage Server (based on the HP ProLiant DL180 G5 server), HP Oracle Database Machine designed for multiterabyte data warehouses, and the Oracle Warehouse Builder integration tool that supports advanced data loads and data capture for low latency databases. They also offer other products like Oracle Partitioning, which can lower query times and increase data availability. Teradata Among other products offered, Terada Database 12 is an 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
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
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
Operationalizing the Buzz: Big Data 2013
The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the

data warehousing analysis etl  the Buzz: Big Data 2013 The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and 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

data warehousing analysis etl  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. 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

data warehousing analysis etl  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
Implementing Energy-Efficient Data Centers
But in the white paper implementing energy-efficient data centers, you''ll learn how to save money by using less electricitywhether your data cente...

data warehousing analysis etl  Energy-Efficient Data Centers Did you realize that your data center(s) may be costing you money by wasting electricity ? Or that there are at least 10 different strategies you can employ to dramatically cut data center energy consumption ? The fact is, most data centers are not designed with energy efficiency in mind. But in the white paper Implementing Energy-efficient Data Centers , you''ll learn how to save money by using less electricity—whether your data centers are still in the design Read More
New Data Protection Strategies
One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased

data warehousing analysis etl  Data Protection Strategies One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets. Read More
MSI Data


data warehousing analysis etl  Data 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

data warehousing analysis etl  number of articles about data quality. ( Poor Data Quality Means A Waste of Money ; The Hidden Role of Data Quality in E-Commerce Success ; and, Continuous Data Quality Management: The Cornerstone of Zero-Latency Business Analytics .) This time our focus takes us to the specific domain of data quality within the customer relationship management (CRM) arena and how applications such as Interaction from Interface Software can help reduce the negative impact that poor data quality has on a CRM objective. Read More
Data Migration Best Practices
Large-scale data migrations can be challenging, but with the appropriate planning—and through careful execution of that plan—organizations can greatly reduce

data warehousing analysis etl  Migration Best Practices Large-scale data migrations can be challenging, but with the appropriate planning—and through careful execution of that plan—organizations can greatly reduce the risks and costs associated with these projects. This paper offers a handy checklist of issues to consider before, during, and after migration. Read More
2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry

data warehousing analysis etl  Big Data Opportunities Survey While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unisphere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses Read More

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