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Documents related to » etl data warehousing analysis


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

etl data warehousing analysis  issue is whether the ETL tool moves all the data through its own engine on the way to the target, or can be a proxy and move the data directly from the source to the target. Selection of the business intelligence tool(s) requires decisions such as: Will multi-dimensional analysis be necessary, or does the organization need only generalized queries? Not all warehouse implementations require sophisticated analysis techniques such as data mining (statistical analysis to discover trends in the data), data 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

etl data warehousing analysis  extract, transform, and load (ETL) development. It is important not to underestimate the importance of data integration, as the way data is integrated into a data warehouse or BI solution is the essence of that system. If a scorecard is developed to measure an organization''s sales metrics and the source data is not accurate, the key performance indicators (KPIs) set and reported on will be meaningless. Administration and Technology The administration and technology track identified and covered topics Read More...
Computer Associates Splashes Into the Data Warehousing Market with Platinum Technology Acquisition
Computer Associates DecisionBase is an Extract/Transform/Load tool designed to help in the population and maintenance of data warehouses. First released in

etl data warehousing analysis  of vendors in the ETL market in the mid-1990''s was small, comprised of basically four companies (Prism, Carleton, Evolutionary Technologies, Trinzic) plus some modest offerings from IBM. In the past four years, the space has become very crowded, with over fifty vendors competing in various market niches (e.g. specializing in access to VSAM databases). Four vendors still primarily control the general market, including Ardent, Computer Associates, Informatica, and Sagent, with some offerings from IBM and 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

etl data warehousing analysis  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. These functions are driven by a number of algorithms that apply AI and fuzzy logic techniques. CGI is a leading provider of IT services. With a base or about 80% of sales in Canada, the billion dollar company is making a move to establish a larger presence in the U.S. CGI has close ties with 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

etl data warehousing analysis  extract, transform, and load (ETL) process in a data warehousing system extracts records from data source(s), transforms them using rules to convert data into a form that is suitable for reporting and analysis, and finally loads the transformed records into the destination (typically a data warehouse or data mart). Data cleansing is an integral part of the transformation process and enforces business and schema rules on each record and field. Data cleansing involves the application of quality screens 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

etl data warehousing analysis  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...
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

etl 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...
Data Quality Strategy: A Step-by-Step Approach
To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how

etl data warehousing analysis  Quality Strategy: A Step-by-Step Approach To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality. Read More...
Backing up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices
This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions

etl data warehousing analysis  up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions to the challenges of protecting distributed business data by establishing a private cloud/enterprise cloud. Learn which best practices can ensure business continuity throughout an organization with a distributed information Read More...
In-memory Computing: Lifting the Burden of Big Data
Business data is growing at an unprecedented speed, and organizations of all sizes, across all industries, have to face the challenge of scaling up their data

etl data warehousing analysis  memory Computing: Lifting the Burden of Big Data Business data is growing at an unprecedented speed, and organizations of all sizes, across all industries, have to face the challenge of scaling up their data infrastructure to meet this new pressure. Advances in server hardware and application design have led to a potential solution: in-memory computing. Read Aberdeen''s Analyst Insight report and see how in-memory computing can address two of the three Vs of big data. Read More...
Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations
While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as

etl data warehousing analysis  Data Analytics: Profiling the Use of Analytical Platforms in User Organizations While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as organizations seek to store and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers. This report examines the rise of big data and the use of analytics to mine that data. Read More...
The Data Explosion
RFID and wireless usage will drive up data transactions by ten fold over the next few years. It is likely that a significant readdressing of the infrastructure

etl data warehousing analysis  Data Explosion Introduction Traffic on the World Wide Web continues to grow. Traffic on your S mall S mart F ast devices continues to grow. Ok, I admit it. I bought the cell phone that takes pictures. I didn''t know if it was useful; but being a technophile, I went for it. And rapidly it all came to me! I tried on a new cool jacket ... I crooned over it ... but for that much money, I wasn''t sure. Should I really buy this? Enter the pic in my cell phone! We chicks have our honor guard. You know those Read More...
TCO Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center
Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30

etl data warehousing analysis  Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30% compared with traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the 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

etl data warehousing analysis  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 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...

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