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Discrete Manufacturing (ERP)
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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...
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

etl data warehousing analysis  data warehouse design. All ETL data warehouse processes were originally designed to be executed in batch mode, during previously scheduled downtimes. All operational data from distinct sources (e.g. ERP systems) was extracted, cleansed under a stage repository, and loaded into the data warehouse over long periods of time, mostly at night. These processes can take minutes or hours, depending on the volume of data being uploaded to the data warehouse. With the pressure to load more recent data into the 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...
Linked Enterprise Data: Data at the heart of the company
The data silos of today''s business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet

etl data warehousing analysis  Enterprise Data: Data at the heart of the company The data silos of today''s business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, 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...
The Data Warehouse RFP
If you don’t have a data warehouse, you’re probably considering drafting a request for proposal (RFP) to screen vendors and ensure that your receive

etl data warehousing analysis  Data Warehouse RFP If you don’t have a data warehouse, you’re probably considering drafting a request for proposal (RFP) to screen vendors and ensure that your receive satisfactory information about the features of various hardware and software and their price. Writing an effective RFP that is well structured and includes different metrics will ensure that you receive the information you need and will make you look good. Read More...
Meet PCI DSS Compliance Requirements for Test Data with Data Masking
Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a

etl data warehousing analysis  PCI DSS Compliance Requirements for Test Data with Data Masking Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more. 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...
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

etl data warehousing analysis  Quality: Cost or Profit? Market Overview In the past year, TEC has published a 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 Read More...
How Companies Use Data for Competitive Advantage
Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage.

etl data warehousing analysis  Companies Use Data for Competitive Advantage How Companies Use Data for Competitive Advantage Today, many businesses find they are under siege dealing with an explosion of data. Yet the best performing companies are mastering their data—and using it for competitive advantage. How are they able to accomplish this? What best practices, approaches, and technologies are they employing? Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage . In this Economist Business 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...

etl data warehousing analysis  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 st Read More...
Data Center Automation
With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and

etl data warehousing analysis  Center Automation With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands. Read More...

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