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Continuous Data Quality Management: The Cornerstone of Zero-Latency Business Analytics
No matter how well an enterprise implements a CRM, ERP, SCM, Business Intelligence, or Data Warehouse project, poor data quality can destroy its utility and

data level zero  if-then logic of certain data objects. For instance, if an employee is of Level 2, then he or she should receive a raise of 5%, unless the employee's total pay is greater than $55,000/year. Functional Dependencies . These rules measure the invariants across columns of data. For example, for every customer number the data should always contain the same customer name. Structural Integrity Structural integrity checks examine whether the data is complete on a macro level. These checks ensure that when you Read More
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Documents related to » data level zero


Guidelines for Specification of Data Center Power Density
Conventional methods for specifying data center density don’t provide the guidance to assure predictable power and cooling performance for the latest IT

data level zero  required Table 2 ' Data required at the row level Data Units Description Primary use # rack locations # The number of rack locations in a row. Includes all locations, some of which may ultimately be consumed by power or cooling equipment, depending on architecture To determine the total power and cooling requirement for the row Rack average in row kW / rack The average per-rack power density exhibited by IT racks in a specified row. Must be specified for each row in the room To determine the bulk power Read More
Business Basics: Unscrubbed Data Is Poisonous Data
Most business software system changes falter--if not fail--because of only a few root causes. Data quality is one of these root causes. The cost of high data

data level zero  Unscrubbed Data Is Poisonous Data Introduction A manufacturing company experienced continually increasing overhead costs in its purchasing and materials departments. It also began to see increased inventory levels and production line delays. A consulting firm was brought in to analyze the company's materials management processes and the level of competence of its materials and procurement staff. After mapping the entire process, from the creation of a bill of materials through post-sales service and Read More
Continuous Data Quality Management: The Cornerstone of Zero-Latency Business Analytics Part 2: One Solution
Most enterprises fight fires with axes, fire hoses, trucks, and hordes of firemen, but the CDQM approach is a smoke detector. It’s far less expensive to put a

data level zero  Data Quality Management: The Cornerstone of Zero-Latency Business Analytics Part 2: One Solution Implementing A CDQM Application It is impossible to improve that which cannot be measured. A CDQM (Continuous Data Quality Management) tool provides a real-time, up-to-date scorecard to measure data quality within the enterprise. By checking data quality in real-time, data fires can be detected when they are just starting, before any real damage has occurred. Most enterprises fight fires with axes, Read More
Best Practices for a Data Warehouse on Oracle Database 11g
Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW

data level zero  sizes help to facilitate data compression as Oracle does its compression at the database block level by eliminating duplicate values within a block. db_file_multiblock_read_count SQL parallel execution is generally used for queries that will access a lot of data, for example when doing a full table scan. Since parallel execution will by-pass the buffer cache and access data directly from disk you want each I/O to be as efficient as possible, and using large I/Os is a way to reduce latency. Set 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.

data level zero  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 each step, 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

data level zero  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
Data Masking: Strengthening Data Privacy and Security
Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating

data level zero  Masking: Strengthening Data Privacy and Security Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you. Read More
Data Management and Business Performance: Part 1-Data
Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a

data level zero  BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of their data as well as to ways to capture the most valuable information for improved decision making and business performance. Let’s look at what the data tells us. Below is a Pareto chart based on data from Technology Evaluation Centers (TEC) on what software users consider to be the most popular functionality features for BI 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 level zero  Data: The Importance of Data Quality in Business Intelligence Originally Published - October 20, 2008 The zeal to get as much business data to the user as soon as possible often prevails over the establishment of processes that control the quality of data. Low data quality standards can lead to bad business decisions and missed opportunities. Even with a data warehouse that is well designed and equipped with the best tools for business intelligence (BI), users will encounter inefficiency and frustration Read More
Data Management Wish List: IT Is Open to Big Changes
Data management, access, and analysis haven’t always received the same amount of consideration, or respect, as the corporate applications that generate and

data level zero  Open to Big Changes Data management, access, and analysis haven’t always received the same amount of consideration, or respect, as the corporate applications that generate and consume the data. In recent years, however, information technology (IT) leaders have focused much more attention on their organizations’ data management platforms and capabilities. Download this white paper to get a better picture of the current data management landscape. Read More
Microsoft says OLE for Data Mining: Is it Bull?
Microsoft released a new version of OLE DB (Object Linking and Embedding Database, based on Microsoft’s Component Object Model or COM) which supports a

data level zero  says OLE for Data Mining: Is it Bull? Event Summary REDMOND, Wash., March 7 /PRNewswire/ -- Microsoft Corp. (Nasdaq: MSFT) announced the beta release of the OLE DB for Data Mining specification, a protocol based on the SQL language, that provides software vendors and application developers with an open interface to more efficiently integrate data mining tools and capabilities into line-of-business and e-commerce applications. A dozen leading data mining and business intelligence vendors 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

data level zero  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
10 Errors to Avoid When Building a Data Center
In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you're going through the data center...

data level zero  Avoid When Building a Data Center Proper data center commissioning can help ensure the success of your data center design and build project. But it's also a process that can go wrong in a number of different ways. In the white paper Ten Errors to Avoid when Commissioning a Data Center , find out which mistakes to avoid when you're going through the data center commissioning process. From bringing in the commissioning agent too late into the process, to not identifying clear roles for commissioning team Read More

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