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Documents related to » olap perspectives on data warehousing


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

olap perspectives on data warehousing  Data Warehouse Definition | OLAP | Business Intelligence | Huge Data Warehouse | Data Warehouse Appliance | Premier Data Warehouse Corporation | Definition of Data Warehousing | Valuable Data Integration | Enterprise Data Warehousing | Contains Information on Data Warehousing | Building the Data Warehouse | Term Data Warehouse Lists | Expensive Data Warehouse | Data Warehousing Provides | Data Warehouse Appliance Consists | Data Warehouse Info | Implementing Data Warehouse | Data Warehouse Process | Read More
Business Performance Management Basics: An Overview of Business Performance Management and Its Benefits to the Organization
Business performance management (BPM) includes setting key performance indicators, using data mining to discover data patterns and using software to help drive

olap perspectives on data warehousing  BI online analytical processing (OLAP) cubes, sales data can be reflected multidimensionally with rolling sales data over a three-year period. This, however, pales in comparison to dashboard functionality, which allows a sales manager to see up-to-date sales figures in real time, and to compare them against predefined metrics. The sales manager can then drill down on the data to access and analyze operational data in order to determine a plan of action. KPIs vary depending on the function of an Read More
Contemporary Business Intelligence and Its Main Components
Business intelligence (BI) represents the tools and systems that play a key role in the strategic planning process by allowing a company to manipulate corporate

olap perspectives on data warehousing  representations for each combination. OLAP is often used in data mining tools, which is a class of database applications that look in a group of data for hidden patterns that can be used to predict future behavior. For example, data mining can help retail companies find customers with common interests. However, the term is commonly misused to describe software that presents data in new ways. True data mining software does not just change the presentation, but actually discovers previously unknown Read More
Business Intelligence Status Report
Spurred by government mandates for more business transparency, business intelligence has emerged to extract information from ERP systems. How has BI emerged

olap perspectives on data warehousing  representations for each combination. OLAP is often used in data mining , which is a class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior. For example. ,it can help retail companies find customers with common interests. Yet, the term is commonly misused to describe software that presents data in new ways, since true data mining software does not just change the presentation, but actually discovers previously unknown relationships Read More
Business Intelligence: A Guide for Midsize Companies
Business intelligence (BI) is not a new concept. What’s new is that BI tools are now accessible for midsize companies. Managers can use BI to analyze complex

olap perspectives on data warehousing  tools '' with embedded OLAP functionality '' permit business users to perform dynamic analyses on their data. As most IT practitioners can attest to, a user working with a static report will likely ask for additional details and modifications; query and analysis tools allow business users to formulate a high-level query and then immediately explore the underlying details on their own. Core BI technology '' like query, reporting, and interactive analysis '' is used to view or analyze what is or has already 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

olap perspectives on data warehousing  data quality jobs,data quality solution,data quality methodology,data quality strategy,address data quality,data quality manager,data quality audit,data quality measurement,what is data quality,data quality in data warehouse,data quality dashboard,data quality program,clinical data quality,improving data quality,data quality measures 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

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Data Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox
Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging

olap perspectives on data warehousing  data warehouse, data integration tools, data integration toolbox, big data management, data exploration tools, master data management, data management platform Read More
Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond
For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet

olap perspectives on data warehousing  data migration,data migration management,data migration tools,data migration software,data migration plan,data migration tool,data migration services,data migration best practices,data migration process,data migration testing,crm data migration manager,data migration manager,data migration plan template,sql server data migration,legacy data migration 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

olap perspectives on data warehousing  Big Data,Big Data architecture,Big Data challenges,Big Data system,Big Data technology Read More
Data Warehousing in the Big Data Era: Are You BIReady?
Netherlands-based BIReady automates the process of designing, deploying, and maintaining a data warehousing solution, allowing the optimization of all necessary

olap perspectives on data warehousing  data warehouse, data warehouse automation, BIReady, BI, business intelligence, big data, DWH, BI automation, analytics, EDW Read More
Paperless Warehousing
Paperless Warehousing Pty Limited was incorporated in 1988 by two of the existing Directors with a vision to overhaul traditional warehousing operations by

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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

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Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise
While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to

olap perspectives on data warehousing   Read More

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