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The Data Management & Warehousing Knowledge Base provides information and techniques about the design, build and implementation of data warehousing solutions that we as a company use and hope that you will also find useful.
- How Data Works
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How business store and manage their data can have critical effect on data quality and consistency as well as performance and development times. This paper examines how data works and explores techniques exploited from understanding how data works
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- Continuous Data Quality Process Wallchart
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A wallchart outlining the process required to develop continuous data quality within an organisation is available for download
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- Data Warehouse Documentation Roadmap
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All projects need documentation and many companies provide templates as part of a methodology. This document describes the templates, tools and source documents used by Data Management & Warehousing. It serves two purposes:
* For projects using other methodologies or creating their own set of documents to use as a checklist. This allows the project to ensure that the documentation covers the essential areas for describing the data warehouse.
* To demonstrate our approach to our clients by describing the templates and deliverables that are produced.
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- Data Warehouse Governance
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An organisation that is embarking on a data warehousing project is undertaking a long-term development and maintenance programme of a computer system. This system will be critical to the organisation and cost a significant amount of money, therefore control of the system is vital. Governance defines the model the organisation will use to ensure optimal use and re-use of the data warehouse and enforcement of corporate policies (e.g. business design, technical design, and application security) and ultimately derive value for money.
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- Overview Architecture for Enterprise Data Warehouses
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This is the first of a series of papers published by Data Management & Warehousing to look at the implementation of Enterprise Data Warehouse solutions in large organisations using a design pattern approach. A design pattern provides a generic approach, rather than a specific solution. It describes the steps that architecture, design and build teams will have to go through in order to implement a data warehouse successfully within their business
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- Job scheduling - fixed and relative timing
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This article looks at the relatve merits of two types of processing schedule, once based on a fixed times (similar to 'cron' on a unix system) and onebased on relative times (similar to 'at' on a unix system)
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- Data Transformation - Procedural and Non-Procedural Solutions
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This paper looks at a somewhat awkward data transformation, and at solutions written in SQL and in a procedural language. It describes some techniques which can be used to develop the solution in both languages. It also compares the solutions in terms of ease of development, performance and cost of maintenance.
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Category: Data Warehousing
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- The Information Life Cycle
- This article is based on the forthcoming book, <i>Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information</i>, by Danette McGilvray, published by Morgan Kaufmann
Publishers, Copyright 2008 Elsevier Inc.
- Grounding Your IQ Management in Sound Quality Management Systems
- For an information quality management function is to succeed, it must be based on the same fundamental principles that led to effective quality systems in manufacturing and the service sector.
- Dark Data
- Data hidden within the enterprise will inevitably be challenged, and it will be up to enterprise information management to tame it.
- Gaining Insight through Analytics - It Takes More than OLAP
- What are the keys to real business insight? Dave Wells describes the nature of insight and what is required to gain true insight.
- Communication in Business Intelligence Teams
- Many companies see the need for effective communication for business intelligence professionals, but they often fail to provide the opportunities to focus on the skills required to achieve it.
- Data Stewardship and Pain
- Do we really need data governance?
- Data Warehousing Architecture
- The data warehouse architecture and the blueprint that will drive its construction are critical to the success or the failure of the program and its projects.
- Is Data Warehousing Essential to Business Intelligence?
- The role of data warehousing is changing as companies move toward using new business intelligence approaches.
- Improving Service Line Performance with Healthcare Business Intelligence
- Business intelligence and analytics can help to get a comprehensive picture of the standard financial and clinical performance measures and then build on these standard measures to find trends and
patterns.
- Activity versus Achievement in Telecom
- The telecom industry might be the poster child for issues associated with mis-definition of measures and key performance indicators, and the ineffective use of those measures across departmental
lines.
- Expanding the Envelope
- The aviation industry provides a metaphor for the state of data warehousing.
- Your Business Intelligence Program
- Taking the time to establish a common vocabulary around business intelligence and master data management projects gets everyone on the same page and also is a means by which to enlist business
involvement.
- Danger - BPM Ahead, Part 1
- This article, the first in a two-part series, covers two of the three problems that can cause significant issues for the companies implementing business performance management solutions.
- Competing on (Customer) Decisions
- Competing by focusing on customer treatment decisions should be a core element of a customer-centric strategy.
- Implementing a Successful Business Intelligence Competency Center
- Developing a centralized strategy and framework can lead to faster application delivery, greater cost reduction and better decision making.
Category: Uncategorized
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