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Documents related to » implementing data warehouse bi


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

implementing data warehouse bi  the technical difficulties of implementing a true real-time data warehouse, there are some advantages. It shortens information delivery times. It improves integration throughout the organization. It eases the analysis of future trends. Basic Principles to Consider With the growing popularity and increasing implementation of real-time data warehouses, it is important to consider some basic principles when considering a real-time data warehouse implementation. Data on Time, at the Right Time . The data Read More...
Achieving Business Intelligence (BI) in Midsize Companies
Like many of today’s IT decision makers, you may be considering a business intelligence (BI) solution for your midsize company. But how do you go about adding

implementing data warehouse bi  systems dynamically to make implementing those decisions seamless and easier. Repeat, as shown in Figure 4.1. Figure This is what true BI is all about. Not just delivering data in visually-stunning dashboards, but giving you real tools to spot trends and underlying causes, to make decisions, and to make those decisions happen. Think Big, Start Small In previous chapters, I''ve mentioned a couple of approaches to data warehouse design. These are both very high-level philosophies, both espoused by very Read More...
Customer Data Integration: A Primer
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a

implementing data warehouse bi  should be considered when implementing master data management (MDM) for CRM within the organization. Finally, key vendors in the industry and their key product features will be identified. Defining Customer Data Integration Within CRM, CDI is the management and consolidation of customer information from across the organization. This includes, but is not limited to, information stored in call centers, sales and marketing departments, and accounts receivables and payables. CDI ensures that each department Read More...
A Road Map to Data Migration Success
Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project

implementing data warehouse bi  processes that they are implementing. Allow time in your planning for changes to the mapping, business rules, and re-loads. It is not uncommon for there to be confusion during beta testing and implementation as to where errors originate. It''s all too easy for bad data to be blamed for every test error. What can you do as part of your planning to avoid this? Implement the migration with as much metadata and reconciliation as possible. Not only are you ensuring the integrity of your data, you are Read More...
Four Critical Success Factors to Cleansing Data
Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment

implementing data warehouse bi  records. Unless you are implementing an ERP or CRM system, initial data cleansing efforts on transactional or historical data would be discouraged. How many integrations do you have that feed your master data to other systems (internal or external) Create a master list by system and data field name. Do you have a data warehouse, one central location for master data? Is now the time to make that move? Now identify the data owner and the business owners for each field. A data owner is the person that is Read More...
Warehouse Management Systems by the Numbers
When it comes to warehouse management systems (WMS), the stats are both shocking and thought-provoking. And although you don''t see these stats in the marketing

implementing data warehouse bi  you''ve given for not implementing a WMS. Your warehouse is not big enough. You don''t have enough people or orders to justify such a large investment. Your information technology (IT) staff isn''t large enough. You are currently searching for a system. (Perhaps you''ve been researching WMS systems for years by attending trade shows, reading industry articles, and talking with vendors, but you still haven''t made a decision and purchased one.) The reasons are endless, but your real reason is very likely a 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...

implementing data warehouse bi  Errors to 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 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

implementing data warehouse bi  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...
Achieving a Successful Data Migration
The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data

implementing data warehouse bi  a Continuously Changing Target Implementing an application is an iterative process, with business and IT staff making frequent changes to the application functionality or underlying processes. The tweaking doesn''t stop after implementation, either throughout the life of an application; evolving business and technical needs require changes ranging from minor refinements to major overhauls. Many of these application changes require adjustments to the data migration capability. If making those adjustments Read More...
Overall Approach to Data Quality ROI
Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company

implementing data warehouse bi  Approach to Data Quality ROI Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI. Read More...
Data Migration Best Practices
Large-scale data migrations can be challenging, but with the appropriate planning—and through careful execution of that plan—organizations can greatly reduce

implementing data warehouse bi  Migration Best Practices Large-scale data migrations can be challenging, but with the appropriate planning—and through careful execution of that plan—organizations can greatly reduce the risks and costs associated with these projects. This paper offers a handy checklist of issues to consider before, during, and after migration. 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

implementing data warehouse bi  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...
Acumen Data Systems
Acumen Data Systems provides employee time and attendance systems and software. Its software@s focuses include job tracking, shop floor data collection, and

implementing data warehouse bi  Data Systems Acumen Data Systems provides employee time and attendance systems and software. Its software’s focuses include job tracking, shop floor data collection, and employee scheduling. Read More...
Logs: Data Warehouse Style
Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources

implementing data warehouse bi  Data Warehouse Style Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources. But where does log data fit in? Historically, log data was reported on through slow legacy applications. But with today’s log data warehouse solutions, data is centralized, allowing users to analyze and report on it with unparalleled speed and efficiency. Read More...
A Roadmap to Data Migration Success
Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources,

implementing data warehouse bi  Roadmap to Data Migration Success Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them. Read More...

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