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Data Center Projects: System Planning
System planning is the Achilles’ heel of a data center physical infrastructure project. Planning mistakes can propagate through later deployment phases
be eliminated by viewing system planning as a data flow model, with sequenced tasks that progressively transform and refine data from initial concept to final design. Learn more.
A CRM System Needs A Data Strategy
A customer relationship management (CRM) system is inherently valuable for supporting customer acquisition and retention by gathering data from each contact
CRM System Needs A Data Strategy Introduction An underutilized customer relationship management (CRM) system - or one that cannot match its owner''s expectations - will reflect poorly on both the vendor who sold it and the IT manager who authorized the purchase and installed it. Both, however, can help successfully manage such expectations (and add value to their respective roles) by wisely counseling about the strategic context into which a CRM system must function. Simply put, the market includes plenty
Ask the Experts: Data Purging and System Migration
One reader recently wrote in with this question:
I mentioned, the old system will have valid data for some time. It may be that the switchover is done on a midnight when the decision taken is to remain on the live system, and not do a fall back. In this case, you will need to address the problem of what to do with your web site interfaces if something goes wrong. For this reason, you should only update these interfaces once you are sure the implementation is a success. (Yes, some go-lives fail the first time. This happens mainly with large systems becau
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 in the current system and then migrate, or correct the data in the new system before bringing it online. Either action would require considerable work and demand changes to business processes and behaviors to ensure ongoing manufacturing productivity. Data Quality Control Every business application should be periodically assessed for data quality. It should be a quarterly effort to assure reliable processing and to maintain the value of business decisions made from data. Software tools such as Carlet
Augmenting Data Backup and Recovery with System-level Protection
File-level recovery on its own is an incomplete strategy when it comes to meeting stringent recovery time objectives (RTOs) for complete system recovery. This
objectives (RTOs) for complete system recovery. This paper investigates what’s at risk, where system-level recovery fits relative to current data protection approaches, the impact of system-level recovery on your IT department’s ability to meet RTOs, and the potential of system-level recovery to reduce costs.
Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever
Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online
Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility.
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
investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.
The Path to Healthy Data Governance through Data Security
Companies today are challenged to maintain their data safe and secure from hackers and others with unauthorized access. In his article, TEC business
the protection of information systems against unauthorized access to or modification of information, whether in storage, processing or transit, and against the denial of service to authorized users or the provision of service to unauthorized users, including those measures necessary to detect, document, and counter such threats. So then, I see the following four elements as essential to an information security perspective: Availability. Ensuring the right data is available to the right people.
Five Tips for Saving Money on Your Business Phone System
With recession looming and profit margins under siege, the last thing any company needs is a capital-draining business phone system. Fortunately, today’s voice
on Your Business Phone System With recession looming and profit margins under siege, the last thing any company needs is a capital-draining business phone system. Fortunately, today’s voice over Internet protocol (VoIP) providers offer plenty of cost-trimming features to keep business phone costs in check or dramatically lower communications overhead. Read here to know the five ways businesses are taking advantage of new VoIP technology to save money.
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...
and lighting equipment why system design is the most important factor in determining the efficiency of a data center In today''s tough economy, you need to look at every energy and money saving option at your disposal. Find out what you need to know about running an energy-efficient data center. Download your PDF copy of Implementing Energy-efficient Data Centers today. For assistance, please contact customer service. Hours: 8:00 AM to 5:30 PM EST. Phone: 514-954-3665, ext. 367.
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
a new inventory management system that is supposed to reduce inventory by $20 million annually, then every day that application is late may be costing the business $55,000. Anecdotal evidence suggests that the data migration phase can consume up to 40 percent of the entire budget of an application implementation, upgrade, or instance consolidation. And, since there are no separate metrics for migration, data migration problems can lead an organization to judge the entire application project a failure.
Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management
Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in
Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses
Developing a Universal Approach to Cleansing Customer and Product Data
Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data
also to data and system management tasks as well. This enables the tasks associated with a data quality program to be deployed as a set of services that can be called dynamically by applications (see Figure 4). This allows business rules for data quality enforcement to be moved outside of applications and applied universally at a business process level, rather than at the individual application level. These services can be called proactively by applications as data is entered into an application system,
A Solution to Data Capture and Data Processing Challenges
Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the
Solution to Data Capture and Data Processing Challenges Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the right information to the right people at the right time—but is your data capture process as efficient as it could be? Learn about the issues surrounding data capture and data processing, and about a solution designed to help you address specific processing problems.
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