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In Search of Clarity: Unraveling the Complexities of Executive Decision Making
Decision making is at the core of all business activity, as executives set strategy and manage operations by weighing a vast array of factors to arrive at the

data analysis and decision making  frustration.” For example, self-reported data from customers is not necessarily of consistent accuracy, so analysis of it may not yield useful insights. To what extent are the metrics used in decision-making (operational and management) standardised throughout your organisation? Another issue is that of metrics. Historically, at most companies different units have developed their own metrics suited to their specific functions. Meaningful data aggregation, though, requires a common set of definitions. Read More...
Discrete Manufacturing (ERP)
The simplified definition of enterprise resource planning (ERP) software is a set of applications that automate finance and human resources departments and help manufacturers handle jobs such as or...
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Documents related to » data analysis and decision making


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 analysis and decision making  emphasize the quality of data that is used for analysis and subsequent decision making. As data captured from a multitude of sources makes its way to an enterprise data warehouse or data marts, a data quality framework creates a screening process that measures the purity of the data and corrects any inconsistencies found. This article walks the reader through a typical data quality strategy by illustrating, through examples, how and where quality issues occur, and the approaches available to inhibit the Read More...
The ASP Decision
The ASP model is the latest in a long line of silver bullets that are supposed to simplify the delivery of technology’s benefits to the business world. This

data analysis and decision making  financial analysis of a data center relocation for a major brokerage house, an analysis of the data center hardware and software contract portfolio for a large Midwest healthcare, the negotiation of a multi-year hardware break/fix contract for a large Northeast insurance company, and the development of an application development services agreement for a Northeast financial services company. Previously, Mr. Hennigan spent over ten years in senior management positions in the Information Technology Read More...
Role of In-memory Analytics in Big Data Analysis
Organizations today need to handle and manage increasingly large volumes of data in various formats and coming from disparate sources. Though the benefits to be

data analysis and decision making  In-memory Analytics in Big Data Analysis In a previous article , I discussed big data and the need for a big data solution to handle, manage, and derive valuable insight from large volumes of data in various formats and coming from disparate sources. Here I discuss the role that in-memory technologies plays in big data analysis and the potential of this technology to change the business intelligence (BI) landscape and the industry technology space. But first we need to understand the basics.   A Basic Read More...
The 2008 Handbook of Application Delivery: A Guide to Decision Making
IT organizations can no longer manage networks in isolation from the applications they support, requiring a shift from focusing on devices to a focus on

data analysis and decision making  offices and into centralized data centers. Also, the handbook does not contain a detailed analysis of any technology. To compensate for this, the handbook includes an extensive bibliography. In addition, the body of the handbook does not discuss any vendor or any products or services. The Appendix to the handbook, however, contains material supplied by the majority of the leading application delivery vendors. To allow IT organizations to compare their situation to those of other IT organizations, this Read More...
Data Storage in the Cloud-Can you Afford Not To?
Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast,

data analysis and decision making  Afford Not To? Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or avoided by using the cloud for backup and archive storage. 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 analysis and decision making  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...
Types of Prefabricated Modular Data Centers
Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod

data analysis and decision making  of Prefabricated Modular Data Centers Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and Read More...
Data Center Projects: Advantages of Using a Reference Design
It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete

data analysis and decision making  aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and shorten the planning and implementation process and reduce downtime risks once up and running. In this paper reference designs are Read More...
ESG - Riverbed Whitewater: Optimizing Data Protection to the Cloud
Riverbed Whitewater leverages WAN optimization technology to provide a complete data protection service to the cloud. The appliance-based solution is designed

data analysis and decision making  - Riverbed Whitewater: Optimizing Data Protection to the Cloud Riverbed Whitewater leverages WAN optimization technology to provide a complete data protection service to the cloud. The appliance-based solution is designed to integrate seamlessly with existing backup technologies and cloud storage provider APIs. Read this ESG Lab report on hands-on testing of the Riverbed Whitewater appliance for ease of use, cost-effective recoverability, data assurance, and performance and scalability. 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 analysis and decision making  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...
Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security
Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all

data analysis and decision making  Best Practices in Application Data Security Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace. 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

data analysis and decision making  what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality. Read More...
Effective Inventory Analysis: the 5 Key Measurements
The white paper effective inventory analysis isolates and walks you through five simple measurements that will help you ensure you are maximizing t...

data analysis and decision making  Inventory Analysis: the 5 Key Measurements As a distributor or manufacturer, how do you stack up when it comes to monitoring the performance of one of your largest investments: your inventory? Computer-generated reports can be more of a hindrance than a help—many systems produce so many reports, you can drown in them. Measurements that evaluate inventory performance? There are literally hundreds of them, so which ones tell you what you really need to know? The white paper Effective Inventory Read More...
Data Center Automation
With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and

data analysis and decision making  increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands. Read More...

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