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 why data mining


The Truth about Data Mining
It is now imperative that businesses be prudent. With rising volumes of data, traditional analytical techniques may not be able to discover valuable data

why data mining  retailer can plan production. Why Not OLAP or Statistics? Data mining includes advanced techniques for understanding data that far exceed the capabilities of online analytical processing (OLAP). OLAP tools provide the means to perform multidimensional analysis by using powerful algorithms for aggregating data. While OLAP can help look at the sales of a certain product within a specific region and time period, data mining can discover relationships between various attributes in the data and deduce why

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Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

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Documents related to » why data mining

How the Mining Industry Benefits from ERP Systems


Integrated enterprise resource planning software normalizes the reporting requirements for a mining company’s various departments. This article loosely shows the parallels between the operations in a mining company and those of a manufacturer whose product is sold on store shelves.

why data mining  the chosen ERP system. Why should any company implement an ERP system? Based on the responses of over 1,400 manufacturers to an August 2007 survey by the Aberdeen Group on the reasons for implementing an ERP system, the following statistics were found: availability of low-cost options that minimize risk: 41% pressure from customers or suppliers for data and collaboration: 40% explosive growth: 33% growth beyond a predefined threshold: 29% regulatory compliance requirements: 25% a disastrous event that Read More

The Necessity of Data Warehousing


An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

why data mining  - August 2, 2000 Why the market is necessary Data warehousing is an integral part of the information age . Corporations have long known that some of the keys to their future success could be gleaned from their existing data, both current and historical. Until approximately 1990, many factors made it difficult, if not impossible, to extract this data and turn it into useful information. Some examples: Data storage peripherals such as DASD (Direct Access Storage Device) were extremely expensive on a Read More

How to Comply with Data Security Regulations


A remote data backup solution can be compliant with almost any international, federal, or state data protection regulation—and can be compliant with the common caveats of most data security laws by providing functionality like data encryption and secure media control. And, as some regulations require files to be archived for several years, you can create a routine that archives files you select for backup and storage.

why data mining  Your Client Data | Why Using Data Protection | Whole Disk Encryption | Whats is Database Protection | What is Data Security | What Does Bizdomain | Tape Data Backup | Tape Backup Data Storage | System Data | System Backup Software | Struggling with Data Security | State Data Protection | State Data | Software Backup | Simplify Data Security | Server Data Protection | Server Data Backup | Server Backup Storage | Security Software | Security of Data | Security Data Center | Securising Database | Secure Read More

Why CRM Is So Hard and What To Do About It: Data is key to making CRM work


Making a CRM investment work is a two-step process that begins with unifying disparate systems by creating and managing standardized, reusable business definitions mapped to the different CRM system schemas throughout the organization.

why data mining  is the axle. It's why Gartner calls managing customer-related data the number one obstacle to getting a return on CRM investments. To fully exploit the power of CRM, and to realize its much-hyped promise, organizations must first recognize that customer-related data often resides in dozens, sometimes hundreds of separate databases, files and data feeds; they must then understand how to utilize all these information sources in a consistent way. Complicating this integration is the thorny fact that 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-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 compares their key attributes, and provides a framework for choosing the best approach(es) based on business requirements.

why data mining  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

Demystifying Data Science as a Service (DaaS)


With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white paper to find out more about how data SaaS is set to become a vital part of business intelligence and analytics, and how India will play a role in this trend.

why data mining  Data Science as a Service (DaaS) With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white 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 migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

why data mining  the data migration process. Why Migrate Data at All? Data migration is a necessary part of application migration, the process of moving business functionality and reliance off one or more existing applications and addressing the business's requirements with another application. Often the intent is to shut down the first application (referred to as the source application) sometime after the migration is complete. Companies may choose to migrate applications primarily for business reasons, for example, in Read More

Master Data Management and Accurate Data Matching


Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process.

why data mining  its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process. Read More

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Don't Be Overwhelmed by Big Data


Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Data can be a Big Deal - read this white paper for some useful tips on ensuring secure, quality data acquisition and management.

why data mining  understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Data can be a Big Deal - read this white paper for some useful tips on ensuring secure, quality data acquisition and management. 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 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 defined and their benefits are explained.

why data mining  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 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 Read More

How Companies Use Data for Competitive Advantage


Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage.

why data mining  Companies Use Data for Competitive Advantage How Companies Use Data for Competitive Advantage Today, many businesses find they are under siege dealing with an explosion of data. Yet the best performing companies are mastering their data—and using it for competitive advantage. How are they able to accomplish this? What best practices, approaches, and technologies are they employing? Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage . In this Economist Business 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...

why data mining  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