X
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 solutions by funtionality, so that you can make accurate and informed software purchasing decisions.
Compare Now
 

 data mining ilm

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.

Compare Now

Documents related to » data mining ilm

Data Center Projects: Project Management


In data center design projects, flawed management frequently leads to delays, expense, and frustration. Effective project management requires well-defined responsibilities for every manager, tight coordination among suppliers, well-defined procedures for managing change, and consistent terminology. Learn how enforcing these requirements can help your company achieve an efficient process with a predictable outcome.

data mining ilm  leading causes of downtime, data loss and hardware damage: power problems and temperature. As a global leader in network-critical physical infrastructure (NCPI) solutions, APC sets the standard in its industry for quality, innovation and support. Source : APC Resources Related to Data Center Project Management : Data Center (Wikipedia) Project Management (Wikipedia) Data Center Projects: Project Management Data Center Project is also known as : Project Management , Internalize Data Centers , Data Center Read More

Data Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox


Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data warehouse.

data mining ilm  Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data 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. 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.

data mining ilm  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

Meet PCI DSS Compliance Requirements for Test Data with Data Masking


Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more.

data mining ilm  Compliance Requirements for Test Data with Data Masking Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more. Read More

Mining & Quarrying


Mining is the extraction from the earth of materials used in different human activities (industry, trade, energy production, etc.). There are four major types of materials: precious metals and minerals (gold, diamonds, silver, etc.); materials used to produce energy (coal, uranium, etc.); base metals (copper, iron, etc.); and building materials (stone, sand, gravel) extracted from quarries, which are open-pit mines. There are two major types of activities specific to the mining industry: exploration, which involves the search for materials; and extraction, which is the activity of getting those materials out of the earth.

data mining ilm  & Quarrying Mining is the extraction from the earth of materials used in different human activities (industry, trade, energy production, etc.). There are four major types of materials: precious metals and minerals (gold, diamonds, silver, etc.); materials used to produce energy (coal, uranium, etc.); base metals (copper, iron, etc.); and building materials (stone, sand, gravel) extracted from quarries, which are open-pit mines. There are two major types of activities specific to the mining industry: Read More

Metagenix Reverse Engineers Data Into Information


Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than depending on the data dictionaries of the existing legacy systems (which are often incorrect). Other unique Metagenix approaches include an "open book" policy, which includes publishing product price lists on their web site and complete access to company officials, including CEO and President Greg Leman. According to Mr. Leman, "we’re pathologically honest".

data mining ilm  Reverse Engineers Data Into Information Metagenix Reverse Engineers Data Into Information M. Reed - February 15, 2001 Event Summary Metagenix, Inc. has designed its flagship product, MetaRecon to, as they put it, Decipher Your Data Genome . The product reverse engineers all of the metadata ( data about data ) from data sources and generates information that is very helpful to developers in designing specifications for a new data store, and assists greatly in preparing for cleansing and Read More

Oracle Database 11g for Data Warehousing and Business Intelligence


Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

data mining ilm  Database 11g for Data Warehousing and Business Intelligence Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data. Read More

Network Data Protection Playbook: Network Security Best Practice for Protecting Your Organization


Malicious hacking and illegal access are just a few of the reasons companies lose precious corporate data every year. As the number of network security breaches increase, companies must find ways to protect data beyond the perimeter of their businesses. But how do they build a data-defensible architecture that will protect data on an ever-evolving network? The answer: by first developing an in-depth defense strategy.

data mining ilm  Data Protection Playbook: Network Security Best Practice for Protecting Your Organization Network Data Protection Playbook: Network Security Best Practice for Protecting Your Organization If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. CipherOptics makes data protection simple. Whether you need to secure data flows over your application environment or encrypt data in motion across the network, CipherOptics makes it easy. Our Read More

Top 10 Evaluation Criteria for Copy Data Management & Data Virtualization


Data virtualization is becoming more important, as industry-leading companies learn that it delivers accelerated IT projects at a reduced cost. With such a dynamic space, one must make sure that vendors will deliver on their promises. This white paper outlines 5 qualification questions to ask before and during the proof of concept (POC), and 5 things to test during the POC.

data mining ilm  Evaluation Criteria for Copy Data Management & Data Virtualization Data virtualization is becoming more important, as industry-leading companies learn that it delivers accelerated IT projects at a reduced cost. With such a dynamic space, one must make sure that vendors will deliver on their promises. This white paper outlines 5 qualification questions to ask before and during the proof of concept (POC), and 5 things to test during the POC. Read More

Data Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses


Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and predictive analysis. Learn more.

data mining ilm  BI Platform to Distribute Data Mining and Predictive Analytics to the Masses Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and predictive analysis. Learn more. Read More

Data Leak versus Data Flood: Problems Addressed by Data Leakage and Data Breach Solutions


Data leakage and data breach are two disparate problems requiring different solutions. Data leakage prevention (DLP) monitors and prevents content from leaving a company via e-mail or Web applications. Database activity monitoring (DAM) is a data center technology that monitors how stored data is accessed. Learn why DAM complements DPL, and how you can benefit by making it part of your overall data security strategy.

data mining ilm  Leak versus Data Flood: Problems Addressed by Data Leakage and Data Breach Solutions Data leakage and data breach are two disparate problems requiring different solutions. Data leakage prevention (DLP) monitors and prevents content from leaving a company via e-mail or Web applications. Database activity monitoring (DAM) is a data center technology that monitors how stored data is accessed. Learn why DAM complements DPL, and how you can benefit by making it part of your overall data security strategy. Read More

Forrester TechRadar Report: Data Security


Data security is not just an IT issue these days but a business imperative, as data volumes explode and it is becoming a Herculean task to protect sensitive data from cybercriminals and prevent privacy infringements. As data volumes continue to rise, the burden of protecting sensitive data and preventing security breaches can be crushing. It is necessary to take a holistic, comprehensive, and long-lasting approach to data security that encompasses people, processes, and technology.

This Forrester TechRadar Data Security report provides a framework for developing a long-term approach to keeping your organization’s information secure. Data breaches and insider threats are becoming more common, and your organization needs to achieve compliance and secure privacy without affecting the bottom line. Most companies are also interested in adopting cloud, mobile, and other technologies, which can complicate data security matters even more.

This comprehensive and in-depth report evaluates 20 of the key traditional and emerging data security technologies. To make the report, Forrester interviewed over 40 experts, customers, and users, and drew from a wealth of analyst experience, insight, and research.

Use this report to get informed about what you need to consider to restrict and strictly enforce access control to data, monitor, and identify abnormal patterns of network or user behavior, block exfiltration of sensitive data, and render successful theft of data harmless.

data mining ilm  TechRadar Report: Data Security Data security is not just an IT issue these days but a business imperative, as data volumes explode and it is becoming a Herculean task to protect sensitive data from cybercriminals and prevent privacy infringements. As data volumes continue to rise, the burden of protecting sensitive data and preventing security breaches can be crushing. It is necessary to take a holistic, comprehensive, and long-lasting approach to data security that encompasses people, 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.

data mining ilm  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

The Path to Healthy Data Governance


Many companies are finally treating their data with all the necessary data quality processes, but they also need to align their data with a more complex corporate view. A framework of policies concerning its management and usage will help exploit the data’s usefulness. TEC research analyst Jorge Garcia explains why for a data governance initiative to be successful, it must be understood as a key business driver, not merely a technological enhancement.

data mining ilm  Path to Healthy Data Governance This article is based on the presentation, “From Data Quality to Data Governance,” by Jorge García, given at ComputerWorld Technology Insights in Toronto, Canada, on October 4, 2011. Modern organizations recognize that data volumes are increasing. More importantly, they have come to realize that the complexity of processing this data has also grown in exponential ways, and it’s still growing. Many companies are finally treating their data with all the necessary Read More

Data Blending for Dummies


Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant.

Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data providers, department data stores, in-house databases, and more, and become faster at delivering better information and results to their organizations. In the past, the challenge for data analysts has been accessing this data and cleansing and preparing the data for analysis. The access, cleansing, and preparing data stages are complex and time intensive. These days, however, software tools can help reduce the burden of data preparation, and turn data blending into an asset.

Read this e-book to understand why data blending is important, and learn how combining data means that you can get answers to your business questions and better meet your business needs. Also learn how to identify what features to look for in data blending software solutions, and how to successfully deploy these tools within your business. Data Blending for Dummies breaks the subject down into digestible sections, from understanding data blending to using data blending in the real world. Read on to discover how data blending can help your organization use its data sources to the utmost.

data mining ilm  Blending for Dummies Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant. Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data Read More