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Software Functionality Revealed in Detail
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 bi data mining

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

Business Intelligence (BI)

Business intelligence (BI) and performance management applications enable real-time, interactive access, analysis, and manipulation of mission-critical corporate information. These applications provide users with valuable insights into key operating information to quickly identify business problems and opportunities. Users are able to access and leverage vast amounts of information to analyze relationships and understand trends that ultimately support business decisions. These tools prevent the potential loss of knowledge within the enterprise that results from massive information accumulation that is not readily accessible or in a usable form. It is an umbrella term that ties together other closely related data disciplines including data mining, statistical analysis, forecasting, and decision support. 

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Documents related to » bi data mining

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.

bi 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 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 to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.

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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. Consequently, data mining technology becomes important. Here is a framework to help understand the data mining process.

bi data mining  the components of Microsoft''s BI suite. It includes several data mining algorithms developed through collaboration between the Microsoft research and SQL Server product teams. SQL Server data mining integrates with other parts of the BI suite: analysis services, integration services, and reporting services. In Conclusion It is essential to lay the groundwork for the complex process of data mining. This includes having a thorough understanding of business data entities and their interrelationships. In Read More

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 environment. This article looks at issues in data quality and how they can be addressed.

bi data mining  primary purpose of a BI solution is to provide a business with the necessary information to support better decision making. This requires the integration of data within and external to an enterprise. A sound data quality strategy protects an enterprise from inconsistencies and anomalies that arise from the complexity of integrating multiple systems and from hidden problems that are uncovered only through sophisticated analysis techniques. Data quality solutions provide organizations with the ability to Read More

Ask the Experts: Approaches to Data Mining ERP


From one of our readers comes this question: I am a student of IT Management; I have an ERP course and I am supposed to write an article to review new aspects of ERP systems. I’ve decided to explore the reasons for using data mining techniques in ERP systems—and to look at different modules to which these techniques have been applied. I am going to prepare a framework to determine

bi data mining  this represents is a BI solution layer on top of traditional manufacturing technologies, enabling users to extract data from their manufacturing environment. What does this mean exactly? Let’s say, for example, that a manufacturer produces cars and that it must procure car parts from multiple suppliers. If these components do not arrive on time, this will negatively affect their production runs, essentially decreasing the company’s bottom line. By mining data in the ERP system, the manufacturer can Read More

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 quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.

bi data mining  Data Cleanse Summary About BI Research About Business Objects Data Quality: What’s The Problem? Data quality has always been an important issue for companies, and this is even more the case today. Business and legislative pressures coupled with the explosion in the amount of data created by organizations is leading to increased corporate attention on improving the quality and accuracy of business data. This paper reviews current industry problems concerning data quality, and takes a detailed look at Read More

The Advantages of Row- and Rack-oriented Cooling Architectures for Data Centers


The traditional room-oriented approach to data center cooling has limitations in next-generation data centers. Next-generation data centers must adapt to changing requirements, support high and variable power density, and reduce power consumption and other operating costs. Find out how row- and rack-oriented cooling architectures reduce total cost of ownership (TCO), and address the needs of next-generations data centers.

bi data mining  IT equipment takes in ambient air and ejects waste heat into its exhaust air. Since a data center may contain thousands of IT devices, the result is that there are thousands of hot airflow paths within the data center that together represent the total waste heat output of the data center; waste heat that must be removed. The purpose of the air conditioning system for the data center is to efficiently capture this complex flow of waste heat and eject it from the room. Room-based cooling is the historical 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 customer relationship management initiative can help provide organizations with a successful framework to manage data on a continuous basis.

bi data mining  appropriately based on order, billing, and call center information. Data redundancy profiling identifies duplicate records or overlapping values between tables. This eliminates the possibility of sending out multiply flyers to an individual customer. Data mapping helps ensure the data elements are the same across disparate systems, and mapped where appropriate. For example, it is important that the customer first and last name link up the same way in each disparate system, to guarantee that the correct Read More

Master Data Management: Extracting Value from Your Most Important Intangible Asset


In a 2006 SAP survey, 93 percent of respondents experienced data management issues during their most recent projects. The problem: many organizations believe that they are using master data, when in fact what they are relying on is data that is dispersed throughout the enterprise. Discover the importance of master data and how the ideal master data management (MDM) solution can help your business get it under control.

bi data mining  MDM SOA | MDM BI | Master Data Management Data Warehouse | Master Data Management Challenge | Data Quality Integration | Master Data Management Solution | MDM Solution | Master Data Integrity | Engineering Data Management | Master Data Management Software | MDM Software | Master Data Management System | Master Data Management Services | Customer Master Data Management | Customer Data Integration | Master Data | Data Governance | Data Quality Management | Data Management Strategy | Business Intelligence Read More

Big Data: Operationalizing the Buzz


Integrating big data initiatives into the fabric of everyday business operations is growing in importance. The types of projects being implemented overwhelmingly favor operational analytics. Operational analytics workloads are the integration of advanced analytics such as customer segmentation, predictive analytics, and graph analysis into operational workflows to provide real-time enhancements to business processes. Read this report to learn more.

bi data mining  Operationalizing the Buzz Integrating big data initiatives into the fabric of everyday business operations is growing in importance. The types of projects being implemented overwhelmingly favor operational analytics. Operational analytics workloads are the integration of advanced analytics such as customer segmentation, predictive analytics, and graph analysis into operational workflows to provide real-time enhancements to business processes. Read this report to learn more. Read More

Big Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone


Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and decision support.

bi data mining  Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and d Read More

Eliminating Mining Industry Profitability Killers through a Common Decision Environment


Mining corporations and their operating units are under constant pressure to improve financial performance. Efforts to become financially healthy are hampered by the operational profitability killers embedded in traditional processes. Find out how technology-supported collaborative decision making drives key efficiencies at all stages of the asset lifecycle, from planning and construction through production and into decommissioning.

bi data mining  Mining Industry Profitability Killers through a Common Decision Environment Mining corporations and their operating units are under constant pressure to improve financial performance. Efforts to become financially healthy are hampered by the operational profitability killers embedded in traditional processes. Find out how technology-supported collaborative decision making drives key efficiencies at all stages of the asset lifecycle, from planning and construction through production and into 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.

bi data mining  problem. Most organizations have bigger concerns to fix first. With 96 percent of data lost by other means, mostly through network and insider attacks, the recent emphasis on encrypting tapes has been far too high. In fact, there is a strong market trend toward Continuous Data Protection solutions (IDC) that use the network for business-continuity and data-recovery operations and protect data in flight when it is copied from one data store to another. This method allows for the immediate protection of 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, 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.

bi data mining  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, 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