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Documents related to » etl data mining


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

etl data mining  extract, transform, and load (ETL) process in a data warehousing system extracts records from data source(s), transforms them using rules to convert data into a form that is suitable for reporting and analysis, and finally loads the transformed records into the destination (typically a data warehouse or data mart). Data cleansing is an integral part of the transformation process and enforces business and schema rules on each record and field. Data cleansing involves the application of quality screens Read More
Best Practices for a Data Warehouse on Oracle Database 11g
Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW

etl data mining  via another set of ETL processes. It is in this layer data begins to take shape and it is not uncommon to have some end-user application access data from this layer especially if they are time sensitive, as data will become available here before it is transformed into the dimension / performance layer. Traditionally this layer is implemented in the Third Normal Form (3NF). Optimizing 3NF Optimizing a 3NF schema in Oracle requires the three Ps – Power, Partitioning and Parallel Execution. Power means Read More
The Evolution of a Real-time Data Warehouse
Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine

etl data mining  data warehouse design. All ETL data warehouse processes were originally designed to be executed in batch mode, during previously scheduled downtimes. All operational data from distinct sources (e.g. ERP systems) was extracted, cleansed under a stage repository, and loaded into the data warehouse over long periods of time, mostly at night. These processes can take minutes or hours, depending on the volume of data being uploaded to the data warehouse. With the pressure to load more recent data into the Read More
A Definition of Data Warehousing
There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing

etl data mining  are currently over 50 ETL tools on the market. The data acquisition phase can cost millions of dollars and take months or even years to complete. Data acquisition is then an ongoing, scheduled process, which is executed to keep the warehouse current to a pre-determined period in time, (i.e. the warehouse is refreshed monthly). Changed Data Capture: The periodic update of the warehouse from the transactional system(s) is complicated by the difficulty of identifying which records in the source have changed Read More
A One-stop Event for Business Intelligence and Data Warehousing Information
The Data Warehousing Institute (TDWI) hosts quarterly World Conferences to help organizations involved in data warehousing, business intelligence, and

etl data mining  extract, transform, and load (ETL) development. It is important not to underestimate the importance of data integration, as the way data is integrated into a data warehouse or BI solution is the essence of that system. If a scorecard is developed to measure an organization''s sales metrics and the source data is not accurate, the key performance indicators (KPIs) set and reported on will be meaningless. Administration and Technology The administration and technology track identified and covered topics Read More
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...

etl data mining  Energy-Efficient Data Centers Did you realize that your data center(s) may be costing you money by wasting electricity ? Or that there are at least 10 different strategies you can employ to dramatically cut data center energy consumption ? The fact is, most data centers are not designed with energy efficiency in mind. But in the white paper Implementing Energy-efficient Data Centers , you''ll learn how to save money by using less electricity—whether your data centers are still in the design 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

etl 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 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

etl data mining  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
The Value of Big Data
As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity

etl data mining  Value of Big Data As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value. 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

etl data mining  mining, extraction, mining quarrying software comparison evaluation, trade, energy production, metals minerals trade, quarries,materials,exploration,extraction earth,eco-friendly extraction methods,environment,mining operations,mine maintenance,mining quarrying companies,mining erp,enterprise resource planning for mines exploration extraction,project maintenance management,process manufacturing management,hr software,international environmental laws,computerized maintenance management systems,extracting materials,process manufacturing,extraction method,tracking costs,quarrying inventory management tools,sales,profits,evaluate mining and quarrying solutions,mines quarries,gold quarry mine, quarry mine set, rock quarry mines,mine quarry trader,iron,undersea extraction,rock crusher,mineral,quarry software comparisons,underground surface mines. 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

etl data mining  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, bre Read More
Data Management and Business Performance: Part 1-Data
Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a

etl data mining  Management and Business Performance: Part 1-Data Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a business intelligence (BI) solution. Two topics resounded: the use of BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of their data as well as to ways to capture the most valuable 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

etl data mining  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. 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

etl 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
Backing up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices
This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions

etl data mining  up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions to the challenges of protecting distributed business data by establishing a private cloud/enterprise cloud. Learn which best practices can ensure business continuity throughout an organization with a distributed information Read More

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