Review on Data Warehouse, Data Mining and OLAP Technology: As
... of books borrowed by a member. Users can use data mining techniques on the data warehouse to extract different kinds of information which would eventually assist the decision making process of an organization (figure 3). For example, if certain books are rarely used by member of particular library, ...
... of books borrowed by a member. Users can use data mining techniques on the data warehouse to extract different kinds of information which would eventually assist the decision making process of an organization (figure 3). For example, if certain books are rarely used by member of particular library, ...
Data Acceleration: Architecture for the Modern Data
... of individual systems or simply trying to keep up with its own growth, having a modern data infrastructure in place that can collect relevant data can lead to differentiation by enabling data insights. But to extract valuable insights from data in this new world, organizations need to harness it fro ...
... of individual systems or simply trying to keep up with its own growth, having a modern data infrastructure in place that can collect relevant data can lead to differentiation by enabling data insights. But to extract valuable insights from data in this new world, organizations need to harness it fro ...
3.4 Overvieuw of various technical aspects in SDWH_v2.1
... In a generic SDWH system we identified four functional layers, starting from the most detailed bottom level up to the top of the SDWH architecture where conceptual level is placed. The ground level corresponds to the area where the process starts, while the top of the pile is where the data warehous ...
... In a generic SDWH system we identified four functional layers, starting from the most detailed bottom level up to the top of the SDWH architecture where conceptual level is placed. The ground level corresponds to the area where the process starts, while the top of the pile is where the data warehous ...
A Design of a Financial Management Information System
... in particular a sharp increase widely used database technology and computer networks, the amount of data businesses have. In the large amounts of data and information, it bears the pros and cons of business operations, if possible with such vast amounts of data quickly and efficiently in-depth infor ...
... in particular a sharp increase widely used database technology and computer networks, the amount of data businesses have. In the large amounts of data and information, it bears the pros and cons of business operations, if possible with such vast amounts of data quickly and efficiently in-depth infor ...
Kevin S. Goff – Brief BIO
... • Much of successful data warehousing is like running a medical practice, a legal practice, etc. – many best/recommended practices, many proven methodologies, many patterns, etc. • This presentation is going to cover a variety of scenarios • Based on custom courseware - packed w/details to help long ...
... • Much of successful data warehousing is like running a medical practice, a legal practice, etc. – many best/recommended practices, many proven methodologies, many patterns, etc. • This presentation is going to cover a variety of scenarios • Based on custom courseware - packed w/details to help long ...
Hadoop Integrating with Oracle Data Warehouse and Data Mining
... • Dimensional squeezing scale data processing • Managing hundreds or thousands of processors • Managing parallelization and distribution • I/O Scheduling • Status and monitoring • Fault/crash tolerance MapReduce technology provides all of these, easily! ...
... • Dimensional squeezing scale data processing • Managing hundreds or thousands of processors • Managing parallelization and distribution • I/O Scheduling • Status and monitoring • Fault/crash tolerance MapReduce technology provides all of these, easily! ...
An Overview of Business Intelligence Technology
... on some of these technologies). We therefore chose to focus on technology where research can play, or has historically played, an important role. In some instances, these technologies are mature but challenging research problems still remain—for example, data storage, OLAP servers, RDBMSs, and ETL t ...
... on some of these technologies). We therefore chose to focus on technology where research can play, or has historically played, an important role. In some instances, these technologies are mature but challenging research problems still remain—for example, data storage, OLAP servers, RDBMSs, and ETL t ...
An Overview of Business Intelligence Technology
... on some of these technologies). We therefore chose to focus on technology where research can play, or has historically played, an important role. In some instances, these technologies are mature but challenging research problems still remain—for example, data storage, OLAP servers, RDBMSs, and ETL t ...
... on some of these technologies). We therefore chose to focus on technology where research can play, or has historically played, an important role. In some instances, these technologies are mature but challenging research problems still remain—for example, data storage, OLAP servers, RDBMSs, and ETL t ...
Data Warehousing: the New Knowledge Management Architecture
... ticket - an online message displays the large number of databases the warehouse is interrogating to locate the best ticket prices, and all carried out in a matter of seconds. It was this desire for greater analysis of business and scientific data that brought about the introduction of data warehouse ...
... ticket - an online message displays the large number of databases the warehouse is interrogating to locate the best ticket prices, and all carried out in a matter of seconds. It was this desire for greater analysis of business and scientific data that brought about the introduction of data warehouse ...
Database Systems Design, Implementation and Management
... The description of computer files requires a specialized vocabulary, different terminology for each discipline. This allowed for easy, clear communication between practitioners. DP Specialists created programs to retrieve, manipulate and present it to the user’s request. As more and more computerize ...
... The description of computer files requires a specialized vocabulary, different terminology for each discipline. This allowed for easy, clear communication between practitioners. DP Specialists created programs to retrieve, manipulate and present it to the user’s request. As more and more computerize ...
A query based approach for integrating heterogeneous data sources
... the sources, i.e. metadata, must be available. If users have little or no knowledge about the structure and the characteristics of the underlying data sources, some \approximate" or \fuzzy" search is still possible. Alternatively, if users know the underlying data sources and their query capabilitie ...
... the sources, i.e. metadata, must be available. If users have little or no knowledge about the structure and the characteristics of the underlying data sources, some \approximate" or \fuzzy" search is still possible. Alternatively, if users know the underlying data sources and their query capabilitie ...
A Database System with Amnesia
... 8th Biennial Conference on Innovative Data Systems Research (CIDR ‘17) January 8-11, 2017 , Chaminade, California, USA. ...
... 8th Biennial Conference on Innovative Data Systems Research (CIDR ‘17) January 8-11, 2017 , Chaminade, California, USA. ...
Chapter 2-021112
... operations. This information is used by Data Modellers, application programmers, system administrators, database administrators and software tools. Technical metadata includes information about data definition, data format, processes, source data, target data, and the rules and processes that are us ...
... operations. This information is used by Data Modellers, application programmers, system administrators, database administrators and software tools. Technical metadata includes information about data definition, data format, processes, source data, target data, and the rules and processes that are us ...
Access, Modify, Enhance: Self-Service Data Management in SAS® Visual Analytics
... users’ ad hoc data sources in a self-service manner for data analysis without depending on the IT resources. Apart from just access to ad hoc data source, there is also an increasing need to enhance data suitable for the needs of analysis and without the need to request that the IT department make c ...
... users’ ad hoc data sources in a self-service manner for data analysis without depending on the IT resources. Apart from just access to ad hoc data source, there is also an increasing need to enhance data suitable for the needs of analysis and without the need to request that the IT department make c ...
System development with Java
... • The DataSet's disconnected nature allows it to be transformed into XML and sent over the wire via HTTP if appropriate. • A connected DataReader cannot be serialized and thus cannot be passed between physical-tier boundaries where only string (XML) data can go. • A connected DataReader is associate ...
... • The DataSet's disconnected nature allows it to be transformed into XML and sent over the wire via HTTP if appropriate. • A connected DataReader cannot be serialized and thus cannot be passed between physical-tier boundaries where only string (XML) data can go. • A connected DataReader is associate ...
Enhancing scientific information systems with semantic annotations
... way. Declarative semantic rules coupled with ontologies are promising means to develop context-aware semantic interoperability. Management of scientific data requires a high level of extensibility which is generally much higher than in enterprise IS. Functionalities in an enterprise IS are all direc ...
... way. Declarative semantic rules coupled with ontologies are promising means to develop context-aware semantic interoperability. Management of scientific data requires a high level of extensibility which is generally much higher than in enterprise IS. Functionalities in an enterprise IS are all direc ...
1 CHAPTER 2 STUDY LITERATURE 2.1 General Theory 2.1.1 Data
... the organizations. However, the building of a data warehouse can take several years, which is why some organizations are building data marts. Data marts support ...
... the organizations. However, the building of a data warehouse can take several years, which is why some organizations are building data marts. Data marts support ...
What Is Relational Data Modeling?
... Data integration: Mapping source and target We're focusing on basic data modeling — what data we are talking about (inventory of elements), how it fits together (rules of behavior and relationships), and what it looks like (shape, size, and so on). A data model doesn't provide the full complement ...
... Data integration: Mapping source and target We're focusing on basic data modeling — what data we are talking about (inventory of elements), how it fits together (rules of behavior and relationships), and what it looks like (shape, size, and so on). A data model doesn't provide the full complement ...
An Overview of Data Warehousing, Data mining, OLAP and
... and database management systems to attempt to pull knowledge form stored data. Data mining is the process of applying intelligent methods to extract data patterns. This is done using the front-end tools. The spreadsheet is still the most compiling front-end Application for Online Analytical Processi ...
... and database management systems to attempt to pull knowledge form stored data. Data mining is the process of applying intelligent methods to extract data patterns. This is done using the front-end tools. The spreadsheet is still the most compiling front-end Application for Online Analytical Processi ...
Data Streams and Data Stream Management Systems
... where all the relevant data is kept and whose updates are relatively rare (almost true for traditional relational databases but not for data streams). This approach has a negative trend on performance if there are many rules to be processed (more than a given threshold) or when the data arrival rate ...
... where all the relevant data is kept and whose updates are relatively rare (almost true for traditional relational databases but not for data streams). This approach has a negative trend on performance if there are many rules to be processed (more than a given threshold) or when the data arrival rate ...
Chapter 19
... Fragments may be replicated. Fragments/replicas allocated to sites. Sites linked by a communications network. Data at each site is under control of a DBMS. DBMSs handle local appns autonomously. Each DBMS participates in at least one global ...
... Fragments may be replicated. Fragments/replicas allocated to sites. Sites linked by a communications network. Data at each site is under control of a DBMS. DBMSs handle local appns autonomously. Each DBMS participates in at least one global ...
Best Practices for Implementing a Data Warehouse on the Oracle
... Companies are recognizing the value of an enterprise data warehouse (EDW). A true EDW provides a single 360-degree view of the business and a powerful platform for a wide spectrum of business intelligence tasks ranging from predictive analysis to near real-time strategic and tactical decision suppor ...
... Companies are recognizing the value of an enterprise data warehouse (EDW). A true EDW provides a single 360-degree view of the business and a powerful platform for a wide spectrum of business intelligence tasks ranging from predictive analysis to near real-time strategic and tactical decision suppor ...
Oracle Database 12c for Data Warehousing and Big Data
... partitioned by the same key. Together these partitioning optimizations are fundamental for accelerating performance for queries on very large database objects. The query performance techniques described here operate in a concerted fashion, and provide multiplicative performance gains. For example, a ...
... partitioned by the same key. Together these partitioning optimizations are fundamental for accelerating performance for queries on very large database objects. The query performance techniques described here operate in a concerted fashion, and provide multiplicative performance gains. For example, a ...
Data Mining and Data Warehousing Henryk Maciejewski Data
... Cubes and Subcubes • OLAP queries related to a subset of dimensions – Result is aggregated at query time from the NWAY cube – E.g., report on sales of all products over subsequent years – sum for all products and all months needs to be computed at run time – If there are many dimensions with high c ...
... Cubes and Subcubes • OLAP queries related to a subset of dimensions – Result is aggregated at query time from the NWAY cube – E.g., report on sales of all products over subsequent years – sum for all products and all months needs to be computed at run time – If there are many dimensions with high c ...
Data Mining - Lyle School of Engineering
... Online Analytic Processing (OLAP): provides more complex queries than OLTP. OnLine Transaction Processing (OLTP): traditional database/transaction processing. Dimensional data; cube view Support ad hoc querying Require analysis of data Can be thought of as an extension of some of the basic aggregati ...
... Online Analytic Processing (OLAP): provides more complex queries than OLTP. OnLine Transaction Processing (OLTP): traditional database/transaction processing. Dimensional data; cube view Support ad hoc querying Require analysis of data Can be thought of as an extension of some of the basic aggregati ...
Big data
Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, and information privacy. The term often refers simply to the use of predictive analytics or other certain advanced methods to extract value from data, and seldom to a particular size of data set. Accuracy in big data may lead to more confident decision making. And better decisions can mean greater operational efficiency, cost reduction and reduced risk.Analysis of data sets can find new correlations, to ""spot business trends, prevent diseases, combat crime and so on."" Scientists, business executives, practitioners of media and advertising and governments alike regularly meet difficulties with large data sets in areas including Internet search, finance and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, and biological and environmental research.Data sets grow in size in part because they are increasingly being gathered by cheap and numerous information-sensing mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers, and wireless sensor networks. The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s; as of 2012, every day 2.5 exabytes (2.5×1018) of data were created; The challenge for large enterprises is determining who should own big data initiatives that straddle the entire organization.Work with big data is necessarily uncommon; most analysis is of ""PC size"" data, on a desktop PC or notebook that can handle the available data set.Relational database management systems and desktop statistics and visualization packages often have difficulty handling big data. The work instead requires ""massively parallel software running on tens, hundreds, or even thousands of servers"". What is considered ""big data"" varies depending on the capabilities of the users and their tools, and expanding capabilities make Big Data a moving target. Thus, what is considered ""big"" one year becomes ordinary later. ""For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration.""