Data mining - Binus Repository
... 4.3 Database Management Systems Database management system (DBMS) is a set of programs that provide users with tools to add, delete, access and analyze data stored in one location. Online transaction processing (OLTP) is when transactions are processed as soon as they occur. Relational databa ...
... 4.3 Database Management Systems Database management system (DBMS) is a set of programs that provide users with tools to add, delete, access and analyze data stored in one location. Online transaction processing (OLTP) is when transactions are processed as soon as they occur. Relational databa ...
M359 Relational databases: theory and practice
... meaningful content from this file. 5. Don’t spend too long trying to interpret the content of the file; you can use a simple text editor like Microsoft Notepad to open the file, then skip straight on to the discussion. ...
... meaningful content from this file. 5. Don’t spend too long trying to interpret the content of the file; you can use a simple text editor like Microsoft Notepad to open the file, then skip straight on to the discussion. ...
data warehouse
... Indicate how data is derived from enterprise data warehouses, including derivation rules Indicate how data is derived from operational data store, including derivation rules Identify available reports and predefined queries Identify data analysis techniques (e.g. drilldown) ...
... Indicate how data is derived from enterprise data warehouses, including derivation rules Indicate how data is derived from operational data store, including derivation rules Identify available reports and predefined queries Identify data analysis techniques (e.g. drilldown) ...
A Review of Data Mining Techniques
... Mining Methodology: An important technical issue is whether it is better to set up a relational database structure or a multidimensional one. In a relational structure, data is stored in tables, permitting ad hoc queries. In a multidimensional structure, on the other hand, sets of cubes are arranged ...
... Mining Methodology: An important technical issue is whether it is better to set up a relational database structure or a multidimensional one. In a relational structure, data is stored in tables, permitting ad hoc queries. In a multidimensional structure, on the other hand, sets of cubes are arranged ...
Combining Data Integration and Information Extraction Techniques
... automatic creation of the global schema all the data sources used by ESTEST will be transformed to an ESTEST data model. Each construct in the external model also has a set of transformations to map onto the ESTEST data model. Once all the data sources have been transformed to this standard represe ...
... automatic creation of the global schema all the data sources used by ESTEST will be transformed to an ESTEST data model. Each construct in the external model also has a set of transformations to map onto the ESTEST data model. Once all the data sources have been transformed to this standard represe ...
chap01r
... Repository – centralized storehouse of metadata Database Management System (DBMS) – software for managing the database Database – storehouse of the data Application Programs – software using the data User Interface – text and graphical displays to users Data Administrators – personnel responsible fo ...
... Repository – centralized storehouse of metadata Database Management System (DBMS) – software for managing the database Database – storehouse of the data Application Programs – software using the data User Interface – text and graphical displays to users Data Administrators – personnel responsible fo ...
A METHODOLOGY FOR GIS INTERFACING OF MARINE DATA
... and/or grids) and in 2.5D triangular irregular networks (TINs) [2]. In this paper note, the methods of marine data input to A/I are discussed, highlighting the importance of data preparation for data georeference, selection, and overlay [1]. The preparation of the 3D marine data in a way that 2D GIS ...
... and/or grids) and in 2.5D triangular irregular networks (TINs) [2]. In this paper note, the methods of marine data input to A/I are discussed, highlighting the importance of data preparation for data georeference, selection, and overlay [1]. The preparation of the 3D marine data in a way that 2D GIS ...
Delphix Virtualization Engine
... Virtualization is the creation of a virtual (rather than actual) version of something, such as an operating system, a server, a storage device, database, files or network resources. ...
... Virtualization is the creation of a virtual (rather than actual) version of something, such as an operating system, a server, a storage device, database, files or network resources. ...
IMPROVING THE QUALITY OF THE DECISION MAKING BY USING
... are examined and are already known, based on which is build a model or a template that can be applied to the new situations of the same type with the already known ones. The specialists in the field of data warehouses consider the data mining instruments as a evaluate form of OLAP instruments. The D ...
... are examined and are already known, based on which is build a model or a template that can be applied to the new situations of the same type with the already known ones. The specialists in the field of data warehouses consider the data mining instruments as a evaluate form of OLAP instruments. The D ...
Normalisation
... cannot be broken down into any smaller components all primary keys must remain unique every foreign key must have a matching primary key in its related table. ...
... cannot be broken down into any smaller components all primary keys must remain unique every foreign key must have a matching primary key in its related table. ...
Introduction To Data Mining
... some function. Regression may be linear (mapping into a linear function the set of given data or non-linear function. • For example, one may map saving amount to a person age as follows: samt = a*age+b, where constant a and b are determined by existing data • Fitting the rest of the data into a defi ...
... some function. Regression may be linear (mapping into a linear function the set of given data or non-linear function. • For example, one may map saving amount to a person age as follows: samt = a*age+b, where constant a and b are determined by existing data • Fitting the rest of the data into a defi ...
Entity-Relationship - Faculty Personal Web Page
... dictionary – Repository links data, process and logic models of an information system – Data elements that are included in the DFD must appear in the data model and visa versa – Each data store in a process model must relate to business objects represented in the data model ...
... dictionary – Repository links data, process and logic models of an information system – Data elements that are included in the DFD must appear in the data model and visa versa – Each data store in a process model must relate to business objects represented in the data model ...
Data Mining with Big Data e-Health Service Using Map
... applications. Examples of online Big Data databases include MongoDB and other NoSQL databases. Offline Big Data encompasses applications that ingest, transform, manage and/or analyze Big Data in a batch context. They typically do not create new data. For these applications, response time can be slow ...
... applications. Examples of online Big Data databases include MongoDB and other NoSQL databases. Offline Big Data encompasses applications that ingest, transform, manage and/or analyze Big Data in a batch context. They typically do not create new data. For these applications, response time can be slow ...
(Student#).
... Same file but data elements are integrated and shared among different files Program controls the structure of a database and access to data ...
... Same file but data elements are integrated and shared among different files Program controls the structure of a database and access to data ...
DataMining vs OLAP
... common Business Intelligence(BI) technologies. • Business intelligence refers to computer-based methods for identifying and extracting useful information from business data. • Data mining is the field of computer science which, deals with extracting interesting patterns from large sets of data. It c ...
... common Business Intelligence(BI) technologies. • Business intelligence refers to computer-based methods for identifying and extracting useful information from business data. • Data mining is the field of computer science which, deals with extracting interesting patterns from large sets of data. It c ...
An Overview of Data Warehouse and OLAP Technology
... different source” [2] 1.1 Data warehouse features: Subject Oriented – For a particular subject area we can use data warehouse. For example subjects as a product, customers, suppliers, revenue, sales, etc. An ongoing operations does not be forces by data warehouse, rather it emphasis on modelling and ...
... different source” [2] 1.1 Data warehouse features: Subject Oriented – For a particular subject area we can use data warehouse. For example subjects as a product, customers, suppliers, revenue, sales, etc. An ongoing operations does not be forces by data warehouse, rather it emphasis on modelling and ...
Integrated system for management of data - Gerda
... to resources and protection – These areas cover 40 % (17.500 km2) of Denmark – The mapping programme started in 1999 and will run until about 2015 – The programme is financed by a fee of 3 cents pr m3 of consumed water – The total cost is about 200 million Euro ...
... to resources and protection – These areas cover 40 % (17.500 km2) of Denmark – The mapping programme started in 1999 and will run until about 2015 – The programme is financed by a fee of 3 cents pr m3 of consumed water – The total cost is about 200 million Euro ...
Data Mining
... about Database Management? • The wrong approach to managing data adds complexity in the management of organizations. – The management of data should be part of the solution, not part of the problem. • You have a right to influence the management of data you need. – The management of databases is not ...
... about Database Management? • The wrong approach to managing data adds complexity in the management of organizations. – The management of data should be part of the solution, not part of the problem. • You have a right to influence the management of data you need. – The management of databases is not ...
Presto
... Presto = Performance • Horizontal scale out • Query execution is pipelined throughout memory • Vectorized columnar processing • Optimized data source readers (e.g. ORC) • Presto is written in highly tuned Java – Efficient in-memory data structures – Very careful coding of inner loops – Bytecode gen ...
... Presto = Performance • Horizontal scale out • Query execution is pipelined throughout memory • Vectorized columnar processing • Optimized data source readers (e.g. ORC) • Presto is written in highly tuned Java – Efficient in-memory data structures – Very careful coding of inner loops – Bytecode gen ...
Notes - University of Maryland at College Park
... • Entity sets may overlap • Customers and Employees CMSC424, Spring 2005 ...
... • Entity sets may overlap • Customers and Employees CMSC424, Spring 2005 ...
Ch03 Data Warehouse
... A type of database often used as an interim area for a data warehouse Oper marts - an operational data mart. Enterprise data warehouse (EDW) A data warehouse for the enterprise. Metadata: Data about data. In a data warehouse, metadata describe the contents of a data warehouse and the manner of its a ...
... A type of database often used as an interim area for a data warehouse Oper marts - an operational data mart. Enterprise data warehouse (EDW) A data warehouse for the enterprise. Metadata: Data about data. In a data warehouse, metadata describe the contents of a data warehouse and the manner of its a ...
Decision Support Systems 1201311 Data Warehousing
... Definitions and Concepts • A data warehouse (DW) is a pool of data produced to support decision making; it is also a repository of current and historical data of potential interest to managers throughout the organization. • Data are usually structured to be available in form ready for analytical pr ...
... Definitions and Concepts • A data warehouse (DW) is a pool of data produced to support decision making; it is also a repository of current and historical data of potential interest to managers throughout the organization. • Data are usually structured to be available in form ready for analytical pr ...
Improvisation of Incremental Computing In Hadoop Architecture
... model is not as simple as Map/Reduce. Also changes are required to make Hadoop and Hive frameworks work together in HadoopDB. It can perform like parallel databases along with high fault tolerance, ability to run in heterogeneous environments and software license cost as Hadoop and can reduce the da ...
... model is not as simple as Map/Reduce. Also changes are required to make Hadoop and Hive frameworks work together in HadoopDB. It can perform like parallel databases along with high fault tolerance, ability to run in heterogeneous environments and software license cost as Hadoop and can reduce the da ...
Building a Data Mining Model using Data Warehouse and OLAP
... decision-support systems to analyze aggregated information for sales, finance, budget, and many other types of applications. OLAP is about aggregating measures based on dimension hierarchies and storing these pre-calculated aggregations in a special data structure. With the help of pre-aggregations ...
... decision-support systems to analyze aggregated information for sales, finance, budget, and many other types of applications. OLAP is about aggregating measures based on dimension hierarchies and storing these pre-calculated aggregations in a special data structure. With the help of pre-aggregations ...
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.""