Administrasi Basis Data
... Instances and Schemas • Similar to types and variables in programming languages • Schema – the logical structure of the database – e.g., the database consists of information about a set of customers and accounts and the relationship between them) – Analogous to type information of a variable in a p ...
... Instances and Schemas • Similar to types and variables in programming languages • Schema – the logical structure of the database – e.g., the database consists of information about a set of customers and accounts and the relationship between them) – Analogous to type information of a variable in a p ...
Chapter 1: Introduction
... – Different approaches: hierarchical, network, object oriented, semi-structured, etc. – Data independence principle ...
... – Different approaches: hierarchical, network, object oriented, semi-structured, etc. – Data independence principle ...
Slides
... Special measures to enforce security policies in which different users are granted different permissions to access diverse subsets of data This becomes tedious and inconvenient, especially at large-scale, with evolving/new user queries and higher probability of failures! ...
... Special measures to enforce security policies in which different users are granted different permissions to access diverse subsets of data This becomes tedious and inconvenient, especially at large-scale, with evolving/new user queries and higher probability of failures! ...
- Third Coast Software Foundry
... shell which conceptually integrates a relational database like Sybase or Oracle into the UNIX file system; state-of-the-art database-enabled internet applications; multi-threaded database applications which unleash all of the power of the underlying hardware; and a system of metadata-driven programs ...
... shell which conceptually integrates a relational database like Sybase or Oracle into the UNIX file system; state-of-the-art database-enabled internet applications; multi-threaded database applications which unleash all of the power of the underlying hardware; and a system of metadata-driven programs ...
GIS Data Structures, Topology, Relational Databases, Accuracy Issues
... We want to make sure that we provide for a mix of conditions for wildlife. Therefore, we use GIS to query the database for those stands that meet our harvesting specification (we're after sawtimber only), that have: 1) immediately adjacent stands of the same type, 2) younger stands with thick cover, ...
... We want to make sure that we provide for a mix of conditions for wildlife. Therefore, we use GIS to query the database for those stands that meet our harvesting specification (we're after sawtimber only), that have: 1) immediately adjacent stands of the same type, 2) younger stands with thick cover, ...
ERP - Simponi
... A database constructed for quick searching, retrieval, ad-hoc queries, and ease of use An ERP system could exist without having a data warehouse. The trend, however, is that organizations ...
... A database constructed for quick searching, retrieval, ad-hoc queries, and ease of use An ERP system could exist without having a data warehouse. The trend, however, is that organizations ...
Pivotal GemFire XD DISTRIBUTED IN-MEMORY AND HADOOP-INTEGRATED SQL DATABASE
... meet requirements for reporting and analytics on current and historical data. Other times its just a default choice of starting with an RDBMS as the data management system. When companies choose to scale-out such applications in high concurrency deployments with thousands to hundreds of thousands of ...
... meet requirements for reporting and analytics on current and historical data. Other times its just a default choice of starting with an RDBMS as the data management system. When companies choose to scale-out such applications in high concurrency deployments with thousands to hundreds of thousands of ...
Data Warehouse
... Customized data for particular target audiences Ad-hoc query support Data mining capabilities ...
... Customized data for particular target audiences Ad-hoc query support Data mining capabilities ...
enterprise data strategy in the healthcare landscape
... data sources. Because schemas often change as project timelines progress, relational technology produces an inefficient cycle of constant ETL (extract load transform), where even a minor change like adding or replacing a column in a table becomes time- and resource-intensive. What’s more, because re ...
... data sources. Because schemas often change as project timelines progress, relational technology produces an inefficient cycle of constant ETL (extract load transform), where even a minor change like adding or replacing a column in a table becomes time- and resource-intensive. What’s more, because re ...
Paper-less Reporting: Online Data Review and Analysis Using SAS/PH-Clinical Software
... parameters needed to run the reports. These windows contain widgets, such as text boxes, pulldown lists, radio buttons, checkboxes, and command buttons. All of these widgets enable the end-users to create their reports in a "point-andclick" fashion with minimal effort. Using PHTemplates, the statist ...
... parameters needed to run the reports. These windows contain widgets, such as text boxes, pulldown lists, radio buttons, checkboxes, and command buttons. All of these widgets enable the end-users to create their reports in a "point-andclick" fashion with minimal effort. Using PHTemplates, the statist ...
Manufacturing Money with Your Own Data - The Business Case for Data Warehouse
... Business Information Direcctory critical to success Data access tools classification scheme needed Users should be given the data they need, and not have to gather it •BUILD it and they will come" Kevin Costner· Field of Dreams (the movie) ...
... Business Information Direcctory critical to success Data access tools classification scheme needed Users should be given the data they need, and not have to gather it •BUILD it and they will come" Kevin Costner· Field of Dreams (the movie) ...
Twitter Data Streaming and Capturing for Tourism
... The dashboard is a tool for enterprise data management, which displays live data to help decision-makers to build appropriate decisions. There are two types of dashboard, analytical and operational. Analytical dashboard used to display statistics as a visible data, the second type of dashboard, is t ...
... The dashboard is a tool for enterprise data management, which displays live data to help decision-makers to build appropriate decisions. There are two types of dashboard, analytical and operational. Analytical dashboard used to display statistics as a visible data, the second type of dashboard, is t ...
Essig Museum Inventory and Loans Database
... Used to select subsets of data or combinations of data from linked tables Two or more tables may be combined in one query using linked fields Data can be entered and changed (changes will propagate through the underlying tables) Queries can also be used to append one table to another, update records ...
... Used to select subsets of data or combinations of data from linked tables Two or more tables may be combined in one query using linked fields Data can be entered and changed (changes will propagate through the underlying tables) Queries can also be used to append one table to another, update records ...
Data Quality Metrics for Minimum Micro Dataset
... Further examining harmonization and comparability issues Providing a flexible platform that can be used at both surveillance centres and centrally, is adapted to local capacity, and can operate in a federated environment Adopting data access and sharing policies that meet the needs of all data provi ...
... Further examining harmonization and comparability issues Providing a flexible platform that can be used at both surveillance centres and centrally, is adapted to local capacity, and can operate in a federated environment Adopting data access and sharing policies that meet the needs of all data provi ...
ppt - Stanford University
... • Extraction: Get the data out of the source systems • Transformation: Convert the data into a useful format for analysis • Load: Get the data into the data warehouse (…and build indexes, materialized views, etc.) ...
... • Extraction: Get the data out of the source systems • Transformation: Convert the data into a useful format for analysis • Load: Get the data into the data warehouse (…and build indexes, materialized views, etc.) ...
A GDR Introduction for Clinicians
... Provide a framework and vocabulary you can use to create report specifications to give to your data analyst ...
... Provide a framework and vocabulary you can use to create report specifications to give to your data analyst ...
Extract Transform Load (ETL) Offload Reduce Growing Data
... Needless to say, the exponential growth in data and different data types is the main reason why the Big Data platform is appropriate for ETL offloading. Focusing on data driven strategies has never been as prevalent as it is now when data ingestion, data processing, data mining and data visualizatio ...
... Needless to say, the exponential growth in data and different data types is the main reason why the Big Data platform is appropriate for ETL offloading. Focusing on data driven strategies has never been as prevalent as it is now when data ingestion, data processing, data mining and data visualizatio ...
An Overview of Data Warehousing and OLAP Technology
... build the derived tables stored in the warehouse; building indices and other access paths; and partitioning to multiple target storage areas. In addition to populating the warehouse, a load utility must allow the system administrator to monitor status, to cancel, suspend and resume a load, and to re ...
... build the derived tables stored in the warehouse; building indices and other access paths; and partitioning to multiple target storage areas. In addition to populating the warehouse, a load utility must allow the system administrator to monitor status, to cancel, suspend and resume a load, and to re ...
Data warehouse
... on the high-level entities of business such as sales, products, and customers. This is in contrast to database systems, which deals with processes such as placing an order. ...
... on the high-level entities of business such as sales, products, and customers. This is in contrast to database systems, which deals with processes such as placing an order. ...
Oracle Data Sheet
... Oracle Data Mining’s embedded data mining in the database not only means that the data stays in the database but also that the mining tasks and data transformations are performed within the database. They can run automatically, asynchronously, and independently of any user interface. The Oracle11g D ...
... Oracle Data Mining’s embedded data mining in the database not only means that the data stays in the database but also that the mining tasks and data transformations are performed within the database. They can run automatically, asynchronously, and independently of any user interface. The Oracle11g D ...
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.""