TRAC: Toward Recency And Consistency Reporting in a
... materialized views. In ICDE, pages 512-520, 1990. A. Labrinidis et al., Balancing performance and data freshness in web database servers. In VLDB, pages 393-404, 2003. L. Bright et al., Using latency-recency profiles for data delivery on the web. In VLDB, pages 550-561, 2002. H. Guo et al., Relaxed ...
... materialized views. In ICDE, pages 512-520, 1990. A. Labrinidis et al., Balancing performance and data freshness in web database servers. In VLDB, pages 393-404, 2003. L. Bright et al., Using latency-recency profiles for data delivery on the web. In VLDB, pages 550-561, 2002. H. Guo et al., Relaxed ...
Architecting the data layer for analytic applications in today’s data-intensive, high-
... a richer user experience and insights into data that neither dataset can provide on its own. Such applications cannot be structured as single SQL aggregate queries. Instead, they require a complex dataflow program where the output of one part of the application is the input of another. MR systems ca ...
... a richer user experience and insights into data that neither dataset can provide on its own. Such applications cannot be structured as single SQL aggregate queries. Instead, they require a complex dataflow program where the output of one part of the application is the input of another. MR systems ca ...
The rise of immutable data stores Some innovators are abandoning long-held database
... “Enterprises hedge their bets with NoSQL databases” described the big-picture basics, comparing and contrasting relational and nonrelational databases and how NoSQL databases have been filling a gap opened by the growth of heterogeneous data for customer-facing systems of engagement. “Using document ...
... “Enterprises hedge their bets with NoSQL databases” described the big-picture basics, comparing and contrasting relational and nonrelational databases and how NoSQL databases have been filling a gap opened by the growth of heterogeneous data for customer-facing systems of engagement. “Using document ...
Example: Data Mining for the NBA - The University of Texas at Dallas
... flight school; but des not care about takeoff or landing ...
... flight school; but des not care about takeoff or landing ...
Data Warehouse and Hive
... Big Data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process within a tolerable elapsed time. Big Data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes in a single data set. ...
... Big Data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process within a tolerable elapsed time. Big Data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes in a single data set. ...
Tree-Structured Indexes
... techniques: complex SQL queries and OLAP “multidimensional”queries (influenced by both SQL and spreadsheets). New techniques for database design, indexing, view maintenance, and interactive querying need to be ...
... techniques: complex SQL queries and OLAP “multidimensional”queries (influenced by both SQL and spreadsheets). New techniques for database design, indexing, view maintenance, and interactive querying need to be ...
Transaction Processing Systems
... Analysing data, in which output from transaction processing is input to different types of info systems o DSS – Provides solutions & consequences to managers to assist decision making (e.g. OLAP) Improve future performance via predictions based on historical data (data warehouse) Data mining, qu ...
... Analysing data, in which output from transaction processing is input to different types of info systems o DSS – Provides solutions & consequences to managers to assist decision making (e.g. OLAP) Improve future performance via predictions based on historical data (data warehouse) Data mining, qu ...
managing organizational data & information
... Organization need to devote considerable time to create a Data warehouse. Training to use data minning tools is also expensive. Some organizations may not need data warehouse; necessary information to support decision making from operational databases. ...
... Organization need to devote considerable time to create a Data warehouse. Training to use data minning tools is also expensive. Some organizations may not need data warehouse; necessary information to support decision making from operational databases. ...
Data Warehouse Schemas
... one entity that are related to a single instance in another table and vice versa. The possible cardinalities are: one-to-one (1:1), one-to-many (1:M), and many-to-many (M:M). C. ATTRIBUTES: Attributes describe the characteristics of properties of the entities. For clarification, attribute naming con ...
... one entity that are related to a single instance in another table and vice versa. The possible cardinalities are: one-to-one (1:1), one-to-many (1:M), and many-to-many (M:M). C. ATTRIBUTES: Attributes describe the characteristics of properties of the entities. For clarification, attribute naming con ...
Slide 1
... key families: HS2002, HS1996, HS1992, SITC Rev.3, SITC Rev.2, and SITC Rev.1 Explanatory notes are integrated with Comtrade SDMX. This is a beta version. The SDMX structure can be modified. Comtrade Web Services are open Site License users. For further information please go to http://comtrade.un.org ...
... key families: HS2002, HS1996, HS1992, SITC Rev.3, SITC Rev.2, and SITC Rev.1 Explanatory notes are integrated with Comtrade SDMX. This is a beta version. The SDMX structure can be modified. Comtrade Web Services are open Site License users. For further information please go to http://comtrade.un.org ...
Incremental Updates VS Full Reload
... Companies usually move changed data from source to target by performing extracts and loads. This approach often involves custom programming, monitoring and moving an entire data volume. The CONNX® DataSync tool solves theses issues with its point-and-click interface and pre-programmed selections. Ta ...
... Companies usually move changed data from source to target by performing extracts and loads. This approach often involves custom programming, monitoring and moving an entire data volume. The CONNX® DataSync tool solves theses issues with its point-and-click interface and pre-programmed selections. Ta ...
Data Warehousing : Data Models and OLAP opreations
... When deciding which technology to go for, consider: 1) Performance: • How fast will the system appear to the end-user? • MDD server vendors believe this is a key point in their favor. 2) Data volume and scalability: • While MDD servers can handle up to 50GB of storage, RDBMS servers can handle hund ...
... When deciding which technology to go for, consider: 1) Performance: • How fast will the system appear to the end-user? • MDD server vendors believe this is a key point in their favor. 2) Data volume and scalability: • While MDD servers can handle up to 50GB of storage, RDBMS servers can handle hund ...
GoldenGate For Real-Time Data Warehousing
... Staying Ahead of the Curve Problem solved? Not completely. Moving data from the production database to the data warehouse can typically be accomplished using extraction, transformation and load (ETL) utilities. These tools are reliable and capable of performing many of the tasks a data warehouse ne ...
... Staying Ahead of the Curve Problem solved? Not completely. Moving data from the production database to the data warehouse can typically be accomplished using extraction, transformation and load (ETL) utilities. These tools are reliable and capable of performing many of the tasks a data warehouse ne ...
DAMA-Big Data (R)evolution Presentation
... • Provide access to all data needed for analytics (internal or external) • Provide the ability to realistically interact with greater ‘depths’ of data – IE: tens of years instead of a couple of months • Provide a greater “speed to insight” for all types of requests • Lower the total cost of ownershi ...
... • Provide access to all data needed for analytics (internal or external) • Provide the ability to realistically interact with greater ‘depths’ of data – IE: tens of years instead of a couple of months • Provide a greater “speed to insight” for all types of requests • Lower the total cost of ownershi ...
Database Systems – Set Theory
... Data constantly changes on transactional systems Lack of historical data Often resources were taxed with both needs on the same systems Operational databases are designed to keep transactions from daily operations. It is optimized to efficiently update or create individual records A database for ana ...
... Data constantly changes on transactional systems Lack of historical data Often resources were taxed with both needs on the same systems Operational databases are designed to keep transactions from daily operations. It is optimized to efficiently update or create individual records A database for ana ...
E-Business Data Warehouse Design and Implementation
... A data warehouse collects, organizes, and makes data available for the purpose of analysis in order to give management the ability to access and analyze information about its business. This type of data can be called informational data. The systems used to work with informational data are referred t ...
... A data warehouse collects, organizes, and makes data available for the purpose of analysis in order to give management the ability to access and analyze information about its business. This type of data can be called informational data. The systems used to work with informational data are referred t ...
technical handout - Logo of semweb LLC
... a worldwide network that is also called “linked (open) data cloud” or “giant global graph“. For all those cases where the focus is less on the open and free usability of the data we speak simply of “linked data”. ...
... a worldwide network that is also called “linked (open) data cloud” or “giant global graph“. For all those cases where the focus is less on the open and free usability of the data we speak simply of “linked data”. ...
The National Bank of Poland’s warehouse-based reporting system
... 7 The SAS System is open, i.e. available on many hardware and software platforms; 7 The SAS System provides client-server architecture that allows to connect computers with various operating systems to each other; 7 Excellent communication with other database systems (dBase, Ingres) enables bi-direc ...
... 7 The SAS System is open, i.e. available on many hardware and software platforms; 7 The SAS System provides client-server architecture that allows to connect computers with various operating systems to each other; 7 Excellent communication with other database systems (dBase, Ingres) enables bi-direc ...
Chapter 1
... translation of this work beyond that permitted in Section 117 of the 1976 United States Copyright Act without express permission of the copyright owner is unlawful. Request for further information should be addressed to the Permissions Department, John Wiley & Sons, Inc. The purchaser may make back- ...
... translation of this work beyond that permitted in Section 117 of the 1976 United States Copyright Act without express permission of the copyright owner is unlawful. Request for further information should be addressed to the Permissions Department, John Wiley & Sons, Inc. The purchaser may make back- ...
MapReduce and Relational Database Management Systems
... compare the estimates of the costs of running a query on Hadoop MapReduce compared to PostgreSQL to choose the least costly technology. As the detailed analysis of the queries execution costs showed a gap mattering between both paradigms, hence the idea of the thorough analysis of the execution proc ...
... compare the estimates of the costs of running a query on Hadoop MapReduce compared to PostgreSQL to choose the least costly technology. As the detailed analysis of the queries execution costs showed a gap mattering between both paradigms, hence the idea of the thorough analysis of the execution proc ...
Different Data Warehouse Architecture Creation Criteria
... This shows different data sources that feed data into the data warehouse. The data source can be any format plain text file. Relational database other type of databases, Excel file, SQL data base, access MySQL, PostGreSQL data base. All can act as a data some. Many different types of data can be dat ...
... This shows different data sources that feed data into the data warehouse. The data source can be any format plain text file. Relational database other type of databases, Excel file, SQL data base, access MySQL, PostGreSQL data base. All can act as a data some. Many different types of data can be dat ...
Week 6
... Created by the ADO Data control at run-time based on the CommandType property (e.g. adCmdTable) If the Recordset object contains no records, the BOF and EOF properties are set to True, and the Recordset object's RecordCount property setting is 0 Any MOVE action will generate an error - so use t ...
... Created by the ADO Data control at run-time based on the CommandType property (e.g. adCmdTable) If the Recordset object contains no records, the BOF and EOF properties are set to True, and the Recordset object's RecordCount property setting is 0 Any MOVE action will generate an error - so use t ...
Using Rapid Prototyping to Develop a Data Mart
... You can reduce time and expense in the development of data marts by using the rapid prototyping method of development over the traditional method. The traditional method of developing a data mart involves frequent interaction among business analysts and business users, developers, and database admin ...
... You can reduce time and expense in the development of data marts by using the rapid prototyping method of development over the traditional method. The traditional method of developing a data mart involves frequent interaction among business analysts and business users, developers, and database admin ...
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.""