- ShareStudies.com
... Non-spatial data: e.g., one-way streets, speed limits, traffic congestion ...
... Non-spatial data: e.g., one-way streets, speed limits, traffic congestion ...
C H A P T E R
... The Database Approach • The Database Management System Approach – A pool of related data is shared by multiple application programs. Rather than having separate data files, each application uses a collection of data that is either joined or related in the database. – A DBMS “knows” everything about ...
... The Database Approach • The Database Management System Approach – A pool of related data is shared by multiple application programs. Rather than having separate data files, each application uses a collection of data that is either joined or related in the database. – A DBMS “knows” everything about ...
Online Analytical Processing (OLAP) for Decision Support
... used to design a data mart that retrieves data from two operational relational databases. This example will demonstrate the important characteristics of dimensional modeling, even though, due to the space limitations, the number of tables and the amount of data is very small when compared to a real ...
... used to design a data mart that retrieves data from two operational relational databases. This example will demonstrate the important characteristics of dimensional modeling, even though, due to the space limitations, the number of tables and the amount of data is very small when compared to a real ...
Business Intelligence for SUPRA® WHITE PAPER
... Analytics for SUPRA Analytics for SUPRA enables multi-dimensional analysis of information from your operational SUPRA databases. This information is expressed in business measures that can reveal product performance, profit trends or productivity comparisons. Multi-dimensional analysis not only allo ...
... Analytics for SUPRA Analytics for SUPRA enables multi-dimensional analysis of information from your operational SUPRA databases. This information is expressed in business measures that can reveal product performance, profit trends or productivity comparisons. Multi-dimensional analysis not only allo ...
Long-term Archiving of Relational Databases with Chronos
... web application based on JSF). Export data from query results into XML, MS Excel, HTML or plain text files. Re-import query results into an external target DBM system with just a few mouse clicks. Chronos automatically performs the necessary physical migration, thus creates a consistent database eve ...
... web application based on JSF). Export data from query results into XML, MS Excel, HTML or plain text files. Re-import query results into an external target DBM system with just a few mouse clicks. Chronos automatically performs the necessary physical migration, thus creates a consistent database eve ...
Problems with Today`s Information Environment
... a subset of corporate-wide data that is of value to a specific groups of users. Its scope is confined to specific, selected groups, such as marketing data mart Independent vs. dependent (directly from warehouse) data mart ...
... a subset of corporate-wide data that is of value to a specific groups of users. Its scope is confined to specific, selected groups, such as marketing data mart Independent vs. dependent (directly from warehouse) data mart ...
Natix - Al Akhawayn University
... Data as centric view: Large number Storedata objects Need to parse the entire file for of tables But: processing every query Designing Nativecentric XML database Document all OOD systems are view: not enough systemsinformantion from scratch a single data item developed to in provide effi ...
... Data as centric view: Large number Storedata objects Need to parse the entire file for of tables But: processing every query Designing Nativecentric XML database Document all OOD systems are view: not enough systemsinformantion from scratch a single data item developed to in provide effi ...
Data integration and transformation o How to change the data from
... mining also requires data integration to find the frequent patterns from large available data. It doesn’t mean all sources are same type when we integrate the data from multiple sources. The sources may be different. Therefore, we need to combine them into a single schema. So there are several issue ...
... mining also requires data integration to find the frequent patterns from large available data. It doesn’t mean all sources are same type when we integrate the data from multiple sources. The sources may be different. Therefore, we need to combine them into a single schema. So there are several issue ...
Evolution of Database Technology
... petabyte-sized databases and managing tertiary storage effectively. Supporting thousands of information consumers with very heavy volume of information requests, including ad-hoc requests and standing orders for daily updates. Providing effective mechanisms for browsing and searching for the des ...
... petabyte-sized databases and managing tertiary storage effectively. Supporting thousands of information consumers with very heavy volume of information requests, including ad-hoc requests and standing orders for daily updates. Providing effective mechanisms for browsing and searching for the des ...
Best Practices in Data Integration: Advanced Data Management
... performance of your jobs, compare one job’s run against another run of the same or different jobs, and drill into a job to see which nodes contribute to the overall runtime . You can also see memory usage information for jobs, runtime and wall clock time performance numbers, and I/O use counts . You ...
... performance of your jobs, compare one job’s run against another run of the same or different jobs, and drill into a job to see which nodes contribute to the overall runtime . You can also see memory usage information for jobs, runtime and wall clock time performance numbers, and I/O use counts . You ...
Semantic Data Integration for Francisella tularensis novicida Proteomic and Genomic Data
... when these data are used together, false discovery rates inherent within those weaknesses could be reduced. The addition of corroborating data can be used to validate predictions that are on the edge of the statistical thresholds. For example, in proteomics experiments, a protein with three or more ...
... when these data are used together, false discovery rates inherent within those weaknesses could be reduced. The addition of corroborating data can be used to validate predictions that are on the edge of the statistical thresholds. For example, in proteomics experiments, a protein with three or more ...
Data Exploration and Discovery: A New Approach to
... OLAP tools can be used to report on the types of products customers are buying, but they often don’t help, for example, in understanding why customers buy certain products, or why they place products in a web shopping basket, but don’t actually purchase them. OLAP tools also don’t help in bringing o ...
... OLAP tools can be used to report on the types of products customers are buying, but they often don’t help, for example, in understanding why customers buy certain products, or why they place products in a web shopping basket, but don’t actually purchase them. OLAP tools also don’t help in bringing o ...
A Data Management Infrastructure for Bridge Monitoring
... [17, 18]. While XML based model representation has been shown appropriate, the XML based schemas often involve complex data structures such as nested data hierarchy. Designing a BrIM database that can support semi-structured and unstructured data schema would be greatly beneficial to take full advan ...
... [17, 18]. While XML based model representation has been shown appropriate, the XML based schemas often involve complex data structures such as nested data hierarchy. Designing a BrIM database that can support semi-structured and unstructured data schema would be greatly beneficial to take full advan ...
Three guiding principles to improve data security and
... embrace the new era of computing. The answers also help organizations focus in on key areas they may be neglecting with current approaches. 1. Organizations can’t protect data if they don’t know it exists. Sensitive data resides in structured and unstructured formats in production environments and n ...
... embrace the new era of computing. The answers also help organizations focus in on key areas they may be neglecting with current approaches. 1. Organizations can’t protect data if they don’t know it exists. Sensitive data resides in structured and unstructured formats in production environments and n ...
Benefits of data archiving in data warehouses
... manage data growth by implementing a partitioning schema in the traditional database management system (DBMS) to separate active data from historical data. However, partitioning in this way still may not reduce the overhead on the database because the indexes remain the same size. Partitioning does ...
... manage data growth by implementing a partitioning schema in the traditional database management system (DBMS) to separate active data from historical data. However, partitioning in this way still may not reduce the overhead on the database because the indexes remain the same size. Partitioning does ...
SQL – the natural language for analysis
... It is clear that SQL’s join code is easily readable – and code-able. The developer only specifies the semantic join condition and leaves the processing details - such as the order of the joins - to the SQL engine. 4. Aggregate Aggregation is an important step in the process of analyzing data sets. M ...
... It is clear that SQL’s join code is easily readable – and code-able. The developer only specifies the semantic join condition and leaves the processing details - such as the order of the joins - to the SQL engine. 4. Aggregate Aggregation is an important step in the process of analyzing data sets. M ...
Develop Your Own Web Data Mart with MYSQL
... Reports built by programmers, users or both? Runs on System i only or runs anywhere? ...
... Reports built by programmers, users or both? Runs on System i only or runs anywhere? ...
Database Data Integration
... • Pre-Integrated with Middleware & Applications • With Oracle BI including BI Standard Edition, BI Standard Edition One and BI Enterprise Edition • With Oracle Master Data Management (UCM, CDH, PIM) • With Oracle PeopleSoft and Oracle Siebel • With Oracle E-Business suite including Spend Analyzer, B ...
... • Pre-Integrated with Middleware & Applications • With Oracle BI including BI Standard Edition, BI Standard Edition One and BI Enterprise Edition • With Oracle Master Data Management (UCM, CDH, PIM) • With Oracle PeopleSoft and Oracle Siebel • With Oracle E-Business suite including Spend Analyzer, B ...
Proven strategies for archiving complex relational data
... In searching for the ideal archiving solution, some organizations consider in-house development, but soon realize that the short- and long-term costs do not offset the expected return on investment. Implementing an off-the-shelf archiving solution does offer advantages in faster acquisition and impl ...
... In searching for the ideal archiving solution, some organizations consider in-house development, but soon realize that the short- and long-term costs do not offset the expected return on investment. Implementing an off-the-shelf archiving solution does offer advantages in faster acquisition and impl ...
In database evolution, two directions of development are better than one
... will need to scale, then graph stores, either standalone or embedded in a platform, provide an answer. The latest twist in non-relational database technologies is the rise of so-called immutable databases such as Datomic, which can support high-volume event processing. Immutability isn’t a new conce ...
... will need to scale, then graph stores, either standalone or embedded in a platform, provide an answer. The latest twist in non-relational database technologies is the rise of so-called immutable databases such as Datomic, which can support high-volume event processing. Immutability isn’t a new conce ...
H7385-ITRON Customer Profile
... storage, servers, and software. Often remotely managed by Itron, these solutions are installed and certified for use in utilities’ data centers. Managing hundreds of terabytes of data, maximizing system performance, and optimizing IT costs are top concerns for Itron’s IT department. “One of the bigg ...
... storage, servers, and software. Often remotely managed by Itron, these solutions are installed and certified for use in utilities’ data centers. Managing hundreds of terabytes of data, maximizing system performance, and optimizing IT costs are top concerns for Itron’s IT department. “One of the bigg ...
Comparing Data Integration Algorithms
... extract more useful data and conclusions [3]. Another application of data integration is the combining of data sources that exist throughout the World Wide Web. The fact that web data sources are autonomous and heterogeneous makes the problem of web integration particularly tricky. Web integration c ...
... extract more useful data and conclusions [3]. Another application of data integration is the combining of data sources that exist throughout the World Wide Web. The fact that web data sources are autonomous and heterogeneous makes the problem of web integration particularly tricky. Web integration c ...
Data Warehouse - dbmanagement.info
... description of the old client and the old branch must be used with the old data warehouse schema • Usually, the data warehouse must assign a generalized key to these important dimensions in order to distinguish multiple snapshots of clients and branches over a period of time • There are different ty ...
... description of the old client and the old branch must be used with the old data warehouse schema • Usually, the data warehouse must assign a generalized key to these important dimensions in order to distinguish multiple snapshots of clients and branches over a period of time • There are different ty ...
EXHIBIT K - EDR Data Integration High Level Design
... Current JIS processing utilizes Change Data Capture to populate the database MFDB2STAGINGTABLES commonly referred as ODS DI-034. This database has been used as a staging area for the Enterprise Data Warehouse (EDW) to pull from and populate associated data warehouse databases. Since this database al ...
... Current JIS processing utilizes Change Data Capture to populate the database MFDB2STAGINGTABLES commonly referred as ODS DI-034. This database has been used as a staging area for the Enterprise Data Warehouse (EDW) to pull from and populate associated data warehouse databases. Since this database al ...
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.""