Data Warehouse System
... Most companies have failed to implement ERP packages successfully or to realize the hoped-for financial returns on their ERP investment. Companies have had similar difficulties with each new wave of information technology since the first mainframe systems. It takes years to realize some envisioned I ...
... Most companies have failed to implement ERP packages successfully or to realize the hoped-for financial returns on their ERP investment. Companies have had similar difficulties with each new wave of information technology since the first mainframe systems. It takes years to realize some envisioned I ...
Metadata
... Size of the cell very important because it will reflect how entities are displayed (i.e., more specific shape with greater number of cells). ...
... Size of the cell very important because it will reflect how entities are displayed (i.e., more specific shape with greater number of cells). ...
Big Data - IOE Notes
... evaluated and describe how organizations demonstrate to regulators or other appropriate authorities the steps they have taken to support it. ...
... evaluated and describe how organizations demonstrate to regulators or other appropriate authorities the steps they have taken to support it. ...
A Future Scenario of interconnected EO Platforms
... Preparation of next ESA Ministerial Conference (December 2016): A specific element addressing EO-Innovation Europe concept will be proposed to ESA Member States within the EO Envelope Programme 5th period (2017-2021) This EOEP-5 element is currently called “EO Applications Platforms” Foreseen acti ...
... Preparation of next ESA Ministerial Conference (December 2016): A specific element addressing EO-Innovation Europe concept will be proposed to ESA Member States within the EO Envelope Programme 5th period (2017-2021) This EOEP-5 element is currently called “EO Applications Platforms” Foreseen acti ...
07 - datawarehouses
... data warehouse systems are well suited for on-line analytical processing, or OLAP OLAP operations use background knowledge regarding the domain of the data being studied in order to allow the presentation of data at different levels of abstraction Examples of OLAP operations include drill-down and r ...
... data warehouse systems are well suited for on-line analytical processing, or OLAP OLAP operations use background knowledge regarding the domain of the data being studied in order to allow the presentation of data at different levels of abstraction Examples of OLAP operations include drill-down and r ...
Data Warehousing
... of consistent, subject-oriented, historical data. By transforming data into meaningful information a DW allows business managers to perform more accurate & consistent analysis. Most Cost-effective decision making: DW helps to reduce overall cost of the product by reducing the number of channels. D ...
... of consistent, subject-oriented, historical data. By transforming data into meaningful information a DW allows business managers to perform more accurate & consistent analysis. Most Cost-effective decision making: DW helps to reduce overall cost of the product by reducing the number of channels. D ...
Database structure
... 1. What kinds of data models (e.g. UML) and database management systems (e.g. Oracle, MySQL) are being used? The various labs in our center (individual labs) use a range of RDBMS systems (Access, mySQL, Oracle 8i & 9i, Postgresql and Microsoft SQL Server 2000). The Center’s database for data integra ...
... 1. What kinds of data models (e.g. UML) and database management systems (e.g. Oracle, MySQL) are being used? The various labs in our center (individual labs) use a range of RDBMS systems (Access, mySQL, Oracle 8i & 9i, Postgresql and Microsoft SQL Server 2000). The Center’s database for data integra ...
Lec. notes
... Data need not be replicated Less wastage of storage space Less data anomaly Reduced and controlled redundancy Tighter control of replicated data ...
... Data need not be replicated Less wastage of storage space Less data anomaly Reduced and controlled redundancy Tighter control of replicated data ...
Document
... • For organizational learning to take place, data from many sources must be gathered together and organized in a consistent and useful way – hence, Data Warehousing (DW) • DW allows an organization to archive snapshots of its data, and what it has noticed about its data ...
... • For organizational learning to take place, data from many sources must be gathered together and organized in a consistent and useful way – hence, Data Warehousing (DW) • DW allows an organization to archive snapshots of its data, and what it has noticed about its data ...
data cubes
... operational reports are fixed. An ad-hoc report would require software development Database query systems provide ad-hoc reporting but are inefficient (slow) for complex querying OLAP queries on precalculated data cubes handle a range of complex queries in reasonable response time. ...
... operational reports are fixed. An ad-hoc report would require software development Database query systems provide ad-hoc reporting but are inefficient (slow) for complex querying OLAP queries on precalculated data cubes handle a range of complex queries in reasonable response time. ...
Big Data in Building Energy Efficiency: Understanding of Big Data
... make sense of them and exploit their value. Big data refers to datasets that are terabytes to petabytes (and even exabytes) in size, and the massive sizes of these datasets extend beyond the ability of average database software tools to capture, store, manage, and analyze them effectively. The conce ...
... make sense of them and exploit their value. Big data refers to datasets that are terabytes to petabytes (and even exabytes) in size, and the massive sizes of these datasets extend beyond the ability of average database software tools to capture, store, manage, and analyze them effectively. The conce ...
The Use of Scripting Languages, Database Technology
... Many researchers currently house data for large research projects on disks or CDs. If several assistants are working with the data, then several copies of the same data set may exist. To synchronize any corrections or changes made to the data, all of the parties would have to make sure each copy is ...
... Many researchers currently house data for large research projects on disks or CDs. If several assistants are working with the data, then several copies of the same data set may exist. To synchronize any corrections or changes made to the data, all of the parties would have to make sure each copy is ...
ADO.NET Objects
... The following diagram illustrates the relationship between a .NET Framework data provider and a DataSet. ...
... The following diagram illustrates the relationship between a .NET Framework data provider and a DataSet. ...
Defining Data Warehouse Concepts and Terminology Chapter 3
... Ensures a successful data warehouse Encourages incremental development Provides a staged approach to an enterprisewide warehouse - Safe - Manageable - Proven - Recommended ...
... Ensures a successful data warehouse Encourages incremental development Provides a staged approach to an enterprisewide warehouse - Safe - Manageable - Proven - Recommended ...
Defining Data Warehouse Concepts and Terminology
... Ensures a successful data warehouse Encourages incremental development Provides a staged approach to an enterprisewide warehouse - Safe - Manageable - Proven - Recommended ...
... Ensures a successful data warehouse Encourages incremental development Provides a staged approach to an enterprisewide warehouse - Safe - Manageable - Proven - Recommended ...
foundations of business intelligence: databases and information
... The data warehouse extracts current and historical data from multiple operational systems inside the organization. These data are combined with data from external sources and reorganized into a central database designed for management reporting and analysis. The information directory provides users ...
... The data warehouse extracts current and historical data from multiple operational systems inside the organization. These data are combined with data from external sources and reorganized into a central database designed for management reporting and analysis. The information directory provides users ...
The Data Warehouse
... system (RDBMS) • based on standard, normalised relational tables • known technology, many supporting applications, portable • standard query interface (SQL) • supports easy summations and calculations • can support very large databases • can be slow when processing complex queries • established supp ...
... system (RDBMS) • based on standard, normalised relational tables • known technology, many supporting applications, portable • standard query interface (SQL) • supports easy summations and calculations • can support very large databases • can be slow when processing complex queries • established supp ...
SAS® Software and IBM® Corporation's DB2''- An End User Computing Strategy
... inspired, in part, by relational database technology; a prime example being mM's DB2. This paper is an attempt to layout one strategy for bridging the gap between the store of corporate data that may exist in a system like DB2; and the end user, who converts. that data into a thing of tangible value ...
... inspired, in part, by relational database technology; a prime example being mM's DB2. This paper is an attempt to layout one strategy for bridging the gap between the store of corporate data that may exist in a system like DB2; and the end user, who converts. that data into a thing of tangible value ...
NoSQL / Spring Data
... - Difficult to handle semi-structured data, e.g. varying attributes - Schema changes = downtime or $$ ...
... - Difficult to handle semi-structured data, e.g. varying attributes - Schema changes = downtime or $$ ...
Datamining :
... Data cleaning removes noise and inconsistent data Data integration combines multiple data sources if necessary ...
... Data cleaning removes noise and inconsistent data Data integration combines multiple data sources if necessary ...
Blue Group (ADO) - DePaul University
... • Strategic High-level data access objects – Provides a uniform interface to data for all business application programmers – Merges RDO and DAO ...
... • Strategic High-level data access objects – Provides a uniform interface to data for all business application programmers – Merges RDO and DAO ...
Data Warehousing: Not our fathers` spreadsheets
... RFI Committee Review of candidates by county data project committee consisting of curriculum directors, technology experts, principals and teachers: Achieve! Data Solutions ...
... RFI Committee Review of candidates by county data project committee consisting of curriculum directors, technology experts, principals and teachers: Achieve! Data Solutions ...
Data Exploration
... displayed in multiple windows and dynamically linked so that selecting records from a table will automatically highlight the corresponding features in a graph and a map. ...
... displayed in multiple windows and dynamically linked so that selecting records from a table will automatically highlight the corresponding features in a graph and a map. ...
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.""