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. ...
Relational Databases vs Non-Relational Databases vs
... • Not a type of database, but rather a open-source software ecosystem that allows for massively parallel computing • No inherent structure (no conversion to relational or JSON needed) • Good for batch processing, large files, volume writes, parallel scans, sequential access • Great for large, distri ...
... • Not a type of database, but rather a open-source software ecosystem that allows for massively parallel computing • No inherent structure (no conversion to relational or JSON needed) • Good for batch processing, large files, volume writes, parallel scans, sequential access • Great for large, distri ...
Data Preprocessing
... Faulty data collection instruments Human or computer error at data entry Errors in data transmission ...
... Faulty data collection instruments Human or computer error at data entry Errors in data transmission ...
What is Data Warehouse?
... will assessing a lot of data doing a lot of calculations. This may result in halt in production system. If hundreds of such queries run same time with this resource, then how much resource allocation is done because of this how much work is done slowing make system efficiency low as with performance ...
... will assessing a lot of data doing a lot of calculations. This may result in halt in production system. If hundreds of such queries run same time with this resource, then how much resource allocation is done because of this how much work is done slowing make system efficiency low as with performance ...
Database administration
... Data administration functions and roles A function is a set of activities to be performed Individuals are assigned roles to perform certain activities Data administration functions may be performed by a: Data administrator Data administration staff Database development Database consultant Database ...
... Data administration functions and roles A function is a set of activities to be performed Individuals are assigned roles to perform certain activities Data administration functions may be performed by a: Data administrator Data administration staff Database development Database consultant Database ...
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Data Streams[Last Lecture] - Computer Science Unplugged
... One-time query vs. continuous query (being evaluated continuously as stream continues to arrive) ...
... One-time query vs. continuous query (being evaluated continuously as stream continues to arrive) ...
Document
... designed to extract information from data and to use such information as a basis for decision making • Decision support system (DSS): – Arrangement of computerized tools used to assist managerial decision making within a business – Usually requires extensive data “massaging” to produce information – ...
... designed to extract information from data and to use such information as a basis for decision making • Decision support system (DSS): – Arrangement of computerized tools used to assist managerial decision making within a business – Usually requires extensive data “massaging” to produce information – ...
Chapter 11
... disaster – key role of servers requires backup plans: redundant servers or shared servers ...
... disaster – key role of servers requires backup plans: redundant servers or shared servers ...
... When the data arrives more slowly than the system design rate, the best possible answer is provided • All data is considered. • Best analysis techniques are used. As the data flows faster than the system design rate the accuracy and/or precision of the solution degrades smoothly. System achieves pre ...
Reverse Engineering in Data Integration Software
... standardized systems from existing (usually transactional) systems. Integrated applications are complex solutions, whose complexity are determined by the economic processes they implement, the amount of data employed (millions of records grouped in hundreds of tables, databases, hundreds of GB) and ...
... standardized systems from existing (usually transactional) systems. Integrated applications are complex solutions, whose complexity are determined by the economic processes they implement, the amount of data employed (millions of records grouped in hundreds of tables, databases, hundreds of GB) and ...
REDCap - Division of Biostatistics
... • Consider the use of closed versus open systems (i.e., forced-choiced questions) • Use consistent units of measurement • Avoid requiring the respondent to make calculations whenever possible • Avoid mixing timeframes in a single section • Consider the consequences of creating incomplete or inadequa ...
... • Consider the use of closed versus open systems (i.e., forced-choiced questions) • Use consistent units of measurement • Avoid requiring the respondent to make calculations whenever possible • Avoid mixing timeframes in a single section • Consider the consequences of creating incomplete or inadequa ...
Data Models (cont…)
... • A data warehouse is centralized repository of information. • A data warehouse is arranged around the relevant subject areas important to the corporation as a whole. • A data warehouse is queryable source of data for enterprise. • A data warehouse is used for analysis and not for transaction proces ...
... • A data warehouse is centralized repository of information. • A data warehouse is arranged around the relevant subject areas important to the corporation as a whole. • A data warehouse is queryable source of data for enterprise. • A data warehouse is used for analysis and not for transaction proces ...
Download PDF
... Also (mentioned below a well), occasionally a need to ingest data after the original investigator has left, or without a specific request for curation from the investigator. You may have to chart workflows, listing all the steps such as data integrity checks of your files (like checksum, to make sur ...
... Also (mentioned below a well), occasionally a need to ingest data after the original investigator has left, or without a specific request for curation from the investigator. You may have to chart workflows, listing all the steps such as data integrity checks of your files (like checksum, to make sur ...
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[Powerpoint] - DataArchPredAnalytics20161210
... clients. Founded August 2010 and as of October 2015 we are an Insight company. ...
... clients. Founded August 2010 and as of October 2015 we are an Insight company. ...
Data Warehouses for Decision Support
... • What: A very large database containing materialized views of multiple, independent source databases. The views generally contain aggregation data (aka datacubes). • Why: The data warehouse (DW) supports read-only queries for new applications, e.g., DSS, OLAP & data mining. ...
... • What: A very large database containing materialized views of multiple, independent source databases. The views generally contain aggregation data (aka datacubes). • Why: The data warehouse (DW) supports read-only queries for new applications, e.g., DSS, OLAP & data mining. ...
Best Practice: Enable quality assessment of
... decisions as long as the right algorithms are used, gave again way to the insight that the principle of garbage-in, garbage-out still holds true. This fact combined with raising concerns regarding data platform usability, data literacy and trust put the quality aspect into the focus. Ironically gove ...
... decisions as long as the right algorithms are used, gave again way to the insight that the principle of garbage-in, garbage-out still holds true. This fact combined with raising concerns regarding data platform usability, data literacy and trust put the quality aspect into the focus. Ironically gove ...
Foundational Methodology for Data Science
... Organizations can then use these insights to take actions that ideally improve future outcomes. There are numerous rapidly evolving technologies for analyzing data and building models. In a remarkably short time, they have progressed from desktops to massively parallel warehouses with huge data volu ...
... Organizations can then use these insights to take actions that ideally improve future outcomes. There are numerous rapidly evolving technologies for analyzing data and building models. In a remarkably short time, they have progressed from desktops to massively parallel warehouses with huge data volu ...
The Database Approach to Data Management
... A contemporary business intelligence infrastructure features capabilities and tools to manage and analyze large quantities and different types of data from multiple sources. Easy-to-use query and reporting tools for casual business users and more sophisticated analytical toolsets for power users are ...
... A contemporary business intelligence infrastructure features capabilities and tools to manage and analyze large quantities and different types of data from multiple sources. Easy-to-use query and reporting tools for casual business users and more sophisticated analytical toolsets for power users are ...
The Impact of Always-on Connectivity for Geospatial
... interface and a horizontally scalable distributed architecture that runs on commodity hardware or in the cloud. Innovative enterprises use MemSQL to better predict and react to opportunities by extracting previously untapped value in their data to drive new revenue. MemSQL is deployed across hundred ...
... interface and a horizontally scalable distributed architecture that runs on commodity hardware or in the cloud. Innovative enterprises use MemSQL to better predict and react to opportunities by extracting previously untapped value in their data to drive new revenue. MemSQL is deployed across hundred ...
SI433-071045-690-1 325KB Nov 04 2011 10
... 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 ...
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.""