Time Series Databases

2014 Computers

Author : Ted Dunning
Release : 2014
Genre : Computers
Kind : eBook
Book Rating : 724/5 ( reviews)

Book Synopsis Time Series Databases by : Ted Dunning

Download or read book Time Series Databases written by Ted Dunning. This book was released on 2014. Available in PDF, EPUB and Kindle. Book excerpt: Time series data is of growing importance, especially with the rapid expansion of the Internet of Things. This concise guide shows you effective ways to collect, persist, and access large-scale time series data for analysis. You'll explore the theory behind time series databases and learn practical methods for implementing them. Authors Ted Dunning and Ellen Friedman provide a detailed examination of open source tools such as OpenTSDB and new modifications that greatly speed up data ingestion. You'll learn: A variety of time series use cases The advantages of NoSQL databases for large-scale time series data NoSQL table design for high-performance time series databases The benefits and limitations of OpenTSDB How to access data in OpenTSDB using R, Go, and Ruby How time series databases contribute to practical machine learning projects How to handle the added complexity of geo-temporal data For advice on analyzing time series data, check out Practical Machine Learning: A New Look at Anomaly Detection, also from Ted Dunning and Ellen Friedman.

Data Mining in Time Series Databases

2004 Computers

Author : Abraham Kandel
Release : 2004
Genre : Computers
Kind : eBook
Book Rating : 40X/5 ( reviews)

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Book Synopsis Data Mining in Time Series Databases by : Abraham Kandel

Download or read book Data Mining in Time Series Databases written by Abraham Kandel. This book was released on 2004. Available in PDF, EPUB and Kindle. Book excerpt: Adding the time dimension to real-world databases produces Time SeriesDatabases (TSDB) and introduces new aspects and difficulties to datamining and knowledge discovery. This book covers the state-of-the-artmethodology for mining time series databases. The novel data miningmethods presented in the book include techniques for efficientsegmentation, indexing, and classification of noisy and dynamic timeseries. A graph-based method for anomaly detection in time series isdescribed and the book also studies the implications of a novel andpotentially useful representation of time series as strings. Theproblem of detecting changes in data mining models that are inducedfrom temporal databases is additionally discussed.

Data Mining in Time Series Databases

2004 Mathematics

Author : Mark Last
Release : 2004
Genre : Mathematics
Kind : eBook
Book Rating : 909/5 ( reviews)

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Book Synopsis Data Mining in Time Series Databases by : Mark Last

Download or read book Data Mining in Time Series Databases written by Mark Last. This book was released on 2004. Available in PDF, EPUB and Kindle. Book excerpt: Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This book covers the state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the book also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed. Contents: A Survey of Recent Methods for Efficient Retrieval of Similar Time Sequences (H M Lie); Indexing of Compressed Time Series (E Fink & K Pratt); Boosting Interval-Based Literal: Variable Length and Early Classification (J J Rodriguez Diez); Segmenting Time Series: A Survey and Novel Approach (E Keogh et al.); Indexing Similar Time Series under Conditions of Noise (M Vlachos et al.); Classification of Events in Time Series of Graphs (H Bunke & M Kraetzl); Median Strings--A Review (X Jiang et al.); Change Detection in Classfication Models of Data Mining (G Zeira et al.). Readership: Graduate students, reseachers and practitioners in the fields of data mining, machine learning, databases and statistics.

Maxdata

2012-12-06 Business & Economics

Author : Wilhelm A. Hennerkes
Release : 2012-12-06
Genre : Business & Economics
Kind : eBook
Book Rating : 465/5 ( reviews)

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Book Synopsis Maxdata by : Wilhelm A. Hennerkes

Download or read book Maxdata written by Wilhelm A. Hennerkes. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: This handbook gives a detailed introduction to the Time Series Database System MAXDATA, which offers a very simple and convenient handling of voluminous numerical databases on a personal computer. It may be regarded as a special education and teaching instrument for the management and evaluation of empirical data and will teach the reader how to do empirical work without any effort. The handbook aims to give the reader a precise idea of the creation, management, documentation and evaluation of voluminous numerical databases on a microcomputer and gives some tips for managing individual numerical databases, but also for having direct access to official national and international economic offline databases. We believe that you will not regret your decision to use MAXDATA in your day-to-day work with statistical data, analyses, graphics, reports etc. Our aim was to design a software product which solves all the major problems associated with professional, decentralized data processing, whilst meeting the highest user requirements for user-friendliness and performance. We hope we have succeeded; positive user response appear to prove our point. Why MAXDATA was created MAXDATA was born of frustration at the multiplicity of computer programs flooding the software market, many of which offer extremely high performance (almost to the point of confusion) but which can generally only be used by computer specialists or those who have undergone a long period of training.

A Comparison of NoSQL Time Series Databases

2015-05-21 Technology & Engineering

Author : Kevin Rudolph
Release : 2015-05-21
Genre : Technology & Engineering
Kind : eBook
Book Rating : 757/5 ( reviews)

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Book Synopsis A Comparison of NoSQL Time Series Databases by : Kevin Rudolph

Download or read book A Comparison of NoSQL Time Series Databases written by Kevin Rudolph. This book was released on 2015-05-21. Available in PDF, EPUB and Kindle. Book excerpt: Research Paper (undergraduate) from the year 2015 in the subject Engineering - Industrial Engineering and Management, grade: 1,0, Technical University of Berlin (Wirtschaftsinformatik - Information Systems Engineering (ISE)), course: Seminar: Hot Topics in Information Systems Engineering, language: English, abstract: During the last years NoSQL databases have been developed to ad-dress the needs of tremendous performance, reliability and horizontal scalability. NoSQL time series databases (TSDBs) have risen to combine valuable NoSQL properties with characteristics of time series data encountering many use-cases. Solutions offer the efficient handling of data volume and frequency related to time series. Developers and decision makers struggle with the choice of a TSDB among a large variety of solutions. Up to now no comparison exists focusing on the specific features and qualities of those heterogeneous applications. This paper aims to deliver two frameworks for the comparison of TSDBs, firstly with a focus on features and secondly on quality. Furthermore, we apply and evaluate the frameworks on up to seven open-source TSDBs such as InfluxDB and OpenTSDB. We come to the result that the investigated TSDBs differ mainly in support- and extension related points. They share performance-enhancing techniques, time-related query capabilities and data schemas optimized for the handling of time-series data.

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