DataNucleus (formerly known as Java Persistent Objects JPOX) is an open source project (under the Apache 2 license) which provides software products around data management in Java. The DataNucleus project started in 2008 (the JPOX project started in 2003 and was relaunched as DataNucleus in 2008 with broader scope). DataNucleus Access Platform is a fully compliant implementation of the Java Data Objects (JDO) 1.0, 2.0, 2.1, 2.2, 3.0, 3.1, 3.2 specifications (JSR 0012, JSR 0243) and the Java Persistence API (JPA) 1.0, 2.0, 2.1, 2.2 specifications (JSR 0220, JSR 0317, JSR 0338), providing transparent persistence of Java objects. It supports persistence to the widest range of datastores of any Java persistence software, supporting all of the main object-relational mapping (ORM) patterns, allows querying using either , JPQL or SQL, and comes with its own byte-code enhancer. It allows persistence to relational datastores (RDBMS), object-based datastores (db4o, ), document-based storage (XML, Excel, OpenDocument spreadsheets), web-based storage (JSON, Google Storage, Amazon Simple Storage Service), map-based datastores (HBase, Google's Bigtable, Apache Cassandra), graph-based datastores (Neo4j), document stores (MongoDB) as well as other types of datastores (e.g. LDAP). Its plugins are OSGi-compliant so can be used equally in an OSGi environment. DataNucleus Access Platform is also utilised by the persistence layer behind Google App Engine for Java, and VMForce (cloud offering from Salesforce.com and VMWare). (Wikipedia).
Data Modeling Tutorial | Data Modeling for Data Warehousing | Data Warehousing Tutorial | Edureka
***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, th
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Intro to Data Science: Historical Context
This lecture provides some historical context for data science and data-intensive scientific inquiry. Book website: http://databookuw.com/ Steve Brunton's website: eigensteve.com
From playlist Intro to Data Science
Intro to Data Science: What is Data Science?
This lecture provides an overview of the various components of data science, including data collection, cleaning, and curation, along with visualization, analysis, and machine learning (i.e. building models with data). These will be some of the topics discussed in this lecture series.
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This video introduces data visualization as a tool for exploring and communicating with data. Bing Brunton's website: www.bingbrunton.com
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Data Science Tutorial for Beginners - 1 | What is Data Science? | Data Analytics Tools | Edureka
( Data Science Training - https://www.edureka.co/data-science ) Data Science Blog Series: https://goo.gl/1CKTyN http://www.edureka.co/data-science Please write back to us at sales@edureka.co or call us at +91-8880862004 for more information. Data Science is all about extracting knowledge
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Learn Data Science Tutorial - Full Course for Beginners
Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the "sexiest job of the 21st century." You'll learn the important elements of data science. You'll be introduced to the principles, practices, and tools that make data science the powerful me
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Data Frames - Introduction to R Programming - Part 6
A Data frame is one of the main objects in R that you will often use when working with data in R. Learn how to access a data frame’s rows and columns, and look up the structure of a data frame. -- Learn more about Data Science Dojo here: https://datasciencedojo.com/data-science-bootcamp/
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10b Data Analytics: Spatial Continuity
Lecture on the impact of spatial continuity to motivate characterization and modeling of spatial continuity.
From playlist Data Analytics and Geostatistics
Queue Data Structure – Algorithms
This is an explanation of the dynamic data structure known as a queue. It compares a linear queue implemented by means of a dynamic array with a linear queue implemented with a static array. It also includes an explanation of how a circular queue works, along with pseudocode for the enqu
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Intro to Data Science: Answering Questions with Data
This lecture describes the central aspect of data science: asking and answering questions with data. In particular, we discuss the thought process and progression of questions one might ask and answer with data science. Book website: http://databookuw.com/ Steve Brunton's website: eigen
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