The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDMS)ijdms
Authors are invited to submit papers for this journal through e-mail ijdmsjournal@airccse.org or ijdmsjournal@aircconline.com Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal
International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDMS)ijdms
Authors are invited to submit papers for this journal through e-mail ijdmsjournal@airccse.org or ijdmsjournal@aircconline.com Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal
International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDMS) ijdms
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed and establishing new collaborations in these areas.
International Journal of Data Mining Systems & Applications (IJDSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Data Mining Systems & Applications . The journal focuses on all technical and practical aspects of Database Management Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced Data Mining Systems & Applications and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDBMS)MiajackB
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDBMS)MiajackB
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
An introduction to the FAIR principles and a discussion of key issues that must be addressed to ensure data is findable, accessible, interoperable and re-usable. The session explored the role of the CDISC and DDI standards for addressing these issues.
Presented by Gareth Knight at the ADMIT Network conference, organised by the Association for Data Management in the Tropics, in Antwerp, Belgium on December 1st 2015.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
This presentation was provided by Courtney R. Butler of The Federal Reserve Bank - Kansas City, during part two of the NISO two-part webinar "Building Data Science Skills: Strategic Support for the Work, Part Two," which was held on March 18, 2020.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
International Journal of Data Mining Systems & Applications (IJDSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Data Mining Systems & Applications. The journal focuses on all technical and practical aspects of Database Management Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced Data Mining Systems & Applications and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
The Web of Linked Open Data, or LOD, is the most relevant achievement of the Semantic Web. Initially proposed by Tim Berners-Lee in a seminal paper published in Scientific American in 2001, the Semantic Web envisions a web where software agents can interact with large volumes of structured, easy to process data. It is now when users have at our disposal the first, mature results of this vision. Among them, and probably the most significant ones, are the different LOD initiatives and projects that publish open data in standard formats like RDF.
This presentation provides an overview and comparison of different LOD initiatives in the area of patent information, and analyses potential opportunities for building new information services based on largely available datasets of patent information. Information is based on different interviews conducted with innovation agents and on the analysis of professional bibliography and current implementations.
LOD opportunities are not only restricted to information aggregators, but also to end-users and innovation agents that need to face with the difficulties of dealing with large amounts of data. In both cases, the opportunities offered by LOD need to be assessed, as LOD has just become a standard, universal method to distribute, share and access data.
This presentation was provided by Sophia Lafferty-Hess of Duke University, during part one of the NISO two-part webinar "Labor and Capacity for Research Data Management," which was held on March 11, 2020.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDMS) ijdms
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed and establishing new collaborations in these areas.
International Journal of Data Mining Systems & Applications (IJDSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Data Mining Systems & Applications . The journal focuses on all technical and practical aspects of Database Management Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced Data Mining Systems & Applications and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDBMS)MiajackB
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDBMS)MiajackB
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
An introduction to the FAIR principles and a discussion of key issues that must be addressed to ensure data is findable, accessible, interoperable and re-usable. The session explored the role of the CDISC and DDI standards for addressing these issues.
Presented by Gareth Knight at the ADMIT Network conference, organised by the Association for Data Management in the Tropics, in Antwerp, Belgium on December 1st 2015.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
This presentation was provided by Courtney R. Butler of The Federal Reserve Bank - Kansas City, during part two of the NISO two-part webinar "Building Data Science Skills: Strategic Support for the Work, Part Two," which was held on March 18, 2020.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
International Journal of Data Mining Systems & Applications (IJDSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Data Mining Systems & Applications. The journal focuses on all technical and practical aspects of Database Management Systems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced Data Mining Systems & Applications and establishing new collaborations in these areas.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
The Web of Linked Open Data, or LOD, is the most relevant achievement of the Semantic Web. Initially proposed by Tim Berners-Lee in a seminal paper published in Scientific American in 2001, the Semantic Web envisions a web where software agents can interact with large volumes of structured, easy to process data. It is now when users have at our disposal the first, mature results of this vision. Among them, and probably the most significant ones, are the different LOD initiatives and projects that publish open data in standard formats like RDF.
This presentation provides an overview and comparison of different LOD initiatives in the area of patent information, and analyses potential opportunities for building new information services based on largely available datasets of patent information. Information is based on different interviews conducted with innovation agents and on the analysis of professional bibliography and current implementations.
LOD opportunities are not only restricted to information aggregators, but also to end-users and innovation agents that need to face with the difficulties of dealing with large amounts of data. In both cases, the opportunities offered by LOD need to be assessed, as LOD has just become a standard, universal method to distribute, share and access data.
This presentation was provided by Sophia Lafferty-Hess of Duke University, during part one of the NISO two-part webinar "Labor and Capacity for Research Data Management," which was held on March 11, 2020.
International Journal of Database Management Systems (IJDBMS)ijfcst journal
The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this field, and establishing new collaborations in these areas.
Detailed slides of data resource management. The relationships among the many individual data elements stored in databases are based on one of several logical data structures, or models.
Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process using on-hand data management tools or traditional data processing applications.
to effectively analyze this kind of information is now seen as a key competitive advantage to better inform decisions. In order to do so, organizations employ Sentiment Analysis (SA) techniques on these data. However, the usage of social media around the world is ever-increasing, which considerably accelerates massive data generation and makes traditional SA systems unable to deliver useful insights. Such volume of data can be efficiently analyzed using the combination of SA techniques and Big Data technologies. In fact, big data is not a luxury but an essential necessary to make valuable predictions. However, there are some challenges associated with big data such as quality that could highly affect the SA systems’ accuracy that use huge volume of data. Thus, the quality aspect should be addressed in order to build reliable and credible systems. For this, the goal of our research work is to consider Big Data Quality Metrics (BDQM) in SA that rely of big data. In this paper, we first highlight the most eloquent BDQM that should be considered throughout the Big Data Value Chain (BDVC) in any big data project. Then, we measure the impact of BDQM on a novel SA method accuracy in a real case study by giving simulation results.
INTRODUCTION TO BIG DATA AND HADOOP
9
Introduction to Big Data, Types of Digital Data, Challenges of conventional systems - Web data, Evolution of analytic processes and tools, Analysis Vs reporting - Big Data Analytics, Introduction to Hadoop - Distributed Computing
Challenges - History of Hadoop, Hadoop Eco System - Use case of Hadoop – Hadoop Distributors – HDFS – Processing Data with Hadoop – Map Reduce.
Most of the time, when you hear about Artificial Intelligence (AI), people talk about new algorithms or even the computation power needed to train them. But Data is one of the most important factors in AI.
This is the BIg Data Presentation which I have submitted to the college. Big Data introduction and types of Big Data have been covered in this presentation.
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Unleashing the Power of Data_ Choosing a Trusted Analytics Platform.pdfEnterprise Wired
In this guide, we'll explore the key considerations and features to look for when choosing a Trusted analytics platform that meets your organization's needs and delivers actionable intelligence you can trust.
2. What’s Big Data:
• Big data is a term for data sets that are complex then traditional data processing
application software. Big data challenges include capturing data, data storage, data
analysis, search, sharing, transfer, visualization, querying, updating and information
privacy.
• Big data usually includes data sets with sizes beyond the ability of commonly used
software tools to capture, curate, manage, and process data within a tolerable
elapsed time.
• Big Data philosophy covers unstructured, semi-structured and structured data.The
main focus is on unstructured data.
Source:Wikipedia
3. Big Data Structure:
DATA STRUCTURES
“Unstructured”
Quasi structured
Semi
structured
Structure
d
NOTES
• Data hat has no inherent structure. Stored as different file types.
Examples: pdf, images etc.
• Textual data with inconsistent data formats. Examples: Web
click stream data.
• Text data with a discernable pattern, enabling parsing. Example:
XML data files that are self describing.
• Data with a defined data type, format. Example:Transaction
data.
Source: EMC proven professional