Best Hadoop Institutes : kelly tecnologies is the best Hadoop training Institute in Bangalore.Providing hadoop courses by realtime faculty in Bangalore.
Priya Singla is seeking a career opportunity in big data and data engineering. She has a Master's degree in Business Analytics from California State University, East Bay and a Bachelor's degree in Electronics and Electrical Engineering from Maharishi Dayanand University in India. She has skills in programming languages like SQL and Python, databases like Oracle SQL, and tools like Excel, PowerPoint, and Linux. Her academic projects include building a Hadoop cluster on AWS and setting up a Cloudera Hadoop cluster. She has work experience as an Assistant Manager of Project Operations at Bata India and as a Graduate Engineer Trainee at GE India.
Data analysis with pandas and scikit-learnGlib Kechyn
Definition and basic features of data analysis with python, pandas and scikit-learn. Brief explanation about most powerful features. Introduction part.
Amazon Neptune is a service that allows you to use graph structures and nodes to visualize stored data in an accessible way. You can find more in our blog entry: https://tinyurl.com/y623ff5j
All the sources are linked in the presentation.
Enjoy and don't forget to check out our blog and other social media!
LCloud Blog https://bit.ly/2Vgooz4
Facebook https://bit.ly/2tCqBJS
Twitter https://twitter.com/LCLOUD16
LinkedIn https://bit.ly/2syaQCr
YouTube https://bit.ly/2tGV62b
Questions? Feel free to ask:
kontakt@lcloud.pl
https://lcloud.pl/
The document discusses the confusing landscape of big data tools and applications. It provides an overview of the different types of structured and unstructured data as well as databases, analytics platforms, and visualization tools that can be used to manage and analyze both structured and unstructured data at massive scale. The document also includes various diagrams and infographics from different sources that depict the big data ecosystem and the many interrelated tools and technologies involved.
Krutika Deshpande is a Masters student at Northeastern University studying Information Systems. She has experience as a Business Analyst Intern at ServiceNow and as a Software Engineer at Cognizant Technology Solutions. She has strong technical skills in languages like Python, R, SQL and Java as well as BI tools like Tableau, Power BI and data integration tools. She has worked on various academic projects involving data analysis using tools like Apache Spark, R and Python.
Kushal Pal Singh has over 3 years of experience in data science. He currently works as a Data Scientist at Geospatial Data Analytics Pvt Ltd, where he develops systems for image color restoration, cloud filling, and satellite image processing using technologies like Python, OpenCV, MongoDB, and Amazon S3. Previously, he worked at Capgemini India Pvt Ltd for 2 years as a Senior Analyst conducting customer analytics, segmentation, and cross-sell modeling using R and SQL. He has skills in Python, R, machine learning algorithms, and databases like SQL, MongoDB, and Spark.
Priya Singla is seeking a career opportunity in big data and data engineering. She has a Master's degree in Business Analytics from California State University, East Bay and a Bachelor's degree in Electronics and Electrical Engineering from Maharishi Dayanand University in India. She has skills in programming languages like SQL and Python, databases like Oracle SQL, and tools like Excel, PowerPoint, and Linux. Her academic projects include building a Hadoop cluster on AWS and setting up a Cloudera Hadoop cluster. She has work experience as an Assistant Manager of Project Operations at Bata India and as a Graduate Engineer Trainee at GE India.
Data analysis with pandas and scikit-learnGlib Kechyn
Definition and basic features of data analysis with python, pandas and scikit-learn. Brief explanation about most powerful features. Introduction part.
Amazon Neptune is a service that allows you to use graph structures and nodes to visualize stored data in an accessible way. You can find more in our blog entry: https://tinyurl.com/y623ff5j
All the sources are linked in the presentation.
Enjoy and don't forget to check out our blog and other social media!
LCloud Blog https://bit.ly/2Vgooz4
Facebook https://bit.ly/2tCqBJS
Twitter https://twitter.com/LCLOUD16
LinkedIn https://bit.ly/2syaQCr
YouTube https://bit.ly/2tGV62b
Questions? Feel free to ask:
kontakt@lcloud.pl
https://lcloud.pl/
The document discusses the confusing landscape of big data tools and applications. It provides an overview of the different types of structured and unstructured data as well as databases, analytics platforms, and visualization tools that can be used to manage and analyze both structured and unstructured data at massive scale. The document also includes various diagrams and infographics from different sources that depict the big data ecosystem and the many interrelated tools and technologies involved.
Krutika Deshpande is a Masters student at Northeastern University studying Information Systems. She has experience as a Business Analyst Intern at ServiceNow and as a Software Engineer at Cognizant Technology Solutions. She has strong technical skills in languages like Python, R, SQL and Java as well as BI tools like Tableau, Power BI and data integration tools. She has worked on various academic projects involving data analysis using tools like Apache Spark, R and Python.
Kushal Pal Singh has over 3 years of experience in data science. He currently works as a Data Scientist at Geospatial Data Analytics Pvt Ltd, where he develops systems for image color restoration, cloud filling, and satellite image processing using technologies like Python, OpenCV, MongoDB, and Amazon S3. Previously, he worked at Capgemini India Pvt Ltd for 2 years as a Senior Analyst conducting customer analytics, segmentation, and cross-sell modeling using R and SQL. He has skills in Python, R, machine learning algorithms, and databases like SQL, MongoDB, and Spark.
Power BI Streaming Datasets - San Diego BI Users GroupGreg McMurray
We all love interactive experiences – and what better way to visualize change than to see it in Power BI? Streaming Datasets are part of the Power BI service that you can continually feed data into and watch your charts respond to the data changes. Greg will walk through the basics of setting up a real-time dashboard in addition to a real-world scenario of viewing the current demand for electricity for the western interconnection. This will be a great opportunity to see this feature in action.
The document is a resume for Advait Kulkarni which outlines his education, including a Master's degree in Data Science and Bachelor's degree in Computer Science, as well as relevant coursework. It also details his work experience as a Data Scientist, Data Analyst Intern, and Associate Data Engineer where he utilized tools like Python, SQL, Spark, and Tensorflow. Finally, it lists several of his projects analyzing Spotify music, classifying news articles, and analyzing Chicago taxi trips where he applied machine learning algorithms and data visualization techniques.
This document is a resume for Aastha Grover, who is seeking a full-time data science position starting in June 2017. She has a Master's degree in Information Systems from Northeastern University and is proficient in programming languages like R, Java, Python and databases like Neo4j, SQL Server and MongoDB. She has work experience in data science roles at Fidelity Investments and as a programmer analyst at Cognizant. She has also completed academic projects involving predictive modeling, big data analysis and recommendation systems.
Due to the 4th Industrial Revolution, the IT industry is making continuous progress. However, flood of unstructured big data through various devices are pouring in and the customers’ needs are becoming more complicated than ever. Although PostgreSQL is definitely an enterprise-class, high quality DBMS, several options require some reviews to meet the various purposes of corporate users.
In this session, we will introduce the concept of Graph Database (which has strength in relation-based data analysis during this hyper-connected era) and the synergy effect in combination of Postgres and NoSQL (Graph Database). Discover a direction of Postgres’ unlimited scalability.
This document is a resume for Vignesh Thulasi Dass summarizing his education and experience. He has a Master's degree in Data Analytics from Northeastern University and a Bachelor's degree in Computer Science. His skills include programming languages like R, Python, and SQL as well as tools like Hadoop, Tableau, and PowerBI. He has work experience as a Software Developer at Just Dial India where he performed website and data analysis. His academic projects include predicting Airbnb user bookings using R and Tableau and analyzing household energy consumption using PySpark and PowerBI. He also has leadership experience co-founding an NGO and being a member of clubs at Northeastern and in Bangalore.
Full-Time Roles : Business Intelligence Analyst, Data Analyst
Skills : Python, R, SQL, Machine Learning, Deep Learning
Tableau, Power Bi, Google Analytics,
Apache Spark
The document discusses the responsibilities of an IT professional including building and supporting an online media budgeting and tracking system, integrating data from various channels, and ensuring accurate client reporting and analytics. Additionally, the IT professional evaluates campaign KPIs, captures necessary metrics, and facilitates data transfers between client and internal systems using various technologies like APIs, databases, and ETL processes. Finally, the professional works with analytic teams to build data cubes and views for attribution and traffic analysis using tools such as HiveQL and Hadoop on the cloud.
This document provides an agenda and overview for a LoQutus Analytics & Insights event. The agenda includes introductions, presentations on scaling analytics with Microsoft, data-driven applications with R Shiny, and a networking drink reception. Presentations will cover LoQutus services, the analytics value chain, data focus components and services, data lakes vs data warehouses, self-service data experiences, and the Microsoft cloud data platform. The R Shiny presentation will discuss building interactive data apps in R.
The document discusses the key differences between data lakes and data warehouses. It provides examples of how a retail company can use a data lake to store various structured and unstructured data sources together. This allows data scientists to more easily combine different data types into models to forecast product demand and for marketing experts to analyze sentiment and determine sales focus. The document also lists some SAP tools for administering and working with data in a data lake, including the SAP HANA Database Explorer, SAP HANA Cockpit, and SAP HANA Cloud Central.
Version 1 of a much deeper topic that I intend to explore. The context is limited to my environment and industry. It's a topic that concerns every tech hiring manager looking for such roles right now.
ProspectR provides B2B marketing data and analytics through a cloud-based platform. Their platform allows users to build custom audiences for marketing campaigns based on firmographic and technographic filters. ProspectR aims to help B2B marketers find new customers and engage existing contacts more effectively through actionable insights and targeted outreach.
An attempt at categorizing the thriving big data ecosystem by @mattturck and @shivonZ - comments are welcome (please add your thoughts on mattturck.com)
This document provides an overview of AWS Glue, a fully managed ETL service for preparing and loading big data for analytics. It discusses what big data and analytics are, and describes the key components of Glue including the crawler, catalog, architecture and ETL jobs. Glue allows for easy, fast and cost-effective processing of vast amounts of data from sources like Amazon S3. It can be used to build data warehouses, run queries against data lakes, create event-driven pipelines, and understand data assets. The document provides examples of how Glue components like the crawler, catalog, and ETL jobs work together in a workflow.
Wordpress for Apps is a service that allows users to create mobile apps without programming. Their team has developed a proprietary engine that compiles apps natively and transcodes media, allowing apps to work across different devices. Their business model includes free and paid community tiers, as well as a revenue sharing model for publishers. They have seen traction with over 20,000 apps created and 1.2 million downloads since launching in October.
with this ppt you will learn about What could be the reason of uneven distribution of population of India? and the Major Factors and also the Minor-Factors.
1) Internet usage in the UK has grown tremendously from 3.6 million users in 1996 to 36.4 million users in 2009.
2) Broadband speeds have increased significantly with 90% of services now above 2Mb/s as of May 2009. Wireless broadband usage has also grown with 58% of people using it at home.
3) Younger and older demographics are increasingly using the internet with women aged 25-34 spending more time online than men and those over 50 accounting for 30% of total internet time despite being only 25% of online users.
Citizenship Through Geography Sagt 2009David Rogers
This document outlines 16 ways to teach citizenship through geography in an engaging manner for students. Some of the proposed activities include guerrilla geography campaigns to post thought-provoking messages in public spaces, evaluating protests and creating action manifestos, exploring moral dilemmas around issues like sustainability, and challenging stereotypes. The overall message is that citizenship education should involve hands-on activities to inspire positive social change rather than just learning about issues.
The document introduces in-store marketing technology called Motion Display that uses electronic paper displays to show animated content and advertisements. Research from multiple case studies and a controlled trial found that using Motion Display resulted in significantly increased sales, customer attention, and brand awareness compared to static signage, with some products seeing sales increases upwards of 100%. Motion Display is proven to be an effective sales tool that reinforces branding while shortening customer search times.
Ryan Sheehy’s APR Readiness Review PresentationRyan Sheehy
As part of the accreditation in public relations process, candidates must deliver an hour long presentation to a panel of APRs. This is meant to help showcase a candidate's professional experience and knowledge base of the 15 KSAs, which they will eventually be tested on.
The above PPT presentation was delivered by Ryan Sheehy, APR in November 2008 and served as a guide for her in-person meeting. She didn't use a computer. Rather, she provided full-color booklets to each panelist in order for them to follow along.
The document discusses the evolution of the World Wide Web from Web 1.0 to 3.0. It provides timelines and key milestones in the development of the early web from 1991 to 2009, including the launch of major websites and technologies like Google, YouTube, Facebook, and the iPhone. The growth of the web was fueled by increasing individual creativity, faster connectivity speeds, and lower data storage costs. While the late 1990s dot-com bubble led to major crashes, the web became mainstream and transformed business and consumer behavior.
Power BI Streaming Datasets - San Diego BI Users GroupGreg McMurray
We all love interactive experiences – and what better way to visualize change than to see it in Power BI? Streaming Datasets are part of the Power BI service that you can continually feed data into and watch your charts respond to the data changes. Greg will walk through the basics of setting up a real-time dashboard in addition to a real-world scenario of viewing the current demand for electricity for the western interconnection. This will be a great opportunity to see this feature in action.
The document is a resume for Advait Kulkarni which outlines his education, including a Master's degree in Data Science and Bachelor's degree in Computer Science, as well as relevant coursework. It also details his work experience as a Data Scientist, Data Analyst Intern, and Associate Data Engineer where he utilized tools like Python, SQL, Spark, and Tensorflow. Finally, it lists several of his projects analyzing Spotify music, classifying news articles, and analyzing Chicago taxi trips where he applied machine learning algorithms and data visualization techniques.
This document is a resume for Aastha Grover, who is seeking a full-time data science position starting in June 2017. She has a Master's degree in Information Systems from Northeastern University and is proficient in programming languages like R, Java, Python and databases like Neo4j, SQL Server and MongoDB. She has work experience in data science roles at Fidelity Investments and as a programmer analyst at Cognizant. She has also completed academic projects involving predictive modeling, big data analysis and recommendation systems.
Due to the 4th Industrial Revolution, the IT industry is making continuous progress. However, flood of unstructured big data through various devices are pouring in and the customers’ needs are becoming more complicated than ever. Although PostgreSQL is definitely an enterprise-class, high quality DBMS, several options require some reviews to meet the various purposes of corporate users.
In this session, we will introduce the concept of Graph Database (which has strength in relation-based data analysis during this hyper-connected era) and the synergy effect in combination of Postgres and NoSQL (Graph Database). Discover a direction of Postgres’ unlimited scalability.
This document is a resume for Vignesh Thulasi Dass summarizing his education and experience. He has a Master's degree in Data Analytics from Northeastern University and a Bachelor's degree in Computer Science. His skills include programming languages like R, Python, and SQL as well as tools like Hadoop, Tableau, and PowerBI. He has work experience as a Software Developer at Just Dial India where he performed website and data analysis. His academic projects include predicting Airbnb user bookings using R and Tableau and analyzing household energy consumption using PySpark and PowerBI. He also has leadership experience co-founding an NGO and being a member of clubs at Northeastern and in Bangalore.
Full-Time Roles : Business Intelligence Analyst, Data Analyst
Skills : Python, R, SQL, Machine Learning, Deep Learning
Tableau, Power Bi, Google Analytics,
Apache Spark
The document discusses the responsibilities of an IT professional including building and supporting an online media budgeting and tracking system, integrating data from various channels, and ensuring accurate client reporting and analytics. Additionally, the IT professional evaluates campaign KPIs, captures necessary metrics, and facilitates data transfers between client and internal systems using various technologies like APIs, databases, and ETL processes. Finally, the professional works with analytic teams to build data cubes and views for attribution and traffic analysis using tools such as HiveQL and Hadoop on the cloud.
This document provides an agenda and overview for a LoQutus Analytics & Insights event. The agenda includes introductions, presentations on scaling analytics with Microsoft, data-driven applications with R Shiny, and a networking drink reception. Presentations will cover LoQutus services, the analytics value chain, data focus components and services, data lakes vs data warehouses, self-service data experiences, and the Microsoft cloud data platform. The R Shiny presentation will discuss building interactive data apps in R.
The document discusses the key differences between data lakes and data warehouses. It provides examples of how a retail company can use a data lake to store various structured and unstructured data sources together. This allows data scientists to more easily combine different data types into models to forecast product demand and for marketing experts to analyze sentiment and determine sales focus. The document also lists some SAP tools for administering and working with data in a data lake, including the SAP HANA Database Explorer, SAP HANA Cockpit, and SAP HANA Cloud Central.
Version 1 of a much deeper topic that I intend to explore. The context is limited to my environment and industry. It's a topic that concerns every tech hiring manager looking for such roles right now.
ProspectR provides B2B marketing data and analytics through a cloud-based platform. Their platform allows users to build custom audiences for marketing campaigns based on firmographic and technographic filters. ProspectR aims to help B2B marketers find new customers and engage existing contacts more effectively through actionable insights and targeted outreach.
An attempt at categorizing the thriving big data ecosystem by @mattturck and @shivonZ - comments are welcome (please add your thoughts on mattturck.com)
This document provides an overview of AWS Glue, a fully managed ETL service for preparing and loading big data for analytics. It discusses what big data and analytics are, and describes the key components of Glue including the crawler, catalog, architecture and ETL jobs. Glue allows for easy, fast and cost-effective processing of vast amounts of data from sources like Amazon S3. It can be used to build data warehouses, run queries against data lakes, create event-driven pipelines, and understand data assets. The document provides examples of how Glue components like the crawler, catalog, and ETL jobs work together in a workflow.
Wordpress for Apps is a service that allows users to create mobile apps without programming. Their team has developed a proprietary engine that compiles apps natively and transcodes media, allowing apps to work across different devices. Their business model includes free and paid community tiers, as well as a revenue sharing model for publishers. They have seen traction with over 20,000 apps created and 1.2 million downloads since launching in October.
with this ppt you will learn about What could be the reason of uneven distribution of population of India? and the Major Factors and also the Minor-Factors.
1) Internet usage in the UK has grown tremendously from 3.6 million users in 1996 to 36.4 million users in 2009.
2) Broadband speeds have increased significantly with 90% of services now above 2Mb/s as of May 2009. Wireless broadband usage has also grown with 58% of people using it at home.
3) Younger and older demographics are increasingly using the internet with women aged 25-34 spending more time online than men and those over 50 accounting for 30% of total internet time despite being only 25% of online users.
Citizenship Through Geography Sagt 2009David Rogers
This document outlines 16 ways to teach citizenship through geography in an engaging manner for students. Some of the proposed activities include guerrilla geography campaigns to post thought-provoking messages in public spaces, evaluating protests and creating action manifestos, exploring moral dilemmas around issues like sustainability, and challenging stereotypes. The overall message is that citizenship education should involve hands-on activities to inspire positive social change rather than just learning about issues.
The document introduces in-store marketing technology called Motion Display that uses electronic paper displays to show animated content and advertisements. Research from multiple case studies and a controlled trial found that using Motion Display resulted in significantly increased sales, customer attention, and brand awareness compared to static signage, with some products seeing sales increases upwards of 100%. Motion Display is proven to be an effective sales tool that reinforces branding while shortening customer search times.
Ryan Sheehy’s APR Readiness Review PresentationRyan Sheehy
As part of the accreditation in public relations process, candidates must deliver an hour long presentation to a panel of APRs. This is meant to help showcase a candidate's professional experience and knowledge base of the 15 KSAs, which they will eventually be tested on.
The above PPT presentation was delivered by Ryan Sheehy, APR in November 2008 and served as a guide for her in-person meeting. She didn't use a computer. Rather, she provided full-color booklets to each panelist in order for them to follow along.
The document discusses the evolution of the World Wide Web from Web 1.0 to 3.0. It provides timelines and key milestones in the development of the early web from 1991 to 2009, including the launch of major websites and technologies like Google, YouTube, Facebook, and the iPhone. The growth of the web was fueled by increasing individual creativity, faster connectivity speeds, and lower data storage costs. While the late 1990s dot-com bubble led to major crashes, the web became mainstream and transformed business and consumer behavior.
Este documento describe la anatomía, movimientos y patologías más comunes del hombro. Explica que el hombro es la articulación más móvil del cuerpo y está compuesto por varias articulaciones y huesos como el húmero, clavícula y escápula. Detalla los principales músculos y movimientos del hombro como la abducción, flexión, extensión y rotación. Finalmente, enumera algunas patologías frecuentes como el pinzamiento subacromial, la tendinitis bicipital y la ruptura del m
Creating iOS and Android Apps with Visual Studio and C# mobiweave
Use Visual Studio and your C#/.NET skills to get your Windows apps into iOS and Android App stores. We will talk about using Xamarin's iOS and Android platforms to use Visual Studio develop and debug your apps. Use the entire Visual Studio's ecosystem of tools like Resharper to help you get more productive when developing mobile apps.
Presenter's Bio:
Ash DCosta is the founder and chief architect at Mobi Weave (http://mobiweave.com), a cloud and mobile solution provider. He has 20+ years of experience in software with Intel, i2 Technologies, IdentityMine, i3Connect and Wells Fargo.
Follow him at @softwareweaver.
An automated donor management system
Collections
The Trima Accel and other automated blood collection devices increase efficiency and flexibility for mobile and in-center blood drives.
Processing
Terumo's automated blood processing systems like the Spectra Optia improve lab efficiency, blood component quality, and process control.
Pathogen Reduction
Terumo is working to make transfusions safer for patients through pathogen reduction technologies with simple procedures for operators.
The document discusses the development of a theoretical framework and hypotheses in research. It explains that after conducting preliminary research like interviews and a literature review, the next step is to develop a theoretical framework. This involves identifying relevant variables, developing a conceptual model of relationships between variables, and providing explanations for these relationships. Hypotheses are then generated based on the theoretical framework. Hypotheses should be testable statements about expected relationships between variables. Null and alternative hypotheses are also discussed.
This document discusses elements of research design, including:
1. The purpose of a study can be exploratory, descriptive, or for hypothesis testing. Exploratory studies investigate unknown phenomena, descriptive studies characterize variables, and hypothesis testing examines relationships.
2. Types of investigation include causal studies that establish cause-and-effect and correlational studies that identify associated factors.
3. The extent of researcher interference ranges from minimal in correlational studies to manipulation and control in causal studies.
Este documento presenta una unidad didáctica sobre las estaciones del año y los sentidos dirigida a alumnos de educación infantil. La unidad se desarrollará a lo largo de una semana con cinco sesiones que incluyen actividades como lectura de cuentos, canciones, juegos y manualidades para familiarizar a los niños con cada estación, sus características y la ropa y frutas asociadas. El documento detalla los objetivos, contenidos, metodología, recursos, actividades y evaluación de la unidad didáctica
Este documento define la seguridad informática y explica que se trata de minimizar el impacto y riesgo mediante una organización efectiva. La seguridad se basa en tres pilares fundamentales: confidencialidad, integridad y disponibilidad, que protegen la información. También describe los elementos que se busca proteger con la seguridad informática: hardware, software, datos y elementos fungibles. Finalmente, explica que nos protegemos principalmente de factores humanos como empleados, hackers, intrusos y terroristas, así como de factores no humanos como errores de software y
WebSite Visit Forecasting Using Data Mining TechniquesChandana Napagoda
Data mining is a technique which is used for identifying relationships between various large amounts of data in many areas including scientific research, business planning, traffic analysis, clinical trial data mining etc. This research will be researching applicability of data mining techniques in web site visit prediction domain. Here we will be concentrating on time series regression techniques which will be used to analyse and forecast time dependent data points. Then how those techniques will be applied to forecast web site visits will be explained.
A Survey on Data Mapping Strategy for data stored in the storage cloud 111NavNeet KuMar
This document describes a method for processing large amounts of data stored in cloud storage using Hadoop clusters. Data is uploaded to cloud storage by users and then processed using MapReduce on Hadoop clusters. The method involves storing data in the cloud for processing and then running MapReduce algorithms on Hadoop clusters to analyze the data in parallel. The results are then stored back in the cloud for users to download. An architecture is proposed involving a controller that directs requests to Hadoop masters which coordinate nodes to perform mapping and reducing of data according to the algorithm implemented.
TechoERP, which is hosted in the cloud, is especially beneficial to businesses since it gives them access to full-featured apps at a low cost without requiring a large initial investment in hardware and software. A company can rapidly scale their business productivity software using the right cloud provider as their business grows or a new company is added.
This poster represents 4 months of work on the MSc project while doing a double degree at Heriot-Watt University.
£50 have been given for rewarding this work.
The presentation describes types of data pipeline architectures. It contains information about AWS services needed to create data pipelines based on Amazon Web Services. Also, users can find different diagrams of implemented pipelines on AWS.
IRJET- Recommendation System based on Graph Database TechniquesIRJET Journal
This document proposes a recommendation system based on graph database techniques. It uses Neo4j to develop a recommendation approach using content-based filtering, collaborative filtering, and hybrid filtering. The system recommends restaurants and meals to customers based on reviews and friend recommendations. It stores data about restaurants, meals, customers and their reviews in a graph database to allow for complex queries and recommendations. The implementation and results of the proposed recommendation system are also discussed.
IRJET- Big Data Processes and Analysis using Hadoop FrameworkIRJET Journal
This document discusses issues with analyzing sub-datasets in a distributed manner using Hadoop, such as imbalanced computational loads and inefficient data scanning. It proposes a new approach called Data-Net that uses metadata about sub-dataset distributions stored in an Elastic-Map structure to optimize storage placement and queries. Experimental results on a 128-node cluster show that Data-Net provides better load balancing and performance for various sub-dataset analysis applications compared to the default Hadoop implementation.
This document is a curriculum vitae for Anuj Gupta that outlines his professional experience and technical skills. It summarizes that he has over 7 years of experience as an IT consultant providing strategic guidance to clients. He has worked as a team leader and senior engineer on various projects for companies like Newgen Software, Infosys, RBS Services, and Airtel. His technical skills include languages like Java, XML, and SQL as well as frameworks like Hibernate, RESTful web services, and Hadoop. He also has experience in data analytics using tools like R, machine learning algorithms, and natural language processing.
Performance evaluation of Map-reduce jar pig hive and spark with machine lear...IJECEIAES
Big data is the biggest challenges as we need huge processing power system and good algorithms to make a decision. We need Hadoop environment with pig hive, machine learning and hadoopecosystem components. The data comes from industries. Many devices around us and sensor, and from social media sites. According to McKinsey There will be a shortage of 15000000 big data professionals by the end of 2020. There are lots of technologies to solve the problem of big data Storage and processing. Such technologies are Apache Hadoop, Apache Spark, Apache Kafka, and many more. Here we analyse the processing speed for the 4GB data on cloudx lab with Hadoop mapreduce with varing mappers and reducers and with pig script and Hive querries and spark environment along with machine learning technology and from the results we can say that machine learning with Hadoop will enhance the processing performance along with with spark, and also we can say that spark is better than Hadoop mapreduce pig and hive, spark with hive and machine learning will be the best performance enhanced compared with pig and hive, Hadoop mapreduce jar.
1) The document discusses the implementation of an SAP system at Delhi Metro Rail Corporation Limited (DMRC) to integrate its various business functions and improve operational efficiency.
2) DMRC required a customized IT system that was fast, integrated, flexible, and modular to help streamline operations, decision making, and resource utilization across departments.
3) After evaluating various options, DMRC implemented SAP R/3, deploying core modules for finance, costing, materials, HR, maintenance, projects, and real estate. The system went live within nine months and provided benefits like real-time project tracking, cost control, and predictive analytics.
Shantanu Gupta is a data scientist with over 5 years of experience in data analysis, cloud computing, and web development. He holds an MS in Computer Engineering from Arizona State University and a BTech in Information Technology. His technical skills include programming languages like Java, Python, and SQL as well as tools like AWS, Hadoop, Spark, and machine learning libraries like TensorFlow and Keras. He has worked on various projects involving pattern recognition, email spam detection, and handwritten digit recognition. Currently, he is a Data Intelligence and Cloud Developer at ASU's Smart City Cloud Innovation Center where he is building prototypes for smart city initiatives utilizing AWS cloud services.
Vivek Adithya Mohankumar has a Master's degree in Information Systems from the University of Texas at Arlington. He has work experience as an Information Developer at SAP where he gathered requirements and helped translate them into user stories. He also has experience analyzing business transactions using Apache Spark and building predictive models with Python. His areas of expertise include data analysis, machine learning, business intelligence, and agile methodologies.
The document discusses using MapReduce for a sequential web access-based recommendation system. It explains how web server logs could be mapped to create a pattern tree showing frequent sequences of accessed web pages. When making recommendations for a user, their access pattern would be compared to patterns in the tree to find matching branches to suggest. MapReduce is well-suited for this because it can efficiently process and modify the large, dynamic tree structure across many machines in a fault-tolerant way.
The document contains a resume for Saketh Vadlamudi seeking an entry level machine learning or data analysis role, highlighting his skills and experience in machine learning algorithms, programming languages, and tools as well as academic and professional projects applying machine learning to problems in various domains like banking, oil prices, sentiment analysis, and credit risk classification. Vadlamudi has a Master's degree in Computer Science from Texas A&M University and is currently working as a Data and Machine Learning Engineer at Reynolds American Inc.
This document summarizes a research paper on using clustering approaches to improve the discovery of semantic web services. It begins by defining semantic web services and semantic similarity measures. It then discusses using clustering to eliminate irrelevant services from a collection before applying semantic algorithms. Specifically, it proposes a clustering probabilistic semantic approach (CPLSA) that filters services based on compatibility with a query before clustering the remaining services into semantically related groups using probabilistic latent semantic analysis (PLSA). The document concludes by discussing applications of approximate semantics and challenges in scaling semantic algorithms.
Hadoop Online Training : kelly technologies is the bestHadoop online Training Institutes in Bangalore. ProvidingHadoop online Training by real time faculty in Bangalore.
This document contains Robin Hesje's resume. It summarizes his 11 years of experience in application development, database development, and systems integration. Currently, he designs application functionality in various SAP systems for a major Canadian railroad, involving requirements gathering, functional specification writing, and testing. The resume lists his technical skills and experience delivering various projects involving SAP transportation management, quoting tools, and other systems.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
Your Skill Boost Masterclass: Strategies for Effective Upskilling
Hadoop training in Bangalore
1. www.kellytechno.com
MapReduce
How Does MapReduce Fit into My Organization and Advanced Analytics?
MapReduce can be used in a variety of ways to bring efficiency into the ways you are processing data
within your organization and drive-down costs significantly over conventional data processing
technologies.
Depending on your specific data analytics needs, you can leverage MapReduce or SQL-MapReduce in
multiple ways and derive deep insights on your data through queries that were previously difficult or
impossible to express.
Check out some of these examples of how companies are using SQL-MapReduce effectively to improve
their ROI and derive deep insights on their entire database:
Fraud Detection – A large online gaming company catches cases of fraud that previous queries
could not detect. And the company reduced its fraud analytics cycle time from one week to 15
minutes, with query response dropping from 90 minutes to 90 seconds.
Graph Analysis – A social media company uses the SQL-MapReduce function nPath for graph
analysis to understand how its users are connected and enhance the networks of its community.
Sharing Behavior – ShareThis uses MapReduce to reduce query times as it analyzes the items
that people share online to understand sharing behavior.
Sessionization – A social network uses the SQL-MapReduce function "sessionize" to break user
data into sessions based on the length of time between activity on the network. With sessionize,
the SQL code dropped from more than 1000 lines to less than 100 and performance improved
dramatically.
Search Behavior – An online media company uses the SQL-MapReduce function nPath to better
understand the paths its users follow after conducting a search to improve search results.
Transformations – Where data transformations previously required multiple complex self joins,
a media company now uses the SQL-MapReduce function nPath to make a single pass of its
data, significantly simplifying the code and improving performance.
Machine Learning – Research show that algorithms that fit the Statistical Query model can be
written in a certain "summation form," which allows them to be easily parallelized on multicore
computers. The researchers adapt Google’s map-reduce paradigm to demonstrate this parallel
speed up technique on a variety of learning algorithms including locally weighted linear
regression (LWLR), k-means, logistic regression (LR), naive Bayes (NB), SVM, ICA, PCA, gaussian
discriminant analysis (GDA), EM, and backpropagation (NN).