Research trends relevant to data warehousing and OLAP include [Cuzzocrea et al.]: Combining the benefits of RDBMS and NoSQL database systems

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Research trends relevant to data warehousing and OLAP include [Cuzzocrea et al.]: Combining the benefits of RDBMS and NoSQL database systems"

Transcription

1 DATA WAREHOUSING RESEARCH TRENDS Research trends relevant to data warehousing and OLAP include [Cuzzocrea et al.]: Data source heterogeneity and incongruence Filtering out uncorrelated data Strongly unstructured nature of data sources High scalability Combining the benefits of RDBMS and NoSQL database systems Query optimization issues in Hadoop-based systems Integrating multidimensional data models and techniques with Hadoop visualisation of big data analytics 1

2 DATA MINING RESEARCH TRENDS Data mining research trends include exploration of the following [Han & Kamber]: Application exploration Scalable and interactive data mining methods Integration of data mining with search engines, database, data warehouse and cloud database systems Mining social and information networks Mining spatiotemporal, moving-objects and cyber-physical systems Mining multimedia, text, and web data Mining biological and biomedical data 2

3 Data mining with software engineering and system engineering Visual and audio data mining Distributed data mining and real-time data stream mining Privacy protection and information security in data mining The above areas for both data warehousing and data mining largely have a computer technology focus. One of our original definitions of a data warehouse was... a collection of technologies aimed at enabling the knowledge worker to make better and faster decisions. Hence, business goals also need to be addressed in considering the use of these technologies. Also, it is increasingly recognised that the complexity of the data and multiple technologies used by a knowledge worker introduces its own problems. 3

4 PRACTICAL LESSONS FROM LARGE-SCALE DATA MINING The importance of domain knowledge. Look and know your data. Many data mining projects fail because of the lack of adequate data: suitable data pre-processing, sampling are crucial. Understand the business goals when developing a mining model. Important metrics in training and deployment of mining models: offline training time, online prediction time, model size or memory footprint. Understand the impact of architecture and scalability issues on algorithm design and implementation. Importance of people in considering the above. Importance of two under-researched areas: visualisation real-time interaction with large datasets. 4

5 BIG DATA ANALYTICS TRENDS AND FUTURE DIRECTIONS Challenges include [Assunção et al.]: Data management Extracting meaningful content quickly out of large volumes of data, especially when it is unstructured. Aggregating and correlating streaming data from multiple sources. Storage enabling easy migration between data centres and cloud providers. Programming models optimized for streaming and/or multidimensional data. Engines combining applications with multiple programming models in a single execution abstraction. Optimizing resource usage and energy consumption during execution of such applications. 5

6 Model building and scoring Techniques utilising the elasticity and scale of cloud systems. Standards and APIs supporting prediction and wider analytics as services. Visualisation and user interaction Efficient techniques supporting real-time visualisation. Cost-effective devices for large-scale visualisation. Other challenges Business models enabling analytics and analytics as a service on the cloud. Supporting replicability of analytics. Incorporating human expertise into the analytics process, particularly in cloud environments. Location and context-aware techniques for collecting, processing, analysing and visualising large-scale mobile and sensor data. 6

7 Reading (Optional) V Gopalkrishnan et al, Big Data, Big Business: Bridging the Gap, Proc. Big Mine 12, August Y Chen et al., Practical Lessons of Data Mining at Yahoo!, Proc. CIKM 09, , J Lin & D Ryaboy, Scaling Big Data Mining Infrastructure: The Twitter Experience, ACM SIGKDD Exploration, 14(2), 6-19, M D. Assunção et al., Big Data computing and clouds: Trends and future directions, J. Parallel and Distributed Computing, 79-80, 3-15,

Search and Data Mining: Techniques. Applications Anya Yarygina Boris Novikov

Search and Data Mining: Techniques. Applications Anya Yarygina Boris Novikov Search and Data Mining: Techniques Applications Anya Yarygina Boris Novikov Introduction Data mining applications Data mining system products and research prototypes Additional themes on data mining Social

More information

COMP9321 Web Application Engineering

COMP9321 Web Application Engineering COMP9321 Web Application Engineering Semester 2, 2015 Dr. Amin Beheshti Service Oriented Computing Group, CSE, UNSW Australia Week 11 (Part II) http://webapps.cse.unsw.edu.au/webcms2/course/index.php?cid=2411

More information

locuz.com Big Data Services

locuz.com Big Data Services locuz.com Big Data Services Big Data At Locuz, we help the enterprise move from being a data-limited to a data-driven one, thereby enabling smarter, faster decisions that result in better business outcome.

More information

Big Data and Analytics: Challenges and Opportunities

Big Data and Analytics: Challenges and Opportunities Big Data and Analytics: Challenges and Opportunities Dr. Amin Beheshti Lecturer and Senior Research Associate University of New South Wales, Australia (Service Oriented Computing Group, CSE) Talk: Sharif

More information

Turning Big Data into Big Insights

Turning Big Data into Big Insights mwd a d v i s o r s Turning Big Data into Big Insights Helena Schwenk A special report prepared for Actuate May 2013 This report is the fourth in a series and focuses principally on explaining what s needed

More information

The basic data mining algorithms introduced may be enhanced in a number of ways.

The basic data mining algorithms introduced may be enhanced in a number of ways. DATA MINING TECHNOLOGIES AND IMPLEMENTATIONS The basic data mining algorithms introduced may be enhanced in a number of ways. Data mining algorithms have traditionally assumed data is memory resident,

More information

Big Data Architectures. Lessons Learned from Industrializing Big Data. Kenan Mujkic, PhD 23 June 2016

Big Data Architectures. Lessons Learned from Industrializing Big Data. Kenan Mujkic, PhD 23 June 2016 Big Data Architectures Lessons Learned from Industrializing Big Data Kenan Mujkic, PhD 23 June 2016 Deloitte Making an impact that matters for clients, for our people, and for society. We serve clients

More information

The Big Data Ecosystem at LinkedIn Roshan Sumbaly, Jay Kreps, and Sam Shah LinkedIn

The Big Data Ecosystem at LinkedIn Roshan Sumbaly, Jay Kreps, and Sam Shah LinkedIn The Big Data Ecosystem at LinkedIn Roshan Sumbaly, Jay Kreps, and Sam Shah LinkedIn Presented by :- Ishank Kumar Aakash Patel Vishnu Dev Yadav CONTENT Abstract Introduction Related work The Ecosystem Ingress

More information

Understanding traffic flow

Understanding traffic flow White Paper A Real-time Data Hub For Smarter City Applications Intelligent Transportation Innovation for Real-time Traffic Flow Analytics with Dynamic Congestion Management 2 Understanding traffic flow

More information

CitusDB Architecture for Real-Time Big Data

CitusDB Architecture for Real-Time Big Data CitusDB Architecture for Real-Time Big Data CitusDB Highlights Empowers real-time Big Data using PostgreSQL Scales out PostgreSQL to support up to hundreds of terabytes of data Fast parallel processing

More information

Data Mining with Big Data e-health Service Using Map Reduce

Data Mining with Big Data e-health Service Using Map Reduce Data Mining with Big Data e-health Service Using Map Reduce Abinaya.K PG Student, Department Of Computer Science and Engineering, Parisutham Institute of Technology and Science, Thanjavur, Tamilnadu, India

More information

Enhance Collaboration and Data Sharing for Faster Decisions and Improved Mission Outcome

Enhance Collaboration and Data Sharing for Faster Decisions and Improved Mission Outcome Enhance Collaboration and Data Sharing for Faster Decisions and Improved Mission Outcome Richard Breakiron Senior Director, Cyber Solutions Rbreakiron@vion.com Office: 571-353-6127 / Cell: 803-443-8002

More information

BIG DATA TRENDS AND TECHNOLOGIES

BIG DATA TRENDS AND TECHNOLOGIES BIG DATA TRENDS AND TECHNOLOGIES THE WORLD OF DATA IS CHANGING Cloud WHAT IS BIG DATA? Big data are datasets that grow so large that they become awkward to work with using onhand database management tools.

More information

A Professional Big Data Master s Program to train Computational Specialists

A Professional Big Data Master s Program to train Computational Specialists A Professional Big Data Master s Program to train Computational Specialists Anoop Sarkar, Fred Popowich, Alexandra Fedorova! School of Computing Science! Education for Employable Graduates: Critical Questions

More information

Using Open Source NoSQL technologies in Designing Systems for Delivering Electric Vehicle Data Analytics.

Using Open Source NoSQL technologies in Designing Systems for Delivering Electric Vehicle Data Analytics. Paper ID #9603 Using Open Source NoSQL technologies in Designing Systems for Delivering Electric Vehicle Data Analytics. Mr. Vamshi Krishna Bolly, Purdue University Vamshi K Bolly is a Master of Science

More information

Big Data Architecture

Big Data Architecture Big Architecture Guido Schmutz BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH Guido Schmutz Working for Trivadis for more than

More information

Improving Data Processing Speed in Big Data Analytics Using. HDFS Method

Improving Data Processing Speed in Big Data Analytics Using. HDFS Method Improving Data Processing Speed in Big Data Analytics Using HDFS Method M.R.Sundarakumar Assistant Professor, Department Of Computer Science and Engineering, R.V College of Engineering, Bangalore, India

More information

Integrating a Big Data Platform into Government:

Integrating a Big Data Platform into Government: Integrating a Big Data Platform into Government: Drive Better Decisions for Policy and Program Outcomes John Haddad, Senior Director Product Marketing, Informatica Digital Government Institute s Government

More information

Pulsar Realtime Analytics At Scale. Tony Ng April 14, 2015

Pulsar Realtime Analytics At Scale. Tony Ng April 14, 2015 Pulsar Realtime Analytics At Scale Tony Ng April 14, 2015 Big Data Trends Bigger data volumes More data sources DBs, logs, behavioral & business event streams, sensors Faster analysis Next day to hours

More information

The Impact of SAP S/4HANA on Exisiting Enterprise Architecture from SAP. Erich Schneider & Martin Mysyk SAP Session ID#5749

The Impact of SAP S/4HANA on Exisiting Enterprise Architecture from SAP. Erich Schneider & Martin Mysyk SAP Session ID#5749 The Impact of SAP S/4HANA on Exisiting Enterprise Architecture from SAP Erich Schneider & Martin Mysyk SAP Session ID#5749 BUSINESS, IT AND THE DIGITAL ECONOMY Hyper Connectivity Super Computing Smart

More information

Topics in basic DBMS course

Topics in basic DBMS course Topics in basic DBMS course Database design Transaction processing Relational query languages (SQL), calculus, and algebra DBMS APIs Database tuning (physical database design) Basic query processing (ch

More information

Navigating the Big Data infrastructure layer Helena Schwenk

Navigating the Big Data infrastructure layer Helena Schwenk mwd a d v i s o r s Navigating the Big Data infrastructure layer Helena Schwenk A special report prepared for Actuate May 2013 This report is the second in a series of four and focuses principally on explaining

More information

The Future of Business Analytics is Now! 2013 IBM Corporation

The Future of Business Analytics is Now! 2013 IBM Corporation The Future of Business Analytics is Now! 1 The pressures on organizations are at a point where analytics has evolved from a business initiative to a BUSINESS IMPERATIVE More organization are using analytics

More information

High-Performance Business Analytics: SAS and IBM Netezza Data Warehouse Appliances

High-Performance Business Analytics: SAS and IBM Netezza Data Warehouse Appliances High-Performance Business Analytics: SAS and IBM Netezza Data Warehouse Appliances Highlights IBM Netezza and SAS together provide appliances and analytic software solutions that help organizations improve

More information

Ashish R. Jagdale, Kavita V. Sonawane, Shamsuddin S. Khan

Ashish R. Jagdale, Kavita V. Sonawane, Shamsuddin S. Khan International Journal of Scientific & Engineering Research, Volume 5, Issue 7, July-2014 1156 Data Mining and Data Pre-processing for Big Data Ashish R. Jagdale, Kavita V. Sonawane, Shamsuddin S. Khan

More information

Keywords Big Data; OODBMS; RDBMS; hadoop; EDM; learning analytics, data abundance.

Keywords Big Data; OODBMS; RDBMS; hadoop; EDM; learning analytics, data abundance. Volume 4, Issue 11, November 2014 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Analytics

More information

5 Keys to Unlocking the Big Data Analytics Puzzle. Anurag Tandon Director, Product Marketing March 26, 2014

5 Keys to Unlocking the Big Data Analytics Puzzle. Anurag Tandon Director, Product Marketing March 26, 2014 5 Keys to Unlocking the Big Data Analytics Puzzle Anurag Tandon Director, Product Marketing March 26, 2014 1 A Little About Us A global footprint. A proven innovator. A leader in enterprise analytics for

More information

The 4 Pillars of Technosoft s Big Data Practice

The 4 Pillars of Technosoft s Big Data Practice beyond possible Big Use End-user applications Big Analytics Visualisation tools Big Analytical tools Big management systems The 4 Pillars of Technosoft s Big Practice Overview Businesses have long managed

More information

Big Data: Opportunities & Challenges, Myths & Truths 資 料 來 源 : 台 大 廖 世 偉 教 授 課 程 資 料

Big Data: Opportunities & Challenges, Myths & Truths 資 料 來 源 : 台 大 廖 世 偉 教 授 課 程 資 料 Big Data: Opportunities & Challenges, Myths & Truths 資 料 來 源 : 台 大 廖 世 偉 教 授 課 程 資 料 美 國 13 歲 學 生 用 Big Data 找 出 霸 淩 熱 點 Puri 架 設 網 站 Bullyvention, 藉 由 分 析 Twitter 上 找 出 提 到 跟 霸 凌 相 關 的 詞, 搭 配 地 理 位 置

More information

Where is... How do I get to...

Where is... How do I get to... Big Data, Fast Data, Spatial Data Making Sense of Location Data in a Smart City Hans Viehmann Product Manager EMEA ORACLE Corporation August 19, 2015 Copyright 2014, Oracle and/or its affiliates. All rights

More information

Managing Big Data with Hadoop & Vertica. A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database

Managing Big Data with Hadoop & Vertica. A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database Managing Big Data with Hadoop & Vertica A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database Copyright Vertica Systems, Inc. October 2009 Cloudera and Vertica

More information

Sanjeev Kumar. contribute

Sanjeev Kumar. contribute RESEARCH ISSUES IN DATAA MINING Sanjeev Kumar I.A.S.R.I., Library Avenue, Pusa, New Delhi-110012 sanjeevk@iasri.res.in 1. Introduction The field of data mining and knowledgee discovery is emerging as a

More information

SAP and Hortonworks Reference Architecture

SAP and Hortonworks Reference Architecture SAP and Hortonworks Reference Architecture Hortonworks. We Do Hadoop. June Page 1 2014 Hortonworks Inc. 2011 2014. All Rights Reserved A Modern Data Architecture With SAP DATA SYSTEMS APPLICATIO NS Statistical

More information

Architecting for Big Data Analytics and Beyond: A New Framework for Business Intelligence and Data Warehousing

Architecting for Big Data Analytics and Beyond: A New Framework for Business Intelligence and Data Warehousing Architecting for Big Data Analytics and Beyond: A New Framework for Business Intelligence and Data Warehousing Wayne W. Eckerson Director of Research, TechTarget Founder, BI Leadership Forum Business Analytics

More information

New Features in Oracle Application Express 4.1. Oracle Application Express Websheets. Oracle Database Cloud Service

New Features in Oracle Application Express 4.1. Oracle Application Express Websheets. Oracle Database Cloud Service Date and Time- Europe/Middle East/Africa Tuesday June 12, 2012 09:00 13:00 BST 10:00 14:00 CEST 12:00 16:00 GST Corresponding UTC (GMT) 08:00:00 Agenda Time Track and Keynote/Session Title 9:00 AM Keynote

More information

Introduction to Data Mining

Introduction to Data Mining Introduction to Data Mining Jay Urbain Credits: Nazli Goharian & David Grossman @ IIT Outline Introduction Data Pre-processing Data Mining Algorithms Naïve Bayes Decision Tree Neural Network Association

More information

BIG DATA Alignment of Supply & Demand Nuria de Lama Representative of Atos Research &

BIG DATA Alignment of Supply & Demand Nuria de Lama Representative of Atos Research & BIG DATA Alignment of Supply & Demand Nuria de Lama Representative of Atos Research & Innovation 04-08-2011 to the EC 8 th February, Luxembourg Your Atos business Research technologists. and Innovation

More information

Real-time distributed Complex Event Processing for Big Data scenarios

Real-time distributed Complex Event Processing for Big Data scenarios Institute of Parallel and Distributed Systems () Universitätsstraße 38 D-70569 Stuttgart Real-time distributed Complex Event Processing for Big Data scenarios Ruben Mayer Motivation: New Applications in

More information

A Novel Cloud Based Elastic Framework for Big Data Preprocessing

A Novel Cloud Based Elastic Framework for Big Data Preprocessing School of Systems Engineering A Novel Cloud Based Elastic Framework for Big Data Preprocessing Omer Dawelbeit and Rachel McCrindle October 21, 2014 University of Reading 2008 www.reading.ac.uk Overview

More information

III Big Data Technologies

III Big Data Technologies III Big Data Technologies Today, new technologies make it possible to realize value from Big Data. Big data technologies can replace highly customized, expensive legacy systems with a standard solution

More information

A Proposed Framework to Use Cloud Computing Power in Business Intelligence

A Proposed Framework to Use Cloud Computing Power in Business Intelligence International Academic Institute for Science and Technology International Academic Journal of Science and Engineering Vol. 3, No. 7, 2016, pp. 10-14. ISSN 2454-3896 International Academic Journal of Science

More information

(b) How data mining is different from knowledge discovery in databases (KDD)? Explain.

(b) How data mining is different from knowledge discovery in databases (KDD)? Explain. Q2. (a) List and describe the five primitives for specifying a data mining task. Data Mining Task Primitives (b) How data mining is different from knowledge discovery in databases (KDD)? Explain. IETE

More information

Complex, true real-time analytics on massive, changing datasets.

Complex, true real-time analytics on massive, changing datasets. Complex, true real-time analytics on massive, changing datasets. A NoSQL, all in-memory enabling platform technology from: Better Questions Come Before Better Answers FinchDB is a NoSQL, all in-memory

More information

UNIVERSITY OF INFINITE AMBITIONS. MASTER OF SCIENCE COMPUTER SCIENCE DATA SCIENCE AND SMART SERVICES

UNIVERSITY OF INFINITE AMBITIONS. MASTER OF SCIENCE COMPUTER SCIENCE DATA SCIENCE AND SMART SERVICES UNIVERSITY OF INFINITE AMBITIONS. MASTER OF SCIENCE COMPUTER SCIENCE DATA SCIENCE AND SMART SERVICES MASTER S PROGRAMME COMPUTER SCIENCE - DATA SCIENCE AND SMART SERVICES (DS3) This is a specialization

More information

A TECHNICAL WHITE PAPER ATTUNITY VISIBILITY

A TECHNICAL WHITE PAPER ATTUNITY VISIBILITY A TECHNICAL WHITE PAPER ATTUNITY VISIBILITY Analytics for Enterprise Data Warehouse Management and Optimization Executive Summary Successful enterprise data management is an important initiative for growing

More information

Business Intelligence meets Big Data: An Overview on Security and Privacy

Business Intelligence meets Big Data: An Overview on Security and Privacy Business Intelligence meets Big Data: An Overview on Security and Privacy Claudio A. Ardagna Ernesto Damiani Dipartimento di Informatica - Università degli Studi di Milano NSF Workshop on Big Data Security

More information

BIG DATA: FIVE TACTICS TO MODERNIZE YOUR DATA WAREHOUSE

BIG DATA: FIVE TACTICS TO MODERNIZE YOUR DATA WAREHOUSE BIG DATA: FIVE TACTICS TO MODERNIZE YOUR DATA WAREHOUSE Current technology for Big Data allows organizations to dramatically improve return on investment (ROI) from their existing data warehouse environment.

More information

1 st Symposium on Colossal Data and Networking (CDAN-2016) March 18-19, 2016 Medicaps Group of Institutions, Indore, India

1 st Symposium on Colossal Data and Networking (CDAN-2016) March 18-19, 2016 Medicaps Group of Institutions, Indore, India 1 st Symposium on Colossal Data and Networking (CDAN-2016) March 18-19, 2016 Medicaps Group of Institutions, Indore, India Call for Papers Colossal Data Analysis and Networking has emerged as a de facto

More information

Alejandro Vaisman Esteban Zimanyi. Data. Warehouse. Systems. Design and Implementation. ^ Springer

Alejandro Vaisman Esteban Zimanyi. Data. Warehouse. Systems. Design and Implementation. ^ Springer Alejandro Vaisman Esteban Zimanyi Data Warehouse Systems Design and Implementation ^ Springer Contents Part I Fundamental Concepts 1 Introduction 3 1.1 A Historical Overview of Data Warehousing 4 1.2 Spatial

More information

Towards Privacy aware Big Data analytics

Towards Privacy aware Big Data analytics Towards Privacy aware Big Data analytics Pietro Colombo, Barbara Carminati, and Elena Ferrari Department of Theoretical and Applied Sciences, University of Insubria, Via Mazzini 5, 21100 - Varese, Italy

More information

BIG. Big Data Analysis John Domingue (STI International and The Open University) Big Data Public Private Forum

BIG. Big Data Analysis John Domingue (STI International and The Open University) Big Data Public Private Forum Big Data Analysis John Domingue (STI International and The Open University) Project co-funded by the European Commission within the 7th Framework Program (Grant Agreement No. 257943) 1 The Data landscape

More information

BIG DATA IN BUSINESS ENVIRONMENT

BIG DATA IN BUSINESS ENVIRONMENT Scientific Bulletin Economic Sciences, Volume 14/ Issue 1 BIG DATA IN BUSINESS ENVIRONMENT Logica BANICA 1, Alina HAGIU 2 1 Faculty of Economics, University of Pitesti, Romania olga.banica@upit.ro 2 Faculty

More information

BIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON

BIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON BIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON Overview * Introduction * Multiple faces of Big Data * Challenges of Big Data * Cloud Computing

More information

Developing Scalable Smart Grid Infrastructure to Enable Secure Transmission System Control

Developing Scalable Smart Grid Infrastructure to Enable Secure Transmission System Control Developing Scalable Smart Grid Infrastructure to Enable Secure Transmission System Control EP/K006487/1 UK PI: Prof Gareth Taylor (BU) China PI: Prof Yong-Hua Song (THU) Consortium UK Members: Brunel University

More information

COURSE NAME: DATA WAREHOUSING & DATA MINING

COURSE NAME: DATA WAREHOUSING & DATA MINING COURSE NAME: DATA WAREHOUSING & DATA MINING LECTURE 5 TOPICS TO BE COVERED: OLTP vs OLAP ROLAP vs MOLAP types of OLAP servers, OLAP SERVER An OLAP Server is a high capacity, multi user data manipulation

More information

ON-LINE VIDEO ANALYTICS EMBRACING BIG DATA

ON-LINE VIDEO ANALYTICS EMBRACING BIG DATA ON-LINE VIDEO ANALYTICS EMBRACING BIG DATA David Vanderfeesten, Bell Labs Belgium ANNO 2012 YOUR DATA IS MONEY BIG MONEY! Your click stream, your activity stream, your electricity consumption, your call

More information

Building Confidence in Big Data Innovations in Information Integration & Governance for Big Data

Building Confidence in Big Data Innovations in Information Integration & Governance for Big Data Building Confidence in Big Data Innovations in Information Integration & Governance for Big Data IBM Software Group Important Disclaimer THE INFORMATION CONTAINED IN THIS PRESENTATION IS PROVIDED FOR INFORMATIONAL

More information

Next-Generation Cloud Analytics with Amazon Redshift

Next-Generation Cloud Analytics with Amazon Redshift Next-Generation Cloud Analytics with Amazon Redshift What s inside Introduction Why Amazon Redshift is Great for Analytics Cloud Data Warehousing Strategies for Relational Databases Analyzing Fast, Transactional

More information

TRAINING PROGRAM ON BIGDATA/HADOOP

TRAINING PROGRAM ON BIGDATA/HADOOP Course: Training on Bigdata/Hadoop with Hands-on Course Duration / Dates / Time: 4 Days / 24th - 27th June 2015 / 9:30-17:30 Hrs Venue: Eagle Photonics Pvt Ltd First Floor, Plot No 31, Sector 19C, Vashi,

More information

BIG DATA TECHNOLOGY. Hadoop Ecosystem

BIG DATA TECHNOLOGY. Hadoop Ecosystem BIG DATA TECHNOLOGY Hadoop Ecosystem Agenda Background What is Big Data Solution Objective Introduction to Hadoop Hadoop Ecosystem Hybrid EDW Model Predictive Analysis using Hadoop Conclusion What is Big

More information

High Performance Data Management Use of Standards in Commercial Product Development

High Performance Data Management Use of Standards in Commercial Product Development v2 High Performance Data Management Use of Standards in Commercial Product Development Jay Hollingsworth: Director Oil & Gas Business Unit Standards Leadership Council Forum 28 June 2012 1 The following

More information

Associate Professor, Department of CSE, Shri Vishnu Engineering College for Women, Andhra Pradesh, India 2

Associate Professor, Department of CSE, Shri Vishnu Engineering College for Women, Andhra Pradesh, India 2 Volume 6, Issue 3, March 2016 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Special Issue

More information

Reference Architecture, Requirements, Gaps, Roles

Reference Architecture, Requirements, Gaps, Roles Reference Architecture, Requirements, Gaps, Roles The contents of this document are an excerpt from the brainstorming document M0014. The purpose is to show how a detailed Big Data Reference Architecture

More information

Big Data and Healthcare Payers WHITE PAPER

Big Data and Healthcare Payers WHITE PAPER Knowledgent White Paper Series Big Data and Healthcare Payers WHITE PAPER Summary With the implementation of the Affordable Care Act, the transition to a more member-centric relationship model, and other

More information

Course 803401 DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

Course 803401 DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Oman College of Management and Technology Course 803401 DSS Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization CS/MIS Department Information Sharing

More information

End to End Solution to Accelerate Data Warehouse Optimization. Franco Flore Alliance Sales Director - APJ

End to End Solution to Accelerate Data Warehouse Optimization. Franco Flore Alliance Sales Director - APJ End to End Solution to Accelerate Data Warehouse Optimization Franco Flore Alliance Sales Director - APJ Big Data Is Driving Key Business Initiatives Increase profitability, innovation, customer satisfaction,

More information

Information Management course

Information Management course Università degli Studi di Milano Master Degree in Computer Science Information Management course Teacher: Alberto Ceselli Lecture 01 : 06/10/2015 Practical informations: Teacher: Alberto Ceselli (alberto.ceselli@unimi.it)

More information

Hadoop. MPDL-Frühstück 9. Dezember 2013 MPDL INTERN

Hadoop. MPDL-Frühstück 9. Dezember 2013 MPDL INTERN Hadoop MPDL-Frühstück 9. Dezember 2013 MPDL INTERN Understanding Hadoop Understanding Hadoop What's Hadoop about? Apache Hadoop project (started 2008) downloadable open-source software library (current

More information

Big Data Analytics. Lucas Rego Drumond

Big Data Analytics. Lucas Rego Drumond Big Data Analytics Lucas Rego Drumond Information Systems and Machine Learning Lab (ISMLL) Institute of Computer Science University of Hildesheim, Germany Big Data Analytics Big Data Analytics 1 / 36 Outline

More information

New Eco-Systems in the software and service domain in the Cloud area

New Eco-Systems in the software and service domain in the Cloud area New Eco-Systems in the software and service domain in the Cloud area What s in it for enterprises Dr. Harald Schöning, Software AG Member of the NESSI Board Outline September 28, 2012 2 Pre-Cloud Situation

More information

Managing Cloud Server with Big Data for Small, Medium Enterprises: Issues and Challenges

Managing Cloud Server with Big Data for Small, Medium Enterprises: Issues and Challenges Managing Cloud Server with Big Data for Small, Medium Enterprises: Issues and Challenges Prerita Gupta Research Scholar, DAV College, Chandigarh Dr. Harmunish Taneja Department of Computer Science and

More information

تعریف Big Data. موضوعات مطرح در حوزه : Big Data. 1. Big Data Foundations

تعریف Big Data. موضوعات مطرح در حوزه : Big Data. 1. Big Data Foundations بو نام خدا گسارش مطالعو برخی مفاىیم زىره رضایی کینجی تعریف Big Data Big Data کلکغیو ی اص هجووػ داد ای بغیاس بضسگ و پیچیذ اعت ک ایي اهش هوجب هی شود پشداصػ آى با اعتفاد اص عیغتن ای هذیشیت پایگا داد و یا

More information

Big Data Mining: Challenges and Opportunities to Forecast Future Scenario

Big Data Mining: Challenges and Opportunities to Forecast Future Scenario Big Data Mining: Challenges and Opportunities to Forecast Future Scenario Poonam G. Sawant, Dr. B.L.Desai Assist. Professor, Dept. of MCA, SIMCA, Savitribai Phule Pune University, Pune, Maharashtra, India

More information

Chapter 7. Using Hadoop Cluster and MapReduce

Chapter 7. Using Hadoop Cluster and MapReduce Chapter 7 Using Hadoop Cluster and MapReduce Modeling and Prototyping of RMS for QoS Oriented Grid Page 152 7. Using Hadoop Cluster and MapReduce for Big Data Problems The size of the databases used in

More information

Complexity and Scalability in Semantic Graph Analysis Semantic Days 2013

Complexity and Scalability in Semantic Graph Analysis Semantic Days 2013 Complexity and Scalability in Semantic Graph Analysis Semantic Days 2013 James Maltby, Ph.D 1 Outline of Presentation Semantic Graph Analytics Database Architectures In-memory Semantic Database Formulation

More information

BIG DATA ANALYTICS REFERENCE ARCHITECTURES AND CASE STUDIES

BIG DATA ANALYTICS REFERENCE ARCHITECTURES AND CASE STUDIES BIG DATA ANALYTICS REFERENCE ARCHITECTURES AND CASE STUDIES Relational vs. Non-Relational Architecture Relational Non-Relational Rational Predictable Traditional Agile Flexible Modern 2 Agenda Big Data

More information

Big Data on the Open Cloud

Big Data on the Open Cloud Big Data on the Open Cloud Rackspace Private Cloud, Powered by OpenStack, Helps Reduce Costs and Improve Operational Efficiency Written by Niki Acosta, Cloud Evangelist, Rackspace Big Data on the Open

More information

Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers

Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers 60 Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative

More information

Hadoop Evolution In Organizations. Mark Vervuurt Cluster Data Science & Analytics

Hadoop Evolution In Organizations. Mark Vervuurt Cluster Data Science & Analytics In Organizations Mark Vervuurt Cluster Data Science & Analytics AGENDA 1. Yellow Elephant 2. Data Ingestion & Complex Event Processing 3. SQL on Hadoop 4. NoSQL 5. InMemory 6. Data Science & Machine Learning

More information

Oracle Big Data Handbook

Oracle Big Data Handbook ORACLG Oracle Press Oracle Big Data Handbook Tom Plunkett Brian Macdonald Bruce Nelson Helen Sun Khader Mohiuddin Debra L. Harding David Segleau Gokula Mishra Mark F. Hornick Robert Stackowiak Keith Laker

More information

Indian Journal of Science The International Journal for Science ISSN 2319 7730 EISSN 2319 7749 2016 Discovery Publication. All Rights Reserved

Indian Journal of Science The International Journal for Science ISSN 2319 7730 EISSN 2319 7749 2016 Discovery Publication. All Rights Reserved Indian Journal of Science The International Journal for Science ISSN 2319 7730 EISSN 2319 7749 2016 Discovery Publication. All Rights Reserved Perspective Big Data Framework for Healthcare using Hadoop

More information

Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

More information

Data Refinery with Big Data Aspects

Data Refinery with Big Data Aspects International Journal of Information and Computation Technology. ISSN 0974-2239 Volume 3, Number 7 (2013), pp. 655-662 International Research Publications House http://www. irphouse.com /ijict.htm Data

More information

How to Leverage Big Data in the Cloud to Gain Competitive Advantage

How to Leverage Big Data in the Cloud to Gain Competitive Advantage How to Leverage Big Data in the Cloud to Gain Competitive Advantage James Kobielus, IBM Big Data Evangelist Editor-in-Chief, IBM Data Magazine Senior Program Director, Product Marketing, Big Data Analytics

More information

Testing Big data is one of the biggest

Testing Big data is one of the biggest Infosys Labs Briefings VOL 11 NO 1 2013 Big Data: Testing Approach to Overcome Quality Challenges By Mahesh Gudipati, Shanthi Rao, Naju D. Mohan and Naveen Kumar Gajja Validate data quality by employing

More information

European Archival Records and Knowledge Preservation Database Archiving in the E-ARK Project

European Archival Records and Knowledge Preservation Database Archiving in the E-ARK Project European Archival Records and Knowledge Preservation Database Archiving in the E-ARK Project Janet Delve, University of Portsmouth Kuldar Aas, National Archives of Estonia Rainer Schmidt, Austrian Institute

More information

Managing Data in Motion

Managing Data in Motion Managing Data in Motion Data Integration Best Practice Techniques and Technologies April Reeve ELSEVIER AMSTERDAM BOSTON HEIDELBERG LONDON NEW YORK OXFORD PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY

More information

Framework and key technologies for big data based on manufacturing Shan Ren 1, a, Xin Zhao 2, b

Framework and key technologies for big data based on manufacturing Shan Ren 1, a, Xin Zhao 2, b International Conference on Materials Engineering and Information Technology Applications (MEITA 2015) Framework and key technologies for big data based on manufacturing Shan Ren 1, a, Xin Zhao 2, b 1

More information

Big Data Analytics. Copyright 2011 EMC Corporation. All rights reserved.

Big Data Analytics. Copyright 2011 EMC Corporation. All rights reserved. Big Data Analytics 1 Priority Discussion Topics What are the most compelling business drivers behind big data analytics? Do you have or expect to have data scientists on your staff, and what will be their

More information

White Paper. How Streaming Data Analytics Enables Real-Time Decisions

White Paper. How Streaming Data Analytics Enables Real-Time Decisions White Paper How Streaming Data Analytics Enables Real-Time Decisions Contents Introduction... 1 What Is Streaming Analytics?... 1 How Does SAS Event Stream Processing Work?... 2 Overview...2 Event Stream

More information

Module 3: Understanding Analysis Services Architecture

Module 3: Understanding Analysis Services Architecture Overview Module 3: Understanding Architecture Microsoft Data Warehousing Overview Components Metadata Repository Cube Options Architecture Office 2000 OLAP Components Microsoft Data Warehousing Overview

More information

Big Data Components for Business Process Optimization

Big Data Components for Business Process Optimization 72 Big Data Components for Business Process Optimization Mircea Răducu TRIFU, Mihaela-Laura IVAN Bucharest University of Economic Studies, Bucharest, Romania trifumircearadu@yahoo.com, ivanmihaela88@gmail.com

More information

Optimizing the Hybrid Cloud

Optimizing the Hybrid Cloud Judith Hurwitz President and CEO Marcia Kaufman COO and Principal Analyst Sponsored by IBM Introduction Hybrid cloud is fast becoming a reality for enterprises that want speed, predictability and flexibility

More information

Hortonworks & SAS. Analytics everywhere. Page 1. Hortonworks Inc. 2011 2014. All Rights Reserved

Hortonworks & SAS. Analytics everywhere. Page 1. Hortonworks Inc. 2011 2014. All Rights Reserved Hortonworks & SAS Analytics everywhere. Page 1 A change in focus. A shift in Advertising From mass branding A shift in Financial Services From Educated Investing A shift in Healthcare From mass treatment

More information

International Journal of Scientific & Engineering Research, Volume 5, Issue 4, April-2014 442 ISSN 2229-5518

International Journal of Scientific & Engineering Research, Volume 5, Issue 4, April-2014 442 ISSN 2229-5518 International Journal of Scientific & Engineering Research, Volume 5, Issue 4, April-2014 442 Over viewing issues of data mining with highlights of data warehousing Rushabh H. Baldaniya, Prof H.J.Baldaniya,

More information

Architecting Your Company. Ann Winblad Co-Founder and Managing Director

Architecting Your Company. Ann Winblad Co-Founder and Managing Director Architecting Your Company Ann Winblad Co-Founder and Managing Director 1990 Embedded Systems Intel A History of Defining Software Innovation 1991 BI/ OLAP Oracle 1995 App Server Sun Est. 1989 1996 Behavioral

More information

Life Insurance & Big Data Analytics: Enterprise Architecture

Life Insurance & Big Data Analytics: Enterprise Architecture Life Insurance & Big Data Analytics: Enterprise Architecture Author: Sudhir Patavardhan Vice President Engineering Feb 2013 Saxon Global Inc. 1320 Greenway Drive, Irving, TX 75038 Contents Contents...1

More information

Big Data and Analytics (Fall 2015)

Big Data and Analytics (Fall 2015) Big Data and Analytics (Fall 2015) Core/Elective: MS CS Elective MS SPM Elective Instructor: Dr. Tariq MAHMOOD Credit Hours: 3 Pre-requisite: All Core CS Courses (Knowledge of Data Mining is a Plus) Every

More information

CA Technologies Big Data Infrastructure Management Unified Management and Visibility of Big Data

CA Technologies Big Data Infrastructure Management Unified Management and Visibility of Big Data Research Report CA Technologies Big Data Infrastructure Management Executive Summary CA Technologies recently exhibited new technology innovations, marking its entry into the Big Data marketplace with

More information