The big data revolution

Size: px
Start display at page:

Download "The big data revolution"

Transcription

1 The big data revolution Friso van Vollenhoven (Xebia) Enterprise NoSQL Recently, there has been a lot of buzz about the NoSQL movement, a collection of related technologies mostly concerned with storing and processing large amounts of data. Although these technologies initially emerged from large web companies and social networking companies that have to deal with huge amounts of data on a daily basis, they are also becoming more relevant and interesting for enterprises. There are essentially three reasons for this: The volume of data that organizations gather has grown explosively in recent years; When dealing with large data volumes, several NoSQL technologies can be more cost effective than existing proprietary solutions; Some NoSQL technologies are better suited for large-scale data mining and business intelligence than the traditional relational databases that are widely used today. In order to understand the advantages of NoSQL, we need to examine what these technologies do and how they solve problems differently than the traditional data storage and processing solutions. Traditionally, database servers are large machines with lots of memory and processing power. If data volumes get too large for the machines, then the solution is simply to add even more memory and processing power to cope with the increased load. But this scale-up approach has limits; a machine cannot be scaled up indefinitely. One solution to this problem is to scale out instead of up. This means adding another database server and splitting the database into two parts. Scaling out, however, poses two new problems. First, relational databases were not built with scaling out in mind, and distributing database transactions over more than one machine has performance implications that are usually solved by using very fast, specialized and expensive network hardware. Secondly, scaling out with proprietary software is expensive. Each additional machine adds additional licensing costs, which can be substantial. What the web companies needed was a solution that can scale out to any number of machines with normal, inexpensive hardware and low additional licensing costs. A solution found by many was to abandon the relational database model, to use only standard commodity hardware and to use only open source software, which has no licensing costs. The software that emerged from this strategy provides an affordable way to deal with extremely large datasets. 1

2 initital hardware purchase number of cluster machines Commodity servers High end hardware With proprietary software, scaling out is very expensive. Besides the cost of the hardware itself, each additional piece of hardware also incurs additional software license fees. Moreover, scaling out may simply not be an option for many proprietary solutions. In contrast, with open source software and scaling out, the only variables are hardware purchase, rack space and power consumption. The ability to work with large data volumes using NoSQL technologies not only solves an important technical problem, but also creates many new opportunities. Having the power to process and analyze all the data an organization owns in a reasonable amount of time creates an exciting possibility: the ability to extract information and conclusions that were not available previously due to technical limitations. For example, ten years ago it would have been unthinkable that a web search company would be able to accurately predict flu epidemics. Today, Google is capable of doing just that, based on data about search terms and geographical distribution. Similarly, organizations can now use this technology to gain new insights from their data, such as customer behavior analytics, risk modeling, fraud detection or fine-grained marketing information. Two techniques have traditionally been used when dealing with data volumes too large for a single machine: archiving and sampling. Archiving is the practice of retaining only the most recent data for live querying; older data is pushed to off-line storage where it cannot be accessed directly. Sampling is the practice of analyzing data by looking at only a fraction of all data points in order to obtain a much smaller, hopefully representative set on which a conclusion is then based. These solutions have become obsolete. Today, it has become technically possible to analyze every single transaction, customer interaction, fraud case 2

3 and mouse click on a website that occurred during the past several years, and then base conclusions on all of that data, instead of just a sample. For example, organizations can now think about building customer behavioral models that predict when customers are about to move to a competitor, and then take preventive action. This is possible even if there are millions of customers across the globe. Such possibilities make NoSQL and big data analytics relevant for enterprise, and not just a technological solution to a problem that is only relevant for Google or Facebook. Case study: Hadoop and HBase at RIPE NCC Processing hundreds of millions of records per day The RIPE NCC is one of five Regional Internet Registries (RIRs) providing Internet resource allocations, registration services and coordination activities that support the operation of the Internet globally. They are responsible for allocating ranges of IP addresses to organizations. Another primary mission of RIPE NCC is to provide high quality, near real-time information about the operation of the internet, such as active latency and routing measurements. These measurements produce hundreds of millions of data points per day, resulting in large volumes of data that must be stored and indexed continuously. RIPE NCC must be able to deal with such volumes of data and convert the data stream into valuable information in real time. Together with Xebia, RIPE NCC realized a system capable of handling millions records per day and achieving sustained throughputs of more than 10,000 records per second from multiple data sources across the globe using only open source software, commodity server hardware and network equipment. New data sources can be added at any time. Moreover, storage and processing capacity can be easily scaled out when required, even without downtime. The solution deals with network measurement data that is collected from sources at data centers across the world and sent to a storage network at RIPE NCC s Amsterdam based data center. From there, all data is moved onto a Hadoop cluster, where a series of Hadoop jobs perform further processing, which is primarily a extract-transform-load (ETL) to push the data into a database that can be used for querying from a web application. The system at RIPE NCC deals with data collected from 15 measurement points around the world. Every eight hours it processes a batch of 160 million updates in 3.5 hours. In addition, every five minutes thousands of additional updates come in. On average around 4,000 updates per second are processed around the clock with peaks of 12,000 updates/second. In total 25TB of source data are indexed, and this amount is growing rapidly. 3

4 RIPE NCC deals with internet measurement data, and internet traffic roughly doubles every year, so scalability is a very important factor for this setup. Initially, RIPE NCC deployed a system backed by a relational database to analyze and store the measurement data. This system was only capable of holding three months of history available for querying and searching. All older data had to be archived and was not directly accessible. Full data analysis was therefore not an option. By adapting big data-ready 4

5 technology, RIPE NCC is now able to use the full potential of the data sets it owns. Not only is it possible to query and search all ten years of historical data, but ad hoc analysis of the full data set has also become a realistic option. When the problem of high volume ETL workloads involving vast amounts of source data is addressed, high-end computing hardware is traditionally the first solution that comes to mind. We often assume that it takes specialized networking and storage equipment and high-end databases to deal with thousands of records each second. Today, however, this assumption is not always correct. By using the open source technologies Hadoop and HBase, businesses can harness the power of the MapReduce parallel processing algorithm, which was originally implemented by Google to build their enormous search indexes. Whereas traditional batch processing systems depend on very fast machines to sequentially process large amounts of data in acceptable time, Hadoop MapReduce is an entirely different approach that splits data into smaller pieces and processes all pieces in parallel. This parallelism is key to its success. This can lead to significantly improved processing times even when using standard server hardware, since each individual piece does not need to be processed at lightning speed as long as all the pieces are being done at the same time. This is achieved by using clusters of machines running Hadoop. Hadoop is designed to run on any number of commodity server machines in parallel, ranging from a few machines to hundreds or even thousands. Additional machines can easily be added while the cluster is running, and Hadoop will immediately start using the additional capacity as it becomes available. As a result, capacity can be expanded simply by adding machines. This scale-out approach makes it realistic for IT to accommodate the demand for expansion as it arises. In a traditional scale-up scenario, capacity is usually expanded by replacing a very big machine with an even bigger one, which makes the existing solution unusable. Hadoop is open source software with a significant installed base and many corporate users who run the software in production and depend on it for daily operation. Setups ranging from five to five hundred machines are powering BI solutions for the banking and insurance sector, online retailers and government agencies. Besides the Hadoop open source community, professional support and user and administration training are available from several providers. Moreover, because the software is open source, you are never locked into a single vendor or supplier for support or licensing. 5

6 Conclusion Besides solving a technical problem that relational databases are often unable to tackle, NoSQL technology especially Apache Hadoop for data crunching is providing new opportunities. Big data business intelligence has emerged as a new field. Traditional business intelligence is often database-driven. This limits the investigation options for the data that is imported into existing databases or data warehouses. However, in most organizations, even more data is available. Historical data is usually archived and is therefore inaccessible for querying. Audit trails and other sources of information are often never imported into databases in the first place. But with Hadoop MapReduce due to its highly parallelized operation it is possible to harvest vast amounts of data in an acceptable time. This makes full data analysis a realistic option, which can lead to insights driving new business. Hadoop enables enterprises to essentially skip the database, and to query large amounts of source data directly by using a cluster that processes large amounts of data in just minutes. On the technical side, Hadoop and other NoSQL related technologies have shown themselves to be production-ready and mature software solutions that are now available for enterprise use. With many companies offering professional services and support for the several NoSQL technologies, the risk of early adoption is manageable. Combined with the competitive advantage that can come from being a early adopter, NoSQL and big data analysis should be considered by organizations that acquire or own substantial amounts of data of any kind. Xebia Nederland b.v., Utrechtseweg 49, 1213 TL Hilversum, The Netherlands, Tel: +31(0) , 6

PAGE 1 l Teradata Magazine l Q1/2011 l 2011 Teradata Corporation l AR-6309

PAGE 1 l Teradata Magazine l Q1/2011 l 2011 Teradata Corporation l AR-6309 PAGE 1 l Teradata Magazine l Q1/2011 l 2011 Teradata Corporation l AR-6309 It s going mainstream, and it s your next opportunity. by Merv Adrian Enterprises have never had more data, and it s no surprise

More information

W H I T E P A P E R. Deriving Intelligence from Large Data Using Hadoop and Applying Analytics. Abstract

W H I T E P A P E R. Deriving Intelligence from Large Data Using Hadoop and Applying Analytics. Abstract W H I T E P A P E R Deriving Intelligence from Large Data Using Hadoop and Applying Analytics Abstract This white paper is focused on discussing the challenges facing large scale data processing and the

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

How to Enhance Traditional BI Architecture to Leverage Big Data

How to Enhance Traditional BI Architecture to Leverage Big Data B I G D ATA How to Enhance Traditional BI Architecture to Leverage Big Data Contents Executive Summary... 1 Traditional BI - DataStack 2.0 Architecture... 2 Benefits of Traditional BI - DataStack 2.0...

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

Keywords Big Data, NoSQL, Relational Databases, Decision Making using Big Data, Hadoop

Keywords Big Data, NoSQL, Relational Databases, Decision Making using Big Data, Hadoop Volume 4, Issue 1, January 2014 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Transitioning

More information

ANALYTICS BUILT FOR INTERNET OF THINGS

ANALYTICS BUILT FOR INTERNET OF THINGS ANALYTICS BUILT FOR INTERNET OF THINGS Big Data Reporting is Out, Actionable Insights are In In recent years, it has become clear that data in itself has little relevance, it is the analysis of it that

More information

ESS event: Big Data in Official Statistics. Antonino Virgillito, Istat

ESS event: Big Data in Official Statistics. Antonino Virgillito, Istat ESS event: Big Data in Official Statistics Antonino Virgillito, Istat v erbi v is 1 About me Head of Unit Web and BI Technologies, IT Directorate of Istat Project manager and technical coordinator of Web

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

Big Data, Big Traffic. And the WAN

Big Data, Big Traffic. And the WAN Big Data, Big Traffic And the WAN Internet Research Group January, 2012 About The Internet Research Group www.irg-intl.com The Internet Research Group (IRG) provides market research and market strategy

More information

BIG DATA IS MESSY PARTNER WITH SCALABLE

BIG DATA IS MESSY PARTNER WITH SCALABLE BIG DATA IS MESSY PARTNER WITH SCALABLE SCALABLE SYSTEMS HADOOP SOLUTION WHAT IS BIG DATA? Each day human beings create 2.5 quintillion bytes of data. In the last two years alone over 90% of the data on

More information

Datenverwaltung im Wandel - Building an Enterprise Data Hub with

Datenverwaltung im Wandel - Building an Enterprise Data Hub with Datenverwaltung im Wandel - Building an Enterprise Data Hub with Cloudera Bernard Doering Regional Director, Central EMEA, Cloudera Cloudera Your Hadoop Experts Founded 2008, by former employees of Employees

More information

Extending the Enterprise Data Warehouse with Hadoop Robert Lancaster. Nov 7, 2012

Extending the Enterprise Data Warehouse with Hadoop Robert Lancaster. Nov 7, 2012 Extending the Enterprise Data Warehouse with Hadoop Robert Lancaster Nov 7, 2012 Who I Am Robert Lancaster Solutions Architect, Hotel Supply Team rlancaster@orbitz.com @rob1lancaster Organizer of Chicago

More information

A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM

A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM Sneha D.Borkar 1, Prof.Chaitali S.Surtakar 2 Student of B.E., Information Technology, J.D.I.E.T, sborkar95@gmail.com Assistant Professor, Information

More information

Converged, Real-time Analytics Enabling Faster Decision Making and New Business Opportunities

Converged, Real-time Analytics Enabling Faster Decision Making and New Business Opportunities Technology Insight Paper Converged, Real-time Analytics Enabling Faster Decision Making and New Business Opportunities By John Webster February 2015 Enabling you to make the best technology decisions Enabling

More information

BIG DATA What it is and how to use?

BIG DATA What it is and how to use? BIG DATA What it is and how to use? Lauri Ilison, PhD Data Scientist 21.11.2014 Big Data definition? There is no clear definition for BIG DATA BIG DATA is more of a concept than precise term 1 21.11.14

More information

The Future of Data Management

The Future of Data Management The Future of Data Management with Hadoop and the Enterprise Data Hub Amr Awadallah (@awadallah) Cofounder and CTO Cloudera Snapshot Founded 2008, by former employees of Employees Today ~ 800 World Class

More information

Lambda Architecture. Near Real-Time Big Data Analytics Using Hadoop. January 2015. Email: bdg@qburst.com Website: www.qburst.com

Lambda Architecture. Near Real-Time Big Data Analytics Using Hadoop. January 2015. Email: bdg@qburst.com Website: www.qburst.com Lambda Architecture Near Real-Time Big Data Analytics Using Hadoop January 2015 Contents Overview... 3 Lambda Architecture: A Quick Introduction... 4 Batch Layer... 4 Serving Layer... 4 Speed Layer...

More information

Big Data Analytics. with EMC Greenplum and Hadoop. Big Data Analytics. Ofir Manor Pre Sales Technical Architect EMC Greenplum

Big Data Analytics. with EMC Greenplum and Hadoop. Big Data Analytics. Ofir Manor Pre Sales Technical Architect EMC Greenplum Big Data Analytics with EMC Greenplum and Hadoop Big Data Analytics with EMC Greenplum and Hadoop Ofir Manor Pre Sales Technical Architect EMC Greenplum 1 Big Data and the Data Warehouse Potential All

More information

Firebird meets NoSQL (Apache HBase) Case Study

Firebird meets NoSQL (Apache HBase) Case Study Firebird meets NoSQL (Apache HBase) Case Study Firebird Conference 2011 Luxembourg 25.11.2011 26.11.2011 Thomas Steinmaurer DI +43 7236 3343 896 thomas.steinmaurer@scch.at www.scch.at Michael Zwick DI

More information

Big Data Technology ดร.ช ชาต หฤไชยะศ กด. Choochart Haruechaiyasak, Ph.D.

Big Data Technology ดร.ช ชาต หฤไชยะศ กด. Choochart Haruechaiyasak, Ph.D. Big Data Technology ดร.ช ชาต หฤไชยะศ กด Choochart Haruechaiyasak, Ph.D. Speech and Audio Technology Laboratory (SPT) National Electronics and Computer Technology Center (NECTEC) National Science and Technology

More information

How In-Memory Data Grids Can Analyze Fast-Changing Data in Real Time

How In-Memory Data Grids Can Analyze Fast-Changing Data in Real Time SCALEOUT SOFTWARE How In-Memory Data Grids Can Analyze Fast-Changing Data in Real Time by Dr. William Bain and Dr. Mikhail Sobolev, ScaleOut Software, Inc. 2012 ScaleOut Software, Inc. 12/27/2012 T wenty-first

More information

Architectures for Big Data Analytics A database perspective

Architectures for Big Data Analytics A database perspective Architectures for Big Data Analytics A database perspective Fernando Velez Director of Product Management Enterprise Information Management, SAP June 2013 Outline Big Data Analytics Requirements Spectrum

More information

Hadoop Beyond Hype: Complex Adaptive Systems Conference Nov 16, 2012. Viswa Sharma Solutions Architect Tata Consultancy Services

Hadoop Beyond Hype: Complex Adaptive Systems Conference Nov 16, 2012. Viswa Sharma Solutions Architect Tata Consultancy Services Hadoop Beyond Hype: Complex Adaptive Systems Conference Nov 16, 2012 Viswa Sharma Solutions Architect Tata Consultancy Services 1 Agenda What is Hadoop Why Hadoop? The Net Generation is here Sizing the

More information

There s no way around it: learning about Big Data means

There s no way around it: learning about Big Data means In This Chapter Chapter 1 Introducing Big Data Beginning with Big Data Meeting MapReduce Saying hello to Hadoop Making connections between Big Data, MapReduce, and Hadoop There s no way around it: learning

More information

Big Data. White Paper. Big Data Executive Overview WP-BD-10312014-01. Jafar Shunnar & Dan Raver. Page 1 Last Updated 11-10-2014

Big Data. White Paper. Big Data Executive Overview WP-BD-10312014-01. Jafar Shunnar & Dan Raver. Page 1 Last Updated 11-10-2014 White Paper Big Data Executive Overview WP-BD-10312014-01 By Jafar Shunnar & Dan Raver Page 1 Last Updated 11-10-2014 Table of Contents Section 01 Big Data Facts Page 3-4 Section 02 What is Big Data? Page

More information

Big Data and Apache Hadoop Adoption:

Big Data and Apache Hadoop Adoption: Expert Reference Series of White Papers Big Data and Apache Hadoop Adoption: Key Challenges and Rewards 1-800-COURSES www.globalknowledge.com Big Data and Apache Hadoop Adoption: Key Challenges and Rewards

More information

Massive Cloud Auditing using Data Mining on Hadoop

Massive Cloud Auditing using Data Mining on Hadoop Massive Cloud Auditing using Data Mining on Hadoop Prof. Sachin Shetty CyberBAT Team, AFRL/RIGD AFRL VFRP Tennessee State University Outline Massive Cloud Auditing Traffic Characterization Distributed

More information

Beyond Web Application Log Analysis using Apache TM Hadoop. A Whitepaper by Orzota, Inc.

Beyond Web Application Log Analysis using Apache TM Hadoop. A Whitepaper by Orzota, Inc. Beyond Web Application Log Analysis using Apache TM Hadoop A Whitepaper by Orzota, Inc. 1 Web Applications As more and more software moves to a Software as a Service (SaaS) model, the web application has

More information

White. Paper. EMC Isilon: A Scalable Storage Platform for Big Data. April 2014

White. Paper. EMC Isilon: A Scalable Storage Platform for Big Data. April 2014 White Paper EMC Isilon: A Scalable Storage Platform for Big Data By Nik Rouda, Senior Analyst and Terri McClure, Senior Analyst April 2014 This ESG White Paper was commissioned by EMC Isilon and is distributed

More information

Well packaged sets of preinstalled, integrated, and optimized software on select hardware in the form of engineered systems and appliances

Well packaged sets of preinstalled, integrated, and optimized software on select hardware in the form of engineered systems and appliances INSIGHT Oracle's All- Out Assault on the Big Data Market: Offering Hadoop, R, Cubes, and Scalable IMDB in Familiar Packages Carl W. Olofson IDC OPINION Global Headquarters: 5 Speen Street Framingham, MA

More information

IBM System x reference architecture solutions for big data

IBM System x reference architecture solutions for big data IBM System x reference architecture solutions for big data Easy-to-implement hardware, software and services for analyzing data at rest and data in motion Highlights Accelerates time-to-value with scalable,

More information

Microsoft Big Data. Solution Brief

Microsoft Big Data. Solution Brief Microsoft Big Data Solution Brief Contents Introduction... 2 The Microsoft Big Data Solution... 3 Key Benefits... 3 Immersive Insight, Wherever You Are... 3 Connecting with the World s Data... 3 Any Data,

More information

Actian SQL in Hadoop Buyer s Guide

Actian SQL in Hadoop Buyer s Guide Actian SQL in Hadoop Buyer s Guide Contents Introduction: Big Data and Hadoop... 3 SQL on Hadoop Benefits... 4 Approaches to SQL on Hadoop... 4 The Top 10 SQL in Hadoop Capabilities... 5 SQL in Hadoop

More information

Hadoop Big Data for Processing Data and Performing Workload

Hadoop Big Data for Processing Data and Performing Workload Hadoop Big Data for Processing Data and Performing Workload Girish T B 1, Shadik Mohammed Ghouse 2, Dr. B. R. Prasad Babu 3 1 M Tech Student, 2 Assosiate professor, 3 Professor & Head (PG), of Computer

More information

Optimize Your Data Warehouse with Hadoop The first steps to transform the economics of data warehousing.

Optimize Your Data Warehouse with Hadoop The first steps to transform the economics of data warehousing. Optimize Your Data Warehouse with Hadoop The first steps to transform the economics of data warehousing. This white paper addresses the challenge of controlling the rising costs of operating and maintaining

More information

Open source Google-style large scale data analysis with Hadoop

Open source Google-style large scale data analysis with Hadoop Open source Google-style large scale data analysis with Hadoop Ioannis Konstantinou Email: ikons@cslab.ece.ntua.gr Web: http://www.cslab.ntua.gr/~ikons Computing Systems Laboratory School of Electrical

More information

Using Big Data for Smarter Decision Making. Colin White, BI Research July 2011 Sponsored by IBM

Using Big Data for Smarter Decision Making. Colin White, BI Research July 2011 Sponsored by IBM Using Big Data for Smarter Decision Making Colin White, BI Research July 2011 Sponsored by IBM USING BIG DATA FOR SMARTER DECISION MAKING To increase competitiveness, 83% of CIOs have visionary plans that

More information

Powerful Duo: MapR Big Data Analytics with Cisco ACI Network Switches

Powerful Duo: MapR Big Data Analytics with Cisco ACI Network Switches Powerful Duo: MapR Big Data Analytics with Cisco ACI Network Switches Introduction For companies that want to quickly gain insights into or opportunities from big data - the dramatic volume growth in corporate

More information

Advanced Big Data Analytics with R and Hadoop

Advanced Big Data Analytics with R and Hadoop REVOLUTION ANALYTICS WHITE PAPER Advanced Big Data Analytics with R and Hadoop 'Big Data' Analytics as a Competitive Advantage Big Analytics delivers competitive advantage in two ways compared to the traditional

More information

Big Data at Cloud Scale

Big Data at Cloud Scale Big Data at Cloud Scale Pushing the limits of flexible & powerful analytics Copyright 2015 Pentaho Corporation. Redistribution permitted. All trademarks are the property of their respective owners. For

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

INTRODUCTION TO APACHE HADOOP MATTHIAS BRÄGER CERN GS-ASE

INTRODUCTION TO APACHE HADOOP MATTHIAS BRÄGER CERN GS-ASE INTRODUCTION TO APACHE HADOOP MATTHIAS BRÄGER CERN GS-ASE AGENDA Introduction to Big Data Introduction to Hadoop HDFS file system Map/Reduce framework Hadoop utilities Summary BIG DATA FACTS In what timeframe

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

The 3 questions to ask yourself about BIG DATA

The 3 questions to ask yourself about BIG DATA The 3 questions to ask yourself about BIG DATA Do you have a big data problem? Companies looking to tackle big data problems are embarking on a journey that is full of hype, buzz, confusion, and misinformation.

More information

Big Data Defined Introducing DataStack 3.0

Big Data Defined Introducing DataStack 3.0 Big Data Big Data Defined Introducing DataStack 3.0 Inside: Executive Summary... 1 Introduction... 2 Emergence of DataStack 3.0... 3 DataStack 1.0 to 2.0... 4 DataStack 2.0 Refined for Large Data & Analytics...

More information

The Enterprise Data Hub and The Modern Information Architecture

The Enterprise Data Hub and The Modern Information Architecture The Enterprise Data Hub and The Modern Information Architecture Dr. Amr Awadallah CTO & Co-Founder, Cloudera Twitter: @awadallah 1 2013 Cloudera, Inc. All rights reserved. Cloudera Overview The Leader

More information

GigaSpaces Real-Time Analytics for Big Data

GigaSpaces Real-Time Analytics for Big Data GigaSpaces Real-Time Analytics for Big Data GigaSpaces makes it easy to build and deploy large-scale real-time analytics systems Rapidly increasing use of large-scale and location-aware social media and

More information

Hadoop and Map-Reduce. Swati Gore

Hadoop and Map-Reduce. Swati Gore Hadoop and Map-Reduce Swati Gore Contents Why Hadoop? Hadoop Overview Hadoop Architecture Working Description Fault Tolerance Limitations Why Map-Reduce not MPI Distributed sort Why Hadoop? Existing Data

More information

Luncheon Webinar Series May 13, 2013

Luncheon Webinar Series May 13, 2013 Luncheon Webinar Series May 13, 2013 InfoSphere DataStage is Big Data Integration Sponsored By: Presented by : Tony Curcio, InfoSphere Product Management 0 InfoSphere DataStage is Big Data Integration

More information

Integrate Big Data into Business Processes and Enterprise Systems. solution white paper

Integrate Big Data into Business Processes and Enterprise Systems. solution white paper Integrate Big Data into Business Processes and Enterprise Systems solution white paper THOUGHT LEADERSHIP FROM BMC TO HELP YOU: Understand what Big Data means Effectively implement your company s Big Data

More information

Agile Business Intelligence Data Lake Architecture

Agile Business Intelligence Data Lake Architecture Agile Business Intelligence Data Lake Architecture TABLE OF CONTENTS Introduction... 2 Data Lake Architecture... 2 Step 1 Extract From Source Data... 5 Step 2 Register And Catalogue Data Sets... 5 Step

More information

Big Data With Hadoop

Big Data With Hadoop With Saurabh Singh singh.903@osu.edu The Ohio State University February 11, 2016 Overview 1 2 3 Requirements Ecosystem Resilient Distributed Datasets (RDDs) Example Code vs Mapreduce 4 5 Source: [Tutorials

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

BIG DATA TOOLS. Top 10 open source technologies for Big Data

BIG DATA TOOLS. Top 10 open source technologies for Big Data BIG DATA TOOLS Top 10 open source technologies for Big Data We are in an ever expanding marketplace!!! With shorter product lifecycles, evolving customer behavior and an economy that travels at the speed

More information

Hadoop vs Apache Spark

Hadoop vs Apache Spark Innovate, Integrate, Transform Hadoop vs Apache Spark www.altencalsoftlabs.com Introduction Any sufficiently advanced technology is indistinguishable from magic. said Arthur C. Clark. Big data technologies

More information

Offload Historical Data to Big Data Lake. Ample White Paper

Offload Historical Data to Big Data Lake. Ample White Paper Offload Historical Data to Big Data Lake The Need to Offload Historical Data for Compliance Queries How often have heard that the legal or compliance department group needs to have access to your company

More information

Implement Hadoop jobs to extract business value from large and varied data sets

Implement Hadoop jobs to extract business value from large and varied data sets Hadoop Development for Big Data Solutions: Hands-On You Will Learn How To: Implement Hadoop jobs to extract business value from large and varied data sets Write, customize and deploy MapReduce jobs to

More information

Integrating Big Data into Business Processes and Enterprise Systems

Integrating Big Data into Business Processes and Enterprise Systems Integrating Big Data into Business Processes and Enterprise Systems THOUGHT LEADERSHIP FROM BMC TO HELP YOU: Understand what Big Data means Effectively implement your company s Big Data strategy Get business

More information

Big Data Zurich, November 23. September 2011

Big Data Zurich, November 23. September 2011 Institute of Technology Management Big Data Projektskizze «Competence Center Automotive Intelligence» Zurich, November 11th 23. September 2011 Felix Wortmann Assistant Professor Technology Management,

More information

Are You Ready for Big Data?

Are You Ready for Big Data? Are You Ready for Big Data? Jim Gallo National Director, Business Analytics April 10, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

More information

Modern Payment Fraud Prevention at Big Data Scale

Modern Payment Fraud Prevention at Big Data Scale This whitepaper discusses Feedzai s machine learning and behavioral profiling capabilities for payment fraud prevention. These capabilities allow modern fraud systems to move from broad segment-based scoring

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

White Paper Storage for Big Data and Analytics Challenges

White Paper Storage for Big Data and Analytics Challenges White Paper Storage for Big Data and Analytics Challenges Abstract Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10

More information

White Paper: What You Need To Know About Hadoop

White Paper: What You Need To Know About Hadoop CTOlabs.com White Paper: What You Need To Know About Hadoop June 2011 A White Paper providing succinct information for the enterprise technologist. Inside: What is Hadoop, really? Issues the Hadoop stack

More information

HADOOP SOLUTION USING EMC ISILON AND CLOUDERA ENTERPRISE Efficient, Flexible In-Place Hadoop Analytics

HADOOP SOLUTION USING EMC ISILON AND CLOUDERA ENTERPRISE Efficient, Flexible In-Place Hadoop Analytics HADOOP SOLUTION USING EMC ISILON AND CLOUDERA ENTERPRISE Efficient, Flexible In-Place Hadoop Analytics ESSENTIALS EMC ISILON Use the industry's first and only scale-out NAS solution with native Hadoop

More information

THE DEVELOPER GUIDE TO BUILDING STREAMING DATA APPLICATIONS

THE DEVELOPER GUIDE TO BUILDING STREAMING DATA APPLICATIONS THE DEVELOPER GUIDE TO BUILDING STREAMING DATA APPLICATIONS WHITE PAPER Successfully writing Fast Data applications to manage data generated from mobile, smart devices and social interactions, and the

More information

From Spark to Ignition:

From Spark to Ignition: From Spark to Ignition: Fueling Your Business on Real-Time Analytics Eric Frenkiel, MemSQL CEO June 29, 2015 San Francisco, CA What s in Store For This Presentation? 1. MemSQL: A real-time database for

More information

INDUS / AXIOMINE. Adopting Hadoop In the Enterprise Typical Enterprise Use Cases

INDUS / AXIOMINE. Adopting Hadoop In the Enterprise Typical Enterprise Use Cases INDUS / AXIOMINE Adopting Hadoop In the Enterprise Typical Enterprise Use Cases. Contents Executive Overview... 2 Introduction... 2 Traditional Data Processing Pipeline... 3 ETL is prevalent Large Scale

More information

Three Open Blueprints For Big Data Success

Three Open Blueprints For Big Data Success White Paper: Three Open Blueprints For Big Data Success Featuring Pentaho s Open Data Integration Platform Inside: Leverage open framework and open source Kickstart your efforts with repeatable blueprints

More information

Deploying an Operational Data Store Designed for Big Data

Deploying an Operational Data Store Designed for Big Data Deploying an Operational Data Store Designed for Big Data A fast, secure, and scalable data staging environment with no data volume or variety constraints Sponsored by: Version: 102 Table of Contents Introduction

More information

How to use Big Data in Industry 4.0 implementations. LAURI ILISON, PhD Head of Big Data and Machine Learning

How to use Big Data in Industry 4.0 implementations. LAURI ILISON, PhD Head of Big Data and Machine Learning How to use Big Data in Industry 4.0 implementations LAURI ILISON, PhD Head of Big Data and Machine Learning Big Data definition? Big Data is about structured vs unstructured data Big Data is about Volume

More information

Investor Presentation. Second Quarter 2015

Investor Presentation. Second Quarter 2015 Investor Presentation Second Quarter 2015 Note to Investors Certain non-gaap financial information regarding operating results may be discussed during this presentation. Reconciliations of the differences

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

Using Tableau Software with Hortonworks Data Platform

Using Tableau Software with Hortonworks Data Platform Using Tableau Software with Hortonworks Data Platform September 2013 2013 Hortonworks Inc. http:// Modern businesses need to manage vast amounts of data, and in many cases they have accumulated this data

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

Integrate and Deliver Trusted Data and Enable Deep Insights

Integrate and Deliver Trusted Data and Enable Deep Insights SAP Technical Brief SAP s for Enterprise Information Management SAP Data Services Objectives Integrate and Deliver Trusted Data and Enable Deep Insights Provide a wide-ranging view of enterprise information

More information

Oracle s Big Data solutions. Roger Wullschleger.

Oracle s Big Data solutions. Roger Wullschleger. <Insert Picture Here> s Big Data solutions Roger Wullschleger DBTA Workshop on Big Data, Cloud Data Management and NoSQL 10. October 2012, Stade de Suisse, Berne 1 The following is intended to outline

More information

1 Performance Moves to the Forefront for Data Warehouse Initiatives. 2 Real-Time Data Gets Real

1 Performance Moves to the Forefront for Data Warehouse Initiatives. 2 Real-Time Data Gets Real Top 10 Data Warehouse Trends for 2013 What are the most compelling trends in storage and data warehousing that motivate IT leaders to undertake new initiatives? Which ideas, solutions, and technologies

More information

TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP

TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP Pythian White Paper TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP ABSTRACT As companies increasingly rely on big data to steer decisions, they also find themselves looking for ways to simplify

More information

Interactive data analytics drive insights

Interactive data analytics drive insights Big data Interactive data analytics drive insights Daniel Davis/Invodo/S&P. Screen images courtesy of Landmark Software and Services By Armando Acosta and Joey Jablonski The Apache Hadoop Big data has

More information

Turn your information into a competitive advantage

Turn your information into a competitive advantage INDLÆG 03 Data Driven Business Value Turn your information into a competitive advantage Jonas Linders 04.10.2015 (dato) CGI Group Inc. 2015 Jonas Linders Education Role Industries M.Sc Informatics Experience

More information

Why DBMSs Matter More than Ever in the Big Data Era

Why DBMSs Matter More than Ever in the Big Data Era E-PAPER FEBRUARY 2014 Why DBMSs Matter More than Ever in the Big Data Era Having the right database infrastructure can make or break big data analytics projects. TW_1401138 Big data has become big news

More information

Einsatzfelder von IBM PureData Systems und Ihre Vorteile.

Einsatzfelder von IBM PureData Systems und Ihre Vorteile. Einsatzfelder von IBM PureData Systems und Ihre Vorteile demirkaya@de.ibm.com Agenda Information technology challenges PureSystems and PureData introduction PureData for Transactions PureData for Analytics

More information

Information Architecture

Information Architecture The Bloor Group Actian and The Big Data Information Architecture WHITE PAPER The Actian Big Data Information Architecture Actian and The Big Data Information Architecture Originally founded in 2005 to

More information

Talend Real-Time Big Data Sandbox. Big Data Insights Cookbook

Talend Real-Time Big Data Sandbox. Big Data Insights Cookbook Talend Real-Time Big Data Talend Real-Time Big Data Overview of Real-time Big Data Pre-requisites to run Setup & Talend License Talend Real-Time Big Data Big Data Setup & About this cookbook What is the

More information

Application and practice of parallel cloud computing in ISP. Guangzhou Institute of China Telecom Zhilan Huang 2011-10

Application and practice of parallel cloud computing in ISP. Guangzhou Institute of China Telecom Zhilan Huang 2011-10 Application and practice of parallel cloud computing in ISP Guangzhou Institute of China Telecom Zhilan Huang 2011-10 Outline Mass data management problem Applications of parallel cloud computing in ISPs

More information

Big Data Use Case: Business Analytics

Big Data Use Case: Business Analytics Big Data Use Case: Business Analytics Starting point A telecommunications company wants to allude to the topic of Big Data. The established Big Data working group has access to the data stock of the enterprise

More information

Making Sense of the Madness

Making Sense of the Madness Making Sense of the Madness Deploying Big Data techniques to deal with real world Bigish Data issues Copyright James Mitchell 2014 1 Introduction Warning! Parental Guidance Recommended Please read the

More information

Benchmarking Hadoop & HBase on Violin

Benchmarking Hadoop & HBase on Violin Technical White Paper Report Technical Report Benchmarking Hadoop & HBase on Violin Harnessing Big Data Analytics at the Speed of Memory Version 1.0 Abstract The purpose of benchmarking is to show advantages

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

Hadoop. http://hadoop.apache.org/ Sunday, November 25, 12

Hadoop. http://hadoop.apache.org/ Sunday, November 25, 12 Hadoop http://hadoop.apache.org/ What Is Apache Hadoop? The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using

More information

What are Hadoop and MapReduce and how did we get here?

What are Hadoop and MapReduce and how did we get here? What are Hadoop and MapReduce and how did we get here? Term Big Data coined in 2005 by Roger Magoulas of O Reilly Media But as the idea of big data sets evolved on the Web, organizations began to wonder

More information

Big Data: Beyond the Hype

Big Data: Beyond the Hype Big Data: Beyond the Hype Why Big Data Matters to You WHITE PAPER Big Data: Beyond the Hype Why Big Data Matters to You By DataStax Corporation October 2011 Table of Contents Introduction...4 Big Data

More information

The Rise of Industrial Big Data

The Rise of Industrial Big Data GE Intelligent Platforms The Rise of Industrial Big Data Leveraging large time-series data sets to drive innovation, competitiveness and growth capitalizing on the big data opportunity The Rise of Industrial

More information

Are You Ready for Big Data?

Are You Ready for Big Data? Are You Ready for Big Data? Jim Gallo National Director, Business Analytics February 11, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

More information

Hadoop Cluster Applications

Hadoop Cluster Applications Hadoop Overview Data analytics has become a key element of the business decision process over the last decade. Classic reporting on a dataset stored in a database was sufficient until recently, but yesterday

More information

RevoScaleR Speed and Scalability

RevoScaleR Speed and Scalability EXECUTIVE WHITE PAPER RevoScaleR Speed and Scalability By Lee Edlefsen Ph.D., Chief Scientist, Revolution Analytics Abstract RevoScaleR, the Big Data predictive analytics library included with Revolution

More information

Big Data Tools: Game Changer for Mainstream Enterprises

Big Data Tools: Game Changer for Mainstream Enterprises Big Data Tools: Game Changer for Mainstream Enterprises Aashish Chandra DVP, Application Modernization, Sears Holdings & GM, Big Data / Legacy Modernization, MetaScale LLC Inside the Modern Consumer s

More information