BIG DATA SOLUTION DATA SHEET

Similar documents
Hadoop. MPDL-Frühstück 9. Dezember 2013 MPDL INTERN

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

Hadoop s Entry into the Traditional Analytical DBMS Market. Daniel Abadi Yale University August 3 rd, 2010

BIG DATA USING HADOOP

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

The Inside Scoop on Hadoop

Lambda Architecture. Near Real-Time Big Data Analytics Using Hadoop. January Website:

Hadoop: A Framework for Data- Intensive Distributed Computing. CS561-Spring 2012 WPI, Mohamed Y. Eltabakh

Hadoop and Map-Reduce. Swati Gore

BIG DATA TRENDS AND TECHNOLOGIES

Hadoop IST 734 SS CHUNG

Open source Google-style large scale data analysis with Hadoop

Open Cloud System. (Integration of Eucalyptus, Hadoop and AppScale into deployment of University Private Cloud)

Big Data for Investment Research Management

Cost-Effective Business Intelligence with Red Hat and Open Source

AGENDA. What is BIG DATA? What is Hadoop? Why Microsoft? The Microsoft BIG DATA story. Our BIG DATA Roadmap. Hadoop PDW

Data processing goes big

Real World Big Data Architecture - Splunk, Hadoop, RDBMS

Chapter 7. Using Hadoop Cluster and MapReduce

NoSQL and Hadoop Technologies On Oracle Cloud

Click Stream Data Analysis Using Hadoop

Workshop on Hadoop with Big Data

Apache Hadoop. Alexandru Costan

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

EXPERIMENTATION. HARRISON CARRANZA School of Computer Science and Mathematics

Big Data Analytics - Accelerated. stream-horizon.com

INTRODUCTION TO APACHE HADOOP MATTHIAS BRÄGER CERN GS-ASE

Session 1: IT Infrastructure Security Vertica / Hadoop Integration and Analytic Capabilities for Federal Big Data Challenges

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY

Big Data Analytics OverOnline Transactional Data Set

An Industrial Perspective on the Hadoop Ecosystem. Eldar Khalilov Pavel Valov

Log Mining Based on Hadoop s Map and Reduce Technique

Big Data and Apache Hadoop s MapReduce

Big Business, Big Data, Industrialized Workload

Introduction to Hadoop HDFS and Ecosystems. Slides credits: Cloudera Academic Partners Program & Prof. De Liu, MSBA 6330 Harvesting Big Data

Big Data: Using ArcGIS with Apache Hadoop. Erik Hoel and Mike Park

Chapter 11 Map-Reduce, Hadoop, HDFS, Hbase, MongoDB, Apache HIVE, and Related

Mr. Apichon Witayangkurn Department of Civil Engineering The University of Tokyo

Hadoop & its Usage at Facebook

Case Study : 3 different hadoop cluster deployments

How To Scale Out Of A Nosql Database

You should have a working knowledge of the Microsoft Windows platform. A basic knowledge of programming is helpful but not required.

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

Big Data on Microsoft Platform

A PERFORMANCE ANALYSIS of HADOOP CLUSTERS in OPENSTACK CLOUD and in REAL SYSTEM

COURSE CONTENT Big Data and Hadoop Training

Infomatics. Big-Data and Hadoop Developer Training with Oracle WDP

Open source software framework designed for storage and processing of large scale data on clusters of commodity hardware

Prepared By : Manoj Kumar Joshi & Vikas Sawhney

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

Capitalize on Big Data for Competitive Advantage with Bedrock TM, an integrated Management Platform for Hadoop Data Lakes

Simplifying Big Data Analytics: Unifying Batch and Stream Processing. John Fanelli,! VP Product! In-Memory Compute Summit! June 30, 2015!!

Virtualizing Apache Hadoop. June, 2012

Hadoop Big Data for Processing Data and Performing Workload

Analytics in the Cloud. Peter Sirota, GM Elastic MapReduce

Luncheon Webinar Series May 13, 2013

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

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

Apache Hadoop: The Big Data Refinery

Data Solutions with Hadoop

Hadoop Ecosystem B Y R A H I M A.

Getting Started with Hadoop. Raanan Dagan Paul Tibaldi

Big Data for Investment Research Management

Hadoop. Sunday, November 25, 12

Hadoop Distributed File System. T Seminar On Multimedia Eero Kurkela

TAMING THE BIG CHALLENGE OF BIG DATA MICROSOFT HADOOP

MapReduce with Apache Hadoop Analysing Big Data

Large scale processing using Hadoop. Ján Vaňo

I/O Considerations in Big Data Analytics

Big Data. White Paper. Big Data Executive Overview WP-BD Jafar Shunnar & Dan Raver. Page 1 Last Updated

A Tour of the Zoo the Hadoop Ecosystem Prafulla Wani

Big Data and Data Science: Behind the Buzz Words

Oracle Big Data SQL Technical Update

Data Mining in the Swamp

Presenters: Luke Dougherty & Steve Crabb

Katta & Hadoop. Katta - Distributed Lucene Index in Production. Stefan Groschupf Scale Unlimited, 101tec. sg{at}101tec.com

IBM InfoSphere Guardium Data Activity Monitor for Hadoop-based systems

W H I T E P A P E R. Building your Big Data analytics strategy: Block-by-Block! Abstract

In-Memory Analytics for Big Data

Real-time Data Analytics mit Elasticsearch. Bernhard Pflugfelder inovex GmbH

Cloudera Certified Developer for Apache Hadoop

Agile Business Intelligence Data Lake Architecture

Hadoop Distributed File System. Dhruba Borthakur Apache Hadoop Project Management Committee

the missing log collector Treasure Data, Inc. Muga Nishizawa

Introduction to Cloud Computing

Deploying Hadoop with Manager

White Paper: Evaluating Big Data Analytical Capabilities For Government Use

Big Data and Industrial Internet

Apache Ignite TM (Incubating) - In- Memory Data Fabric Fast Data Meets Open Source

Composite Data Virtualization Composite Data Virtualization And NOSQL Data Stores

WHAT S NEW IN SAS 9.4

Qsoft Inc

White Paper: Datameer s User-Focused Big Data Solutions

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

Transcription:

BIG DATA SOLUTION DATA SHEET

Highlight. DATA SHEET HGrid247 BIG DATA SOLUTION Exploring your BIG DATA, get some deeper insight. It is possible! Another approach to access your BIG DATA with the latest technology, Hadoop Distribute applications across clusters of commodity hardware using MapReduce technique Large scaled distributed file system with unlimited scalability Highly fault tolerant and designed to be deployed on low cost hardware A proven framework implemented by large social media such as Google, Amazon, Facebook and Zynga It is difficult to develop real world applications. Not anymore, HGrid247 make it much easier HGri247 is Hadoop grid workflow designer created by Solusi247 with readyto use ETL library No coding or less coding experience to generate MapReduce code Now, transaction data is too big for a traditional data warehousing. Large social media, such as Google, Amazon, Facebook and Zynga have implemented an open source framework, Hadoop, to manage their data. It spans an arc from that sort of starting point to the enterprise to pick up Hadoop and use it as an alternative to the traditional data warehousing. In 20o4, Google described an architecture called MapReduce to support their query engine and Yahoo started an open source development project under Apache to bring the MapReduce forward. And created a distributed file system to support it called Hadoop Distributed File System (HDFS). And rather than take the conventional step of moving data over a network to be processed by program, MapReduce uses a smarter approach tailor made for big data sets. MapReduce moves the processing program to the data.

DATA SHEET Hadoop has become a mainstream for Big Data solution. Many big vendors like Oracle, IBM, Teradata, HP, Microsoft, and others have been busy adopting and implementing this technology into their offering stack. Hadoop has capabilities to be implemented as processing resource, storage or both at the same time. It scales up to tens of thousands of nodes, almost unlimited and processed peta bytes of data easily. Hadoop lets you store files bigger than what can be stored on one particular node or server. So you can store very, very large files. It also lets you store many, many files. HGrid247 Big Data Solution is an experiences based solution of Big Data. For more than a decade we plunge into large scale data processing of telco transaction data. HGrid247 Workflow Designer is application tool to generate MapReduce code with no or less coding experience required. Data Monitoring is an application to monitor the trend of data processing result. Hadoop is quite complex to use, thus we are creating tool to make the hadoop implementation much easier called HGrid247 Workflow Designer as part of HGrid247 Big Data Solution. HGrid247 Workflow Designer

DATA SHEET Features Drag and drop workflow design and visualization Ready to use ETL library: Transformator Converter Aggregator Combiner Join Group by Filter Duplicate check Ready to use workflow library: Pipe Splitter Buffer Merger PMML Check point Sequence workflow Custom library editor Basic Statistic and Data Mining Library Source and Sink Library Hadoop file system JDBC Executable map reduce generator Audit log counter process Performance optimization HGrid247 Workflow Designer. A graphical user interface designer that will ease the workflow design and implementation in Hadoop. HGrid247 Workflow Designer is provided by a comprehensive set of ETL functions, data preparation and predictive modeling library. HGrid247 Workflow Designer is built on top of cascading framework. Cascading is created in late 2007 as a new java API to implement functional programming for large data workflows. Cascading is a pattern language for enterprise data workflows which is simple to build, easy to test and robust in production.

DATA SHEET Benefits Develop and test code from any development environment including from PC or Laptop Easy deployment to Hadoop Grid Cluster Additional functions is easily written and added as UDF in Java (simple and easy, not necessary to learn any new language/ script) Help organization accelerating time to value by reducing complexity in big data implementation

Powered By : Segitiga Emas Bussiness Park Unit No 6 Jl. Dr. Satrio Kav-6 Jakarta 12940- Indonesia Tel. +62 21 579511 32 (Hunting) Fax. +62 21 579511 28