preparing your infrastructure to tap big … · 2017-05-30 · your current infrastructure. ... sap...
TRANSCRIPT
The promise of big data to transform business outcomes is immense. Companies that embrace the full breadth of opportunities presented by big data will not only gain competitive advantage, but also transform their business models and create growth in new and unexpected ways.
However, taking advantage of big data may require changes to your current infrastructure. Here you will find a brief overview of key technology requirements to help you plan an effective big data roadmap.
NAVIGATING A CROWDED LANDSCAPEThe crowded technology landscape offers a confusing plethora of software and hardware products. Business and IT leaders are inundated with advertisements for big data solutions.
Solutions fall broadly into five categories:Data sources and capture: These are the data gatherers, such as Facebook and Twitter, as well as solutions that access and parse data from multiple sources.
IT infrastructure: Hardware and software designed to support the performance demands of big data analysis, security and management.
Data management and integration: Solutions that allow both structured and unstructured data to be tapped and, in some cases, cached for faster processing.
Analytics platforms and solutions: Open source and proprietary data platforms to run algorithms based on business needs.
Analytics services and support: Monitoring and maintenance of big data platforms and functions.
Organizations have many options for architecting a big data solution—from open source point solutions to integrated big data offerings from the largest technology vendors (such as EMC/Pivotal, Intel, Cisco, Cloudera, Hortonworks, HP and MapR)
Standardized architecture, such as industry-leading Intel® processor-based servers, supports distributed processing of data and objects across a network of connected systems through the sharing of resources on that system. To determine the right big data technology stack, companies need to evaluate a variety of new technologies designed for accessing and processing massive data stores.
PREPARING YOUR INFRASTRUCTURE TO TAP BIG DATA VALUE NAVIGATING BIG DATA TECHNOLOGIES
2
BIG DATA INFRASTRUCTURE BRIEF
© Copyright 2014 by World Wide Technology, Inc. All Rights Reserved
To deploy an appropriate software and hardware stack, it’s important to understand the foundational big data technologies, described in the table below.
KEY DATABASE/SOFTWARE TECHNOLOGIES
PURPOSE
Hadoop and MapReduce Open source software for intensive distributed applications on clusters• Hadoop Distributed File System (HDFS) to automatically distribute blocks over a large
number of data nodes• Language (MapReduce) to distribute jobs for parallel processing and assemble results
NoSQL A family of non-relational databases for flexible, large-scale data storage • Web-scale database• High performance and high availability• Rapid retrieval• Input to MapReduce• Load can easily grow by distributing itself over cost-effective Intel®-based servers
Relational Analytics Databases
Grid-based, column-oriented, analytic databases designed to manage large, fast-growing volumes of data • Provides very fast query performance when used for data warehouses and other
query-intensive applications• Optimized for Online Analytical Processing (OLAP) and data storage and retrieval
for advanced analytics
In-Memory Designed to deliver better performance of both analytical and transactional applications through multiengine query processing• Complex event processing• Real-time analytics• Common database for transactions and analytics• Supports relational data and graph and text processing for semi-structured and
unstructured data management
Ingest Engines Enable user-developed applications to quickly ingest, analyze and correlate information as it arrives from hundreds of real-time sources.• Flexible platforms providing data integration solutions designed to scale for any type of
integration challenge and volume of data (can handle very high data throughput rates, up to millions of events or messages per second)
© Copyright 2014 by World Wide Technology, Inc. All Rights Reserved 3
BIG DATA INFRASTRUCTURE BRIEF
AC
QU
IRE
DA
TAO
RG
AN
IZE
AN
ALY
ZE
DE
CID
E
Analytics
Access/Queries
AnalyticsDatabase
Transform
Management
File System Database
Ingest
Real time and batch
Optimized for high volume reads
Flexible, compressed, fast read
Fast, scalable
Provisioning maintenance
Parallel, distributed
Interfaces to accept data
OLAPNatural LanguageCustom Analytics
Custom APIsSQL
ColumnarIn-MemoryParallel RDBMS MapReduce
HDFSNoSQL - Document - Key value - Wide column
BatchStreaming
INTEGRATED LAYERS PROPERTIES OPTIONS EXAMPLES OF PRODUCTS OFFERINGS
SASSPSS
SplunkTalend
Greenplum
ParAccel
Vertica
Vectorwise
Cloudera
Hortonworks
MapR
Intel
EMC/Pivotal HD /Greenplum
HP/Vertica/Cloudera
Oracle Big Data Appliance/ exadata/ exalytics
IBM InfoSphere BigInsights
SAP HANA
Terracotta BigMemory
RPython
SQLPIGHive
SqoopFlume
HadoopCassandraMongoDB
HBase
Hadoop
Zookeeper
Visualization > Forecasts > Pricing > Reports > Alerts > Scores > O�ersUser/Machine Workflow >
Legend: Proprietary or Commercial Open SourceOpen Source
Enterprise Structured Enterprise Unstructured Third Party Web/Unstructured
ODS Data Warehouse Call Center Server Logs Financial Demographic
The big data software stack, shown below, illustrates how the foundational technologies work together to convert data to insight, and how they fit with tools for ingest, management and analytics. It also lists sample products for each layer in the stack.
THE BIG DATA STACK
HOW WWT CAN HELP
Effective big data decisions align both business and IT requirements. WWT delivers a unique end-to-end big data capability from use case design to infrastructure implementation to proof-of-concept (POC) deployment.
WWT can help you capture big data opportunities by:1. Outlining strategic, precisely defined use cases
2. Delivering analytical and consulting support for use cases and POCs
3. Determining current state capability and identifying requisite architecture and gaps
4. Creating an organizational plan integrating data ownership, IT infrastructure and analytics with business unit needs
5. Deploying any necessary hardware and software
6. Providing management services, as needed
BIG DATA INFRASTRUCTURE BRIEF
1. www.EMC.com/BigData© 2014 EMC Corporation. All rights reserved. © 2014, World Wide Technology. All rights reserved.
World Wide Technology, Inc.60 Weldon ParkwaySt. Louis, MO 63043
800.432.7008www.wwt.com
BIG DATA TECHNOLOGY OPTIMIZATION WORKSHOPThe WWT Big Data Technology Optimization Workshop is a two- to four-hour technical and strategic whiteboard session designed to increase your understanding of the hardware and software infrastructure associated with big data analytics. Experts examine the costs, benefits and differences between architectures, technologies, processes and tools by drilling down into big data technology use cases.
This workshop gives your organization the opportunity to gain a better understanding of how specific infrastructure, data management strategies and use cases impact a big data implementation.
Contact us at: [email protected] to schedule a Big Data Technology Optimization Workshop for your organization.
WWT can help bring the competitive advantages and benefits of big data to your organization in a way that supports your business goals.
We are here to talk about next steps and answer any questions.
EMC Scale-Out Storage for Big Data To achieve big data scale, organizations need an automated, scale-out storage platform that allows them to add capacity with minimal additional operational cost and achieve scalability, performance and throughput.
EMC® Isilon® is a scale-out platform that delivers storage for big data. Powered by the OneFS® operating system, Isilon nodes are clustered to create a high-performing, single pool of storage. As big data volumes increase, capacity can be added in minutes, while also gaining linear performance. With up to 80 percent storage utilization and more than one million IOPS, Isilon provides the scale and performance for big data requirements.1
Unifying storage and data management software and processes reduces the complexity of data ownership, enabling WWT solutions to adapt to changing business needs without interruption, and resulting in reduced total cost of ownership.
www.EMC.com/BigData
Learn MoreContact us at: [email protected] Learn more at: www.wwt.com
Download our comprehensive big data guide: Turning Big Data into Business Value: A Practical Guide to Big Data.