DATA ACCELERATION:
HOW TO ENABLE ENTERPRISE
INSIGHTS FROM BIG DATA
Done well, a modern data supply chain allows
organizations to leverage more data sources
and enhance data discovery more quickly.
CHALLENGES
Data acceleration helps organizations address three challenges:
MOVEMENT
PROCESSING
how to move data swiftly from
its source to places in the
organization where it is needed
how to process it to gain
actionable insights as quickly as
possible
INTERACTIVITY
how to foster faster responses to
queries submitted by users or
applications—referred to as
interactivity
Each component can address data movement, processing, and/or interactivity,
and each has distinctive technology features.
WHY ACCELERATE DATA?
Supports faster processing
by leveraging advances in
hardware and software for
computer clusters, enabling
them to operate more
efficiently than ever.
Reduces user wait time,
speeding the ability to gain the
insights required to make the
business decision facing them and to
satisfy their clients’ expectations.
Supports faster interactivity
by enabling users and applications to connect to the data
infrastructure in universally acceptable ways and by ensuring
that query results are delivered as quickly as required.
CHOOSING YOUR ARCHITECTURAL COMPONENTS
Organizations can choose from many different data technology components
to build the architecture needed to support data acceleration.
COMPLEX EVENT
PROCESSING
Distributed computing
In-memory
Streaming
BIG DATA
PLATFORMS
Distributed computing
In-memory
Streaming
Optimized network
INGESTION
Distributed computing
In-memory
Streaming
APPLIANCES
Distributed computing
In-memory
Optimized network
Custom silicon
IN-MEMORY
DATABASES
ARCHITECTURAL
COMPONENTS AND THEIR
TECHNOLOGY FEATURES
Distributed computing
In-memory
CACHE
CLUSTERS
In-memory
By exploring the various potential architecture configurations,
executives can initiate valuable discussion about which configurations
may be best for their organization’s needs.
TAKING IT STEP BY STEP
1
2
3
INVENTORY
YOUR DATA
IDENTIFY
INEFFICIENT
PROCESSES
IDENTIFY
DATA SILOS
4
5
6
CONSIDER
SIMPLIFY
PRIORITIZE
DATA ACCESS INDIVIDUAL DATA EXTERNAL
SUPPLY CHAINS DATA SOURCES
CONCLUSION
Big Data brings big challenges and to surmount them, organizations need
to establish a data supply chain that accelerates data movement, processing,
and interactivity—enabling decision makers to more swiftly discover
and act on insights from their data.
Copyright © 2014 Accenture
All rights reserved.
Accenture, its logo, and
High Performance Delivered
are trademarks of Accenture.
Accenture Analytics’ Big Data and Accenture Technology Labs teams
examined data challenges and architectural components available to
address them—by creating a modern data supply chain.
For more information about Data Acceleration,
visit accenture.com/dataacceleration