Apache Hadoop is 100% open source, and pioneered a
fundamentally new way of storing and processing data. Instead of relying on
expensive, proprietary hardware and different systems to store and process
data, Hadoop enables distributed parallel processing of huge amounts of data
across inexpensive, industry-standard servers that both store and process the
data, and can scale without limits. With Hadoop, no data is too big. And in
today’s hyper-connected world where more and more data is being created every
day, Hadoop’s breakthrough advantages mean that businesses and organizations
can now find value in data that was recently considered useless. One of the
cost advantages of Hadoop is that because it relies in an internally redundant
data structure and is deployed on industry standard servers rather than
expensive specialized data storage systems, you can afford to store data not
previously viable. And we all know that once data is on tape, it’s essentially
the same as if it had been deleted - accessible only in extreme circumstances.
Since last decade, companies have been struggling to
figure out how to deal with all of the new data that is streaming in all around
them. From smartphones to production line sensors, everything is generating
data. Apache Hadoop has become the go-to solution for storing and
processing big data, and it provides a distinct competitive advantage for
organizations across industries in several key functional areas, including
security and risk management, marketing optimization, operational intelligence,
the enterprise data hub, and the Internet of Things. Let’s take a closer look
at these core functions that benefit from Hadoop enterprise solutions.
Data
Velocity, Data Security and Risk Management
As Data fraud, velocity and professional security breaches
are becoming more frequent and typical and old fashioned security solutions
just not up to the challenge of reliably protecting your company assets.
Hadoop, can help your organization analyze large amounts and different types of
data in real time, secure the speed of threat analysis, and improve
ability to assess risk by using great machine learning models. As an
example, Solutionary, a leading Managed Security Service Provider (MSSP), took
their security solutions to the next level by implementing the Cisco UCS Common
Platform Architecture (CPA) for Big Data with MapR. This joint solution made it
possible for Solutionary to perform real-time analysis on big data in order to
help protect and defend against sophisticated, and organized adversaries.
Operational
Intelligence
If we want to remain competitive, we should look
forward for ways to benefit our organization’s productivity and profitability.
But even when it seems that our operations have been properly analyzed and
optimized, we still can make subtle changes in operating environments in
order to realize even greater improvement. By taking a wide variety of granular
measurements from sensors, you can track patterns in operations to find new
ways to optimize your organization. Cisco provides infrastructure and analytics
to support Hadoop distributions such as MapR, and this type of joint solution
can give you the ability to evaluate data at the speed your business demands.
Sales
and Business Marketing Optimization
Current growth of social media channels which customers are
using can make it seem like you’re drowning in data in an effort to better
understand your customers. Hadoop can be used to cost-effectively integrate and
analyze your disparate data in order to gain richer customer insights, develop
personalized real-time customer relationships, and increase revenue.
Specific uses cases in sales and business marketing
optimization include data analysis, audio/video advertising optimization,
recommendation engine and targeting, social media analysis, and round the clock
customer view. As an example many data analytics’ and business intelligence
company, provides consumer insights, retail measurement, product libraries,
analytics reporting, and consulting services for retail and manufacturing
clients
Data
Enterprise Hub
Hadoop can be used as a cost-effective data enterprise hub
(DEH) to store, transform, cleanse, filter, analyze and gain new value from all
kinds of data. Building a successful DEH starts with selecting the right
technology in three key areas: infrastructure, a foundational system to drive
DEH applications, and the data processing platform. For example, the Cisco
Unified Computing System™ (Cisco UCS®) Integrated Infrastructure for Big Data
can be used to reliably run your EDH. This solution delivers a highly scalable
platform that is proven for enterprise applications, and can be deployed with a
Hadoop distribution such as MapR, which is especially well-suited to take
advantage of the compute and I/O bandwidth of Cisco UCS.Specific use cases in
the EDH area include collecting raw data in a data lake, data refining, big
data exploration, data warehouse optimization, and mainframe optimization.
Internet
of Things
The four main areas of uses cases for the Internet of Things
include personal IoT (smartphones, fitness devices), group IoT (family in a
smart house, tourist group), community IoT (smart cities and roads), and
industrial IoT (smart factories, retailer supply chains). The partnership
between Cisco and MapR provides you with an infrastructure that can readily
handle the massive amounts of real-time big data from the Internet of Things.
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