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Big Data Just Beginning to Explode

The world of "big data" is changing dramatically right before our eyes – from the amount of data being produced to the way in which it’s structured and used. The trend of "big data growth" presents enormous challenges, but it also presents incredible business opportunities. Our big data growth interactive infographic below helps you visualize some of the latest trends. Please use the numbers to navigate through each of the three chapters.

The Rapid Growth of Global Data

The production of data is expanding at an astonishing pace. Experts now point to a 4300% increase in annual data generation by 2020. Drivers include the switch from analog to digital technologies and the rapid increase in data generation by individuals and corporations alike.

Size of Total Data

Enterprise Managed Data

Enterprise Created Data

DATA PRODUCTION Will be
44 TIMES greater
in 2020 than it was in 2009

More than 70% of the digital universe is generated by individuals. But enterprises have responsibility for the storage, protection and management of 80% of it.*

What is a ZETTABYTE?

1 gigabyte

1,000,000,000,000

1 terabyte

1,000,000,000,000

1 petabyte

1,000,000,000,000

1 exabyte

1,000,000,000,000

1 zettabyte

1,000,000,000,000

1 terabyte holds the equivalent of roughly 210 single-sided DVDs.

It took roughly 1 petabyte of local storage to render the 3D CGI effects in Avatar.

The current estimated information content of all human knowledge is only 12 exabytes.

What is a
Zettabyte?

Taking on the Explosion with Radical New Databases

The dramatic rise of unstructured data like photos, videos and social media has ushered in a new breed of non-relational databases that allow data to reveal its own structure and patterns. This shift is a revolutionary change after 40 years of dominance by relational databases – an eternity in the world of IT.

Structured

Unstructured

Newly Expanded Database Stack

Traditional Stack

DIRECT RECORD ACCESS OR QUERIES

What’s this? (Click for more)

Lets you retrieve data from various types of databases, then apply analysis or
transactional applications for making comparisons, tracking, sorting lists, etc.

MapReduce Programs

What’s this? (Click for more)

Provide a framework for processing highly distributable problems using clusters or
grids of computers.

high-performance traditional relational database

What’s this?
(Click for more)

Suitable for transaction processing and basic analysis applications due to advanced processing power, adaptability and wide acceptance
in marketplace.

noSQL
Database

What’s this?
(Click for more)

Developed for storing and performing real-time analytics on huge volumes of data that does not follow a fixed pattern. (NoSQL stands for 'no structured query language.')

Parallel
relational
database

What’s this?
(Click for more)

Used for analyzing large amounts of tabular structured data, as well as for processing real-time online transactions and creating rapid prototyping test beds for developing algorithms for
systems like Hadoop.

Hadoop
(MapReduce
engines)

What’s this?
(Click for more)

Useful in processing petabytes of unstructured
data by enabling
distributed applications
to work with thousands of
independent computers.

Monolithic Hardware

What’s this? (Click for more)

Combines architecturally disparate components in a single integrated circuit to allow multiple types of processing.

Distributed Hardware

What’s this? (Click for more)

Increases processing power by connecting many independent
computers via a high-performance network.

Connecting the data dots
to Make New Discoveries

As we make the important shift from collecting to connecting data, businesses are searching for relationships between data sets to reveal valuable new insights.
Click the industry buttons at right to see how some companies are finding insights for better business.

THIS NEW WORLD of DATA ANALYTICS IS
REVEALING INSIGHTS
IN LITERALLY EVERY FIELD IMAGINABLE

The evolution of the way we produce, process and analyze data is changing the world around us in fundamental ways. To learn more about how to prepare for what’s ahead, download our DATA rEVOLUTION white paper.


These new, unexpected patterns are helping businesses find new solutions to complex problems.

Case Study:

Finding Genomes

Using the leading open-source predictive analytics language to sort through 10 GB of data, a biotech company recently isolated 23 optimal genes, thereby creating the first gender-specific diagnostic tests for heart disease.

42,000 blood samples
50,000 genes each containing
1-2 million pieces of genetic data

23 Key Genes Isolated

Case Study:

GOING FULL THROTTLE

By combining search engine and analytical databases, Endeca helped Toyota sift through six years of data from numerous systems to identify patterns related to its gas pedal recall that it would not have known to look for.

50 million records analyzed
75 dimensions compared
800,000 hours in annual query processing savings

Case Study:

TRACKING CRIMINALS

Visual Analytics helps law enforcement find criminals by acquiring and visually analyzing data from disparate sources involving addresses, vehicles, phones, intercepts, criminal cases, suspicious activity and much more.

"Data integration is a critical step towards organization collaboration, with visualization bringing the essential ingredient for insight and awareness around relationships between organizations, data and processes."

- Chris Westphal, CEO,
Visual Analytics

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