Big Data Predictions for 2015

©2014, Pentaho. All Rights Reserved
2015 Big Data Predictions|learn more at blogs.pentaho.com
Quentin Gallivan
CEO, Pentaho
Big Data Predictions for 2015
POWER TO THE
PEOPLE
Read more at blog.pentaho.com

Quentin Gallivan
Last year I speculated that the big data ‘power curve’ in 2014 would be shaped by
business demands for data blending. Customers presenting at our debut PentahoWorld
conference last October, from Paytronix, to RichRelevance, to NASDAQ, certainly proved
my speculations to be true. Businesses like these are examples of how increasingly large
and varied data sets can be used to deliver high and sustainable ROI. In fact, Ventana
Research recently confirmed that 22 percent of organizations now use upwards of 20
data sources, and 19 percent use between 11 – 20 data sources.*
Moving into 2015, and fired up by their initial big data bounties, businesses will seek
even more power to explore data freely, structure their own data blends, and gain
profitable insights faster. They know “there’s gold in them hills” and they want to mine for
even more!
With that said, the following are my big data predictions for 2015.
*Ventana Research, Big Data Integration Report, Tony Cosentino and Mark Smith, May 2014.

The digital universe is exploding at a rate that even Carl
Sagan might struggle to articulate. Analysts believe it’s
doubling every year, but with the unstructured
component doubling every three months. By 2025, IDC
estimates that 40 percent of the digital universe will be
generated by machine data and devices, while
unstructured data is getting all the headlines.*
The ROI business use cases we’ve seen require the
blending of unstructured data with more traditional,
relational, data. For example, one of the most common
use cases we are helping companies create is a 360
view of their customers. The de facto reference
architecture involves the blending of relational/
transactional data detailing what the customer has
bought, with unstructured weblog and clickstream data
highlighting customer behavior patterns around what
they might buy in the future. This blended data set is
further mashed up with social media data describing
sentiment around the company’s products and
customer demographics. This “Big Blend” is fed into
recommendation platforms to drive higher conversion
rates, increase sales, and improve customer
engagement.
The “blended data” approach is fundamental to other
popular big data use cases like Internet of Things,
security and intelligence applications, supply chain
management and regulatory and compliance demands
in Financial Services, Healthcare and Telco industries.
Big Data Meets
The Big Blender
* IDC, The Digital Universe of Opportunities: Rich Data and the Increasing
Value of the Internet of Things, Gantz, Minton, Turner, Reinsel, Turner, April
2014.
1

Internet of Things
Will Fuel the New
‘Industrial Internet’
Early big data adoption drove the birth of new
business models at companies like our customers
Beachmint and Paytronix.
In 2015, I’m convinced that we’ll see big data starting
to transform traditional industrial businesses by
delivering operational, strategic and competitive
advantage. Germany is running an ambitious Industry
4.0 project to create “Smart Factories” that are
flexible, resource efficient, ergonomic and integrated
with customers and business partners.
The machine data generated from sensors and
devices, are fueling key opportunities like Smart
Homes, Smart Cities, and Smart Medicine, which all
require big data analytics. Much like the ‘Industrial
Internet’ movement in the U.S., Industry 4.0 is is being
defined by the Internet of Things. According to
Wikibon, the value of efficiency from machine data
could reach close to $1.3 trillion dollars and will drive
$514B in IT spend by 2020.* The bottlenecks are
challenges related to data security and governance,
data silos, and systems integration.
* Wikibon, Defining and Sizing the Industrial Internet, David Floyer,
June 2013.
2

As companies with huge data volumes seek to
operate in more elastic environments, we’re
starting to see some running all, or part of, their big
data infrastructures in the cloud. This says to me
that the cloud is now “IT approved” as a safe,
secure, and ﬂexible data host.
At PentahoWorld, I told a story about a “big data-
throw down” that occurred during our Strategic
Advisory Board meeting. At one point in the
meeting, two enterprise customers in highly
regulated industries started one-upping each other
about how much data they stored in Amazon
Redshift Cloud. One shared that they processed
and analyzed 5-7 billion records daily.
The next shared that they stored a half petabyte of
new data every day and on top of that, they had to
hold the data for seven years while still making it
available for quick analysis. Both of these
customers are held to the highest standards for
data governance and compliance – regardless of
who won, the forecast for their big data
environments is the cloud!
Big Data Gets
Cloudy
3

Embedded
Analytics is the
New BI
Although “classic BI,” which involves a business analyst
looking at data with a separate tool outside the flow of
the business application, will be around for a while, a
new wave is rising in which business users increasingly
consume analytics embedded within applications to
drive faster, smarter decisions.
Gartner’s latest research estimates that more than half
the enterprises that use BI now use embedded
analytics.* Whether it’s a RichRelevance data scientist
building a predictive algorithm for a recommendation
engine, or a marketing director accessing Marketo to
consume analytics related to lead scoring or campaign
effectiveness, the way our customers are deploying
Pentaho leave me with no doubt that this prediction will
bear out.
As classic BI matured, we witnessed a final “tsunami” in
which data visualization and self-service inspired
business people to imagine the potential for advanced
analytics. Users could finally see all their data – warts
and all – and also start to experiment with rudimentary
blending techniques. Self-service and data visualization
prepared the market for what I firmly expect to be the
most significant analytics trend in 2015.
* Gartner, Use Embedded Analytics to Extend the Reach and Benefits of
Business Analytics, Daniel Yuen, October 3, 2014.
4

Data Refineries
Give Real Power to
the People
The big data stakes are higher than ever before. No
longer just about quantifying ‘virtual’ assets like
sentiment and preference, analytics are starting to
inform how we manage physical assets like
inventory, machines and energy. This means
companies must turn their focus to the traditional
ETL processes that result in safe, clean and
trustworthy data. However, for the types of ROI use
cases we’re talking about today, this traditional IT
process needs to be made fast, easy, highly scalable,
cloud-friendly and accessible to business. And this
has been a stumbling block – until now.
Enter Pentaho’s Streamlined Data Refinery, a market-
disrupting innovation that effectively brings the
power of governed data delivery to “the people,”
unlocking big data’s full operational potential. I’m
tremendously excited about 2015 and the journey
we’re on with both customers and partners.
You’re going to hear a lot more about the
Streamlined Data Refinery in 2015 – and that’s a
prediction I can guarantee will come true!
5

Finally, as I promised at PentahoWorld in October,
we’re only going to succeed when you tell us you’ve
delivered an ROI for your business. Let’s go forth
and prosper together in 2015!
 Quentin Gallivan
 Chief Executive Oﬃcer
 Pentaho

Big Data Predictions for 2015

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