The New Data Dynamics How to turn data into a competitive advantage

The New
Data Dynamics
How to turn data into
competitive advantage

An opportunity
wrapped in a crisis
If you haven’t noticed something rather
big happening to your business – in fact to
every business, department, and discipline
– welcome back from Mars.
The megatrends of the day, from cloud and
social data to mobile and the Internet of Things,
are all really justsparkly facets of a much bigger
and more profound trend.
The datascape in which your business
lives is changing dramatically.
This eBook is about these changes, what
they mean for your business, and what
you should be doing right now to rise to
the new challenges.
• It’s about recognizing and managing
data as a strategic business asset.
• It’s about moving from a purely
app-centric view to a data-centric
and app-aware perspective.
• It’s about the new principles for
every business or line-of-business
that wants to harness the awesome
power of data.
• And it’s about what will happen
to businesses that ignore these
imperatives.
We call this set of challenges and
strategies the New Data Dynamics,
and we’re convinced it’s the single
most important thing any enterprise
can address right now.
If you’ve got apparently more pressing
things in the center of your boardroom
table, shove them aside. This is bigger.
Informatica The New DataDynamics

Data has
changed
for good
Data has always been
important to business.
So why the big change?
Here’s why:
There’s far more data to collect
and consider.
Think yottabytes, not megabytes.
It’s coming in from all directions.
Not five sources, five thousand. That
means if it’s structured at all (most isn’t),
it’s multi-structured.
A lot of it doesn’t even look like data.
It looks like text or images or thumbs-ups
or tweets…
It doesn’t only live in nice warehouses.
It lives in apps, cloud stores, distant servers,
and email attachments.
It’s alive.
Data from sensors, transaction systems,
and social media channels doesn’t stand
still. It streams.
It’s dark.
A huge amount of it is buried deep in your
organization – hidden from view and out
of the reach of your analytics.
It’s inter-related.
This isn’t a random sample of the
universe: it’s all related to your business
and your customers. Multiply that
complexity.
It’s free-range.
It can’t just be owned by any single
application. It needs to flow freely to
wherever you need the insight.
That’s a lot of change. In fact:
Even if only one or two of these trends
were big enough to worry about (they all
are), your current data stacks, strategies,
and infrastructures will put you at a
serious disadvantage.
And you don’t want that.

App-centric
blinders
The changes demanded by the new
age of data amountto more than
a new set ofprocesses or technologies.
They call for a new mindset.
That means letting go of a fundamental
perspective that every enterprise shares:
the app-centric perspective.

What app-centric
means
Since the dawn of IT, applications have
been the way that people automate their key
business processes. Applications are where
the data is created, accessed, managed,
analyzed, and manipulated.
As packaged applications matured, they
created their own centers of gravity – as if
the application itself was the end instead of
the means to better business performance
and understanding.
In fact, most business professionals don’t
think ‘data’; they think CRM, ERP,
ecommerce, supply chain management,
and business intelligence.
So it’s natural that people and businesses
still take this application-centric view into
the new age of data. Natural but far
from ideal…

Why app-centric
is limiting
An app-centric perspective is limiting
because an application is a silo.
It may be integrated with other apps, but
it’s still a silo for data. It owns and controls
the data it needs to perform its function.
Most importantly:
The app decides how its data is
structured – and will always optimize
for its own needs.
That means its data structure won’t
be designed for easy connectivity or
integration with other applications.
In a world where you only needed
to worry about a few apps and data
sources, this was a hassle. In the new
age of data, it’s crippling.

Apples, meet oranges
A handy table to underline what data-centricity
really means:
Again, you don’t want to attack the
challenges represented by the right-hand
column with the tools and tactics optimized
for the left.
Old world of data
Structured
Batch
Limited # of sources
Low data volumes
Data at rest
SQL
App-centric
Transaction-focused
Enterprise-only
Known skills
IT vs. business
On-premise
Departmental silos
New age of data
All data
Streaming
Infinite # of sources
Big data
Data in motion
SQL + NoSQL/ Hadoop/ HiveQL
Data-centric and app-informed
Interaction-focused
Data from inside and outside
New skill sets
Interdependent IT business
Hybrid (on-premise and cloud)
Whole enterprise

What
data-centric
means
For data to become the strategic business
asset that it must be, it has to be liberated
from the application silos. Not divorced
from them but abstracted from them.
When this happens, data can
be structured and optimized for many
different uses, not just for one application
and business process.
That means it’s accessible, usable and
independent of the platform, application,
or device that created it – and that
integrations, provisioning, security, data
quality, and management are handled
intelligently and systematically, across
all applications and use cases.
With this approach, data is ready to fuel
everything your business does, from strategy
and performance monitoring to how you
build products and interact with customers.

The data-centric
dividend
A data-centric view means your
data is ready for anything.
Ready to be deployed where
the business most needs it.
Ready to be integrated into
new applications.
Ready to be combined with other
data sources.
Ready to be pumped into new analytics,
visualizations, and intelligence tools.
Importantly, this switch is not at the
expense of the app-centric view.
You can still look at and optimize any
data set in the context of an application.
But now you can multiply the value of that
data by ensuring it’s prepared for a much
wider role in your business.
That’s the power of a data-centric
perspective.

Death to structure?
Not quite
The new, unstructured, Hadoop-y world
where data is available for every need
will not happen overnight.
In fact, even though only about 20%
of enterprise data is structured today,
it’s an important 20%.
The real world is a hybrid world, where SQL
and No-SQL co-exist – and it will probably
be that way for the next decade.
The new age of data is here.
And it incorporates the old.
The difference now is that, instead of
the data moving to the apps, the apps
move to the data.

The New
Data Dynamics
New Data Dynamics
describes the essentials
of this new approach
to data. It makes it easier
for your business to do
five important things:
Access and prepare data.
Discover important data sources, capture
the data, and make it ready for insight.
Ensure data quality.
Establishing that strategists can create
a single, high-fidelity version of truth for
each critical data dimension: customers,
products, suppliers, sites, assets…
Protect data.
Keeping sensitive data safe and
regulation-compliant, using techniques
such as data security, archiving, and
role-based data masking and redaction.
Enhance data.
Adding value by capturing the context of the
data (e.g., where it was shared, when, how,
and by whom), and its connections (how it
relates to other data sets), and augmenting
it with new data and metadata.
Provision data.
Getting the right data to the right people,
processes, or applications at the right time,
in the right format, in the easiest
way possible.
These are the new imperatives for every
enterprise – and New Data Dynamics
is the discipline that can get you there.

The10principles
of theNew Data
Dynamics
What does the
New Data Dynamics
look like? Like this:
Embrace volume.
One of the premises of Big Data
is to go for the full fire hose rather
than use the sampling techniques
designed to make data
manageable. With new data
technologies, you may not need
to sample. Go for it all.
Capture relationships.
No data point is an island.
Uncover and capture the
relationships between your
data sets so you can see where
the connections are and the
underlying dynamics of
your business.
Test before rolling out.
Data flows and integrations
are far too important to put into
production without thorough
testing and test data management,
in an environment as close
to identical as your production
environment.
Prepare once, consume
anywhere.
The data-centric view means
you do most of the data
preparation once, centrally,
so you can then deploy the data
where it’s most needed.
Measure quality.
Data quality and hygiene
can only be managed if they’re
measured. Assign responsibility,
define your metrics, and track
and report on them regularly, as
if the data were a piece of gold
on a manufacturing line.
Market your wins.
Data people tend to be modest.
That’s not so good if you need to
win more resources to fund your
journey to the New Data Dynamics.
Capture your wins and let key
stakeholders know.
Automate data management.
Manual processes are too slow
– and data skills are too rare – for
the New Data Dynamics. You need
the tools and technologies
to automate as many processes as
possible, from ingestion to tagging
to structuring and provisioning.
Secure smartly.
Know where your sensitive data
is and make sure it gets the same
level of protection and safeguards
no matter where it goes – from
production to test, from on-premise
to the cloud, from Minnesota
to Mumbai. for it all.
Enable self-service.
If IT needs to get heavily involved
every time a business strategist
needs to prepare and provision
some data, nothing will ever
happen. Think about self-service
models and tools that let
non-technical users do it
themselves (and iterate freely).
Standardize and document.
Create golden masters of your
most critical data dimensions (such
as customers) and populate all key
systems with it. Then capture and
manage critical business definitions
and concepts in a published glossary
so everyone is working from the
same hymn sheet.

The benefits of the
New Data Dynamics
The New Data Dynamics isn’t an abstract
concept for data purists. It’s a practical,
hard-nosed discipline that rises to the
challenges of the new age of data, so
everyone in your business can:
Ask better questions.
Including many you could never ask before.
Get faster, more accurate answers.
So you can make better decisions.
Improve any and all processes.
Driving down costs and improving
efficiencies.
Delight customers.
Because you understand them better
– and treat them accordingly.
Reduce the cost of compliance.
While tightening up your controls
and reporting.
Those aren’t small benefits, they’re huge
ones. (And they’re only a sample.)

Getting there
The New
Data Dynamics
maturity model
The journey to the
New Data Dynamics can
and should be managed
and systematic.
We’ve developed a Maturity Model to show
the clearest steps and help you establish
where you are today.
It would take a whole new eBook in itself
to take you through the model (watch this
space), but here’s a peek:
Data Resource Planning
Intelligent Data Platform
Data as a Service
Self-Service
Data Provisioning
Intelligent Data
Preparation
Industry-Specific
Data-Fueled
Applications
(e.g., Internet
of Things)
Data Integration
Data Quality
(Master,
Transactional, Test)
Data Security
Data Migration
Data Tiering
and Archiving
Virtual and
Physical
Consolidation
(DIH)
Analyze, Assess,
Recommend
Metadata
Augmentation
Data Rationalization
Data
Catalogue
Metadata
Manager
Business
Glossary
Data Inventory
Management
Data Portfolio
Management
Data Services
‘As a Service’
Data-Centric
Applications
As a Service
Data Economic
Realization
Data-Driven
Applications
Data Resource
Utilization

Conclusion
Data mattersnow
more than ever
The new age of data may well be
one of the biggest inflection points
in business history.
Trying to master the New Data Dynamics
using yesterday’s data strategies,
processes, and technologies is the fast
track to irrelevance.
But if you get it right, using the principles
outlined here, you’ll gain a serious
advantage in the most important areas
of your business.
One thing is clear: No discipline or
department can afford to sit this one out.
But you weren’t planning to sit it out
anyway, were you?

Further
reading
Liked this?
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The Informatica
Advantage
Informatica helps organizations
derive measurable business value
from complete, accurate views
of business-critical data – about
customers, products, suppliers, and
contexts – and the relationships
between them.
We’re leaders in critical disciplines
including Data Quality, Master Data
Management, Data Security, ...
and the New Data Dynamics.
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The New Data Dynamics How to turn data into a competitive advantage

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