Becoming data ready in the digital age.

data ready.

Three imperatives for designing great data.

It’s the new Moore’s law.

2013 4.4 Zettabytes

2020 44 Zettabytes

Data is everywhere.The amount of data generated in the world today is doubling every two years.

Along with the explosion in volume, we’re also solidifying the way we’re using data:

We continue to focus on improving organizationproductivity

We’re using data to improve customer engagements and drive better business decisions — in real time

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2

Improving organizationproductivity

Traditionally, data generated by technology was simplya record we stored.

We would then analyze the records afterwards to tell us:

How much we sold

Which product is the best-seller

Which region is our best performer

And we did forecasts and even predictionsusing this historical data.And this capability remains important today.

Driving and optimizing decisions, engagements, and interactions in real time

Businesses want to respond to events and activities asthey happen to improvebusiness decisions and customer service.

Real-time actions are driving:

Operational and business decisions

Live interactions and recommendations

Instant alternatives and promotionsto customers

And data is the keyto all of this.

Business leaders view dataas a game-changer.

But not everyone is con�dent about using their data.

97% of C-level execs saydata is strategic1.

Only 15% of C-level execs believe they are as good or better than competitors at using data2.

Only 4% of businesses can extract full value from the information they hold3.

But while businesses are using data for competitive advantage, many business analysts are working with

data that is:

Delivered late:Data scientists can spend up to 80% of their time data wrangling before doing any meaningful analysis 4

Unsafe:Analysts may be dealing with sensitive customer data that has not been masked

Bad:Data is collected with a lack of data governanceIncomplete:Different business units maintaininconsistent data about the same customers

So why are so many organizationsfailing with data?

4 trends are to blame.

Trend #1Computing

Businesses are using more apps in the cloud.

An average enterprise uses 508

applications5.

Businesses are choosing best-of-breed applicationsover monolithic application suites.The continued pace of merger and acquisitions puts pressure on businesses to modernize their applications strategy.

The result?A data nightmare of trying to connect

applications together to supportbusiness processes.

Trend #2Data

Today, data is big, it’s less-structured, and includes all the different ways customers interact with you (think social media, instant messages, and sensor data).

Traditionally, we collected structured, well-formatted data (think transaction data).

A complex process is required tounderstand the data and to

make use of it.

The result?

Trend #3Analytics

? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?

Traditionally, we’ve focused on analyzing data post-event to determine how well processes performed.

Today, we want data to fuel predictions or prescriptions in real time.We want to provide a place for data scientists to experiment, and a way to quickly operationalize the insights they discover.

A complex—and speedy—process is required to bring all data together and to deliver it so business analysts can make

accurate decisions, fast.

The result?

Trend #4Data Security

Traditionally, data security was achieved by securing the perimeters ofapplications, devices, and data centers.Today, data needs to move all over and out of its original context.

The result?Sensitive data needs to be discoveredand classi�ed before it is moved and

then governed by policies and rules toensure compliance.

We know that we need to get great data to fuel our business. But traditional approaches make it too hard, take too long, and are not repeatable.

Each data problem is treated inisolation and traditional approaches just don’t work anymore.

Hand coding – takes too long and is not scalable

Rely on scarce developer staff – too expensive

Developers use “tool of choice” – great for developers; not for the company when they quit

A new approach is needed.

One that makes data management a core business capability—like every

other core business capability thatmakes your company unique.

One that enables you to delivergreat data—data that is clean, safe, and connected—to everyperson, application, or process

in a timely fashion.

Automated and repeatedly.

Anywhere. Anytime.

3 Considerations forDesigning Great Data

An enterprise data management architecture is the only way to deliver the right

data to any process, person, or application on a continuous basis.

#1

From siloed projects to enterprise data management

Get there by:

Optimizing using a true hybrid platform

Standardizing on common data management technologies and approaches

Modernizing your data management environment using the latest technologies

End the era of IT being the bottleneck. Let your data scientists and business

analysts access trusted and timely datathemselves by building self-service into

your data management architecture.

#2

Give users self service

Do this by giving them:

Easy ways to share reviews, ratings, and advicewith each other

If done right, you can still track what users are usingand creating, and monitor for data governance.

Easy-to-�nd reusable building blocks

Intelligent recommendations for further data re�nement and preparation

You’ll never know what the nextdata explosion brings.

Reduce technology adoption complexity

#3

Lower your learning and adoption curve by:

Deploying tools that enable you to reuse existing designswith minimal rework when you point it to a new database technology

Using a modern visual design and development approachthat abstracts developers from changes in the underlyingtechnology. Avoid hand-coding of all types

Deploying tools that intelligently manage and optimize how to access the data

Further readingWe've helped many companies create great data so they can dominate in their industries. And we've gathered some of the lessons learned in this eBook. Get your free copy tosee how businesses like yours learned to use data to leapfrog the competition.

Get your copy

AboutInformatica.We’re Informatica and we help the world's biggest enterprises build data infrastructures to power process ef�ciency and business insights. If you're looking to create a modern data architecture to take your business to the next level we should talk.

Let's talk.

Sources.1. Economist Intelligence Unit--The Data Directive.2. Economist Intelligence Unit--The Data Directive3. PWC, "Seizing the information advantage." September 2015.4. New York Times, "For big data scientists, 'janitor work' is key hurdle to insights," August 17, 2014.5. Forbes, "Latest Enterprise Application Use Survey Results." July 2014.