becoming data ready in the digital age
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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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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.
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