“The world’s most valuable resource is no longer oil, but data,” claimed The Economist back in 2017. You’ve probably heard the short version (“Data is the new oil!”) at your last big data engineering conference or from leading data governance experts. Then there’s my favorite, which cuts to the chase: Data is “the currency of the 21st century,” as it best describes how companies now value strategic, business-critical, and personally sensitive data used for data intelligence.
What is data intelligence?
Many definitions exist, but I’ll offer one of the briefest from IDC: “Data intelligence leverages business, technical, relational and operational metadata to provide transparency of data profiles, classification, quality, location, lineage and context; Enabling people, processes and technology with trustworthy and reliable data.”
Simple, right? Yet, it’s hard to achieve. Let’s look at a few stats that underscore the data intelligence gaps that exist today:
- In 2019, we exceeded 1 billion knowledge workers
- By 2025, the amount of data will double every 12 hours!
- Only 27% say data and analytics projects produce insights and recommendations that are highly actionable
- Only 32% of companies can realize tangible and measurable value from data
Business value stems from data intelligence – not data alone
Much has been said on the value-creation opportunities an organization can achieve from data analytics to unlock new insights into customer experience, increase operational efficiencies, and unleash new products and services based on greater understanding of trends and untapped revenue. But, is this really the case?
Today, according to the Harvard Business Review, only 24% would rate their organization as data-driven, down from 38% prior to the pandemic.
Ouch! More than simply an oil analogy, data is constantly driving new opportunities to transform business as a renewable resource—but are we there yet? Nope. So, what’s needed to turn raw data into useful data intelligence to drive business value creation?
As clever as it sounds, using data as an analogy for oil is not focusing where the true value lies—much like oil converted into gas, data intelligence is the real fuel needed to accelerate past the competition and create value. No company gets credit for simply being the best data collector around—quite the opposite, it’s a risk and liability if data is not curated and used responsibly.
So, what’s the secret? The best data-driven organizations have learned how to build the best data refineries! And that means increasing data intelligence for knowledge workers through self-service data analytics, rather than being stuck, mired in the tar of unusable data lakes.
These market-leading organizations have several things in common—they’ve taken all that raw data, curated it to understand what’s useful within their data lakes, cataloged the data to make sense of it as fit for purpose, and democratized it across the organization to enable analytic insights from data intelligence. In essence, they’ve focused their data stewards on unleashing data intelligence—rather than figuring out data sources and how to tap them—to achieve actionable results based on metadata-driven insights.
Data intelligence enables a comprehensive data governance platform
Once again, Harvard Business Review sums up the pandemic and post-pandemic challenges that exist today: “92.2% of mainstream companies report that they continue to struggle with cultural challenges relating to organizational alignment, business processes, change management, communication, people skill sets, and resistance or lack of understanding to enable change.”
Here’s where the best companies differentiate: Data governance is the key to building a data-driven culture and increasing data literacy with data intelligence as their fuel. At Informatica, we know this firsthand through our customers who are emerging post-pandemic with a market-leading advantage, instead of struggling to still make sense of a data collection. .
They’re harnessing data intelligence with the building blocks of data mastering, data quality, data cataloging, data steward collaboration, and data security and privacy on a unified platform to build trust assurance in the data itself, then feeding that reliable data stream into self-service analytics to refine into data intelligence to transform business through a data marketplace.
Simply put, data intelligence maturity can be measured by the data governance maturity your organization can achieve today—how would you rate your data intelligence maturity?
Supercharging data governance with data intelligence in the cloud
Self-service analytics from your data marketplace, new streamlined cloud applications and services, consumer loyalty programs, business operational efficiency, and other revenue-generating and cost-saving applications are at the heart of what makes data intelligence one of today’s most critical IT spends for generating high ROI.
The pandemic has only increased the gap with those who’ve realized data as a business advantage by accelerating how data intelligence can be used—and where.
And, leading organizations today are taking data intelligence one step further by adopting cloud-hosted data governance solutions to realize a few meaningful advantages:
- Consumption-centric bias vs. provision-centric. Self-service consumption of trusted data requires data governance programs to be right-sized to applications and immediate organizational needs, accelerating time to value for results by minimizing provisioning that delays new value-creation initiatives. You need to spend less time spinning up infrastructure with new OpEx and CapEx, and more time generating data intelligence.
- Fully integrated and unified solutions
While on-premises data governance solutions can be offered as a platform with any number of components, by combining capabilities within a cloud-hosted solution with transparency to user experience, the line can be blurred between users and discrete applications to instead focus on end-to-end use cases that produce data intelligence for results, utilizing global data sets. Data governance can be abstracted to be more agile, flexible, and available to all who need reliable data to consume.
- Metadata-driven approach to data intelligence and automation
Similar to the previous point, data intelligence is more aligned to process manufacturing than to discrete outcomes, as data governance is a process that continually refines the “oil of data” into the “gasoline of data intelligence” that fuels the organization. A cloud-hosted solution underpinned by metadata management can better automate and accelerate results from data analytics applied at scale, increasing efficiency and achieving data insights faster and continuously.
The future of data intelligence in the cloud and beyond
If data is the new oil and data intelligence is the new gas to fuel your business transformation, market-leading companies will adopt and expand data governance programs as the path to leapfrog the competition, unleash data value and put data risks in the rearview mirror.
This means being able to stand up new data intelligence–driven applications quickly, taking advantage of cloud agility, elasticity and scale to right-size new programs. And doing so cost-effectively to democratize data use, so self-service analytics with trusted data can be available for all who need it.
If you’d like to further your data intelligence goals and accelerate your data governance program, empower your teams with trusted data to make better decisions, and create value for your organization with reliable data intelligence, check out the ebook, Six Strategic Steps to Democratizing Data now.