What is Data Intelligence?

A company achieving data intelligence

Data Intelligence is the ability to understand and use your data in the right way. It is the output or result of connecting the right data, insights and algorithms to allow all Data Citizens to optimize processes, increase efficiency and drive innovation. 

Why do you need Data Intelligence?

It is not a cute slogan or an abstract concept; it’s optimal, achievable, and hugely beneficial. In this operating environment — awash in massive data volumes, buffeted by a constant flow of new technologies that will deliver more data, under pressure from evolving compliance mandates, and always in pursuit of digital transformation — Data Intelligence is critical. 

However, this ideal state can only be realized when it’s fully understood. There isn’t a one-off tactic or resource allocation that will get it done. It certainly requires particular technologies to support enterprise-wide data collation and inter-departmental collaboration, but there’s more to it. It means creating policies and processes to allow authorized access to the right data, always with full transparency and context. It’s also important to develop metrics to ensure that the system is working, and changes can be made to adjust and enhance each step.  

This won’t happen overnight. With many enterprises today, data is locked away in disparate silos, which drains resources and clogs processes. Data Intelligence means changing that dynamic. It unlocks the value of in-house and incoming data and transforms it into a strategic and competitive asset.

Data Intelligence use cases

Data Intelligence helps organizations achieve three key use cases: grow the business, run the business, and protect the business. 

Grow the business

Growing the business is revenue focused. Data Intelligence helps organizations grow their businesses by enabling business analysts to find, access, understand and trust their data so they can use this data to make impactful business decisions. This leads to increased revenue via customer cross-sell, increased revenue via improved marketing campaigns and product launches, and improved net sales margins.

Run the business

Running the business is cost focused. Data Intelligence can help organizations reduce IT operations and maintenance costs, reduce duplicate data spend, and reduce business performance/reporting spend.  

Protect the business

Protecting the business is risk focused. Data intelligent products ensure an organization’s data is trustworthy and used in a compliant manner. This results in avoided regulatory fines and penalties, avoided data breaches, and increased productivity in compliance related legal activities. 

How to achieve Data Intelligence?

Achieving Data Intelligence is not easy. Organizations must first establish a governance foundation and then scale from there. They must think beyond the technology and look towards total digital transformation within their organization; they must look at the big picture. To do this, an organization needs to consider the following factors. 

  1. What’s often missing in these infrastructures is a foundation that offers full visibility across the entire data landscape. Many organizations have a heterogeneous mix of data management technologies that grew over time, and the fragmentation leads to a siloed network. A comprehensive, cloud-based platform can ensure enterprise security and scale up to meet specific standards for reliability, privacy and compliance. 
  2. It’s all about the purpose — the data should be secure and compliant, but it must also serve business needs. There should be a full complement of solutions that:
    • Automate governance and privacy
    • Extract the right data regardless of location
    • Apply a single definition to ensure that users are building on the same foundation
    • Prioritize consent, usage and retention policies
    • Rely on valid data transparency and lineage to deliver meaningful business intelligence
  3. Organizations must remember that technology is dynamic — there are always innovations coming down the pike, and it’s important to make judgments on each as they emerge. Artificial intelligence and machine learning alone will likely be integral to 75% of all enterprise applications by 2021, and all infrastructures must have the flexibility to integrate with the best of these.  
  4. But there’s an even more important variable here. Data Intelligence is a people and process issue; intelligence is a fundamentally human characteristic, and so we need policies and processes that drive knowledge sharing and collaboration.

So now what? 

There’s no golden rule here — every institution must evaluate its own philosophy and network settings to create a full-fledged data culture. To achieve Data Intelligence, the core mission is to make it easier for knowledge workers to find the data they need, learn from it, add to it and collaborate with it.

Data Intelligence doesn’t help only a few executives or particular disciplines; it’s all-encompassing and helps reimagine every function across the enterprise. It gives everyone the power to use data to solve problems, implement ideas and grow businesses. It fosters collaboration to drive business value. It enhances operational efficiency and identifies new revenue opportunities. Data Intelligence enables an organization to get the most out of their data by turning data into a competitive and strategic asset. This happens when data is seen not as an end in itself but a powerful weapon to deliver new insights and drive better decisions. Data Intelligence gets us there. 

Want to learn more about how to achieve Data Intelligence with Collibra?

Read the Collibra Data Intelligence Cloud e-book

Related resources

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12 Steps to Data Intelligence:
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12 steps to Data Intelligence:
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12 steps to Data Intelligence: Part 3

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12 steps to Data Intelligence: Part 4

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