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You Need To Think Data Centric To Be A Successful Business: Stop Being Data Driven, Application Centric

Many businesses find themselves drowning in data yet left thirsting for genuine insights. Despite being tech-savvy and frequently working with data, business leaders still struggle to fully harness this wealth of information. Indeed, their data is stuck in data silos, duplicated, jammed into different formats and of such terrible quality that it’s virtually unusable or untrustworthy. A change of approach is required. Businesses need to pivot towards a data centric approach as opposed to merely being data-driven or focused on applications. In this article, I’ll explain the concept of a “data-centric” mindset – clarifying what it encompasses and what it doesn’t, while also contrasting it with such notions as “data-driven” or “application-centric.”

“We are surrounded by data, but starved for insights.”

Jay Baer

What Is A Data-Centric Business?

a data centric business

A data-centric business begins with a corporate mindset that values data as a crucial asset, not just a by-product of enterprise systems. Indeed, data ranks as your most important business asset because you can draw on it continually for sharper insights and better decision-making. Now, if a company centers only on applications, it won’t realize these benefits. The encouraging news is that adopting a “data centric” outlook is possible today without extra software or technology investments. By adopting this mindset, you can start to transform your business processes immediately. And before long, your company will mature into a data-centric enterprise.

But, before we start talking about the benefits of data centric, let’s start with a data centric definition. And then we can discuss what data centric is and is not.

Data Centric Definition

“Data centric refers to an architecture where data is the primary and permanent asset, and applications come and go.  In the data centric architecture, the data model precedes the implementation of any given application and will be around and valid long after it is gone.”

TDAN, The Data-Centric Revolution: Data-Centric vs. Data-Driven

I like this definition. It defines data as the primary component of business technology. Specifically, this definition tells us that technology, software applications, and automation will come and go. Conversely, our business data will never grow obsolete. Indeed, data is a permanent business asset that businesses do not need to constrain within any particular technology or software application. For a more detailed look at the challenges of dealing with data overload and the concept of running a data centric business, read my article, Being A Data Centric Business: It’s Going Beyond The Frenzy Of More Big Data And High Tech.

A Data Driven Business Is Not A Data Centric Business – Here’s Why.

The term “data-driven” is commonplace, yet distinct from being data-centric. Data-driven approaches underscore the importance of data in decision-making processes, acting as a departure from relying solely on intuition. Consider the complex web of a large global supply chain. In such scenarios, decisions are informed by robust data collected on products, suppliers, transportation carriers, ports, and regulatory agencies. This reliance on data ensures that choices are grounded in reality and tangible evidence, not guesswork.

“… a ‘data-driven’ mentality does not prevent data silos, multiple copies of data, make your business more agile, or simplifies businesses”

The problem with a “data driven” only approach is it can easily overwhelm a business with data. And, this can result in unintended consequences. In particular, a “data-driven” mentality does not prevent data silos, multiple copies of data, make your business more agile, or simplifies businesses. 

At best, a “data driven” approach enhances decision-making and typically outshines impromptu strategies such as “flying by the seat of your pants”. Adopting a “data centric” methodology elevates data to the rank of a critical business asset, characterized by permanence, value, and adaptability. Data, in this perspective, doesn’t emerge as an incidental byproduct or as something produced solely for specific software applications. By embracing a data centric strategy, you ensure that your data remains free from the constraints of outdated software applications, allowing you to harness its full potential. The following definitions clarify the distinctions between data centric and data driven architectures.

Data Centric Vs Data Driven Architecture Definitions

Data centric architecture refers to a system in which data is the primary and permanent asset, whereas applications change.

Data-driven architecture means the creation of technologies, skills, and an environment for ingesting a large amount of data.

To sum it up, I like these two definitions as they draw out the difference between “data centric” and “data driven”. Your data is a most valuable business asset that you do not constrain within legacy software. These definitions come from Neptune.AI blog posting, Data-Centric Approach vs Model-Centric Approach in Machine Learning. Even though this article is focused on AI, it applies to any software or technology that uses data.

A Business Cannot Be Both Application Centric And Data Centric – Here’s Why.

In the last half of the 20th century there was a software boom that enabled businesses to increase their efficiency. Especially enterprise software such as those used in supply chains enabled businesses to automate many business processes. Additionally, business software applications streamlined operations, and improved service delivery in terms of timeliness. Of course, at the same time these systems started generating a lot of business data. Indeed, the challenge was, and still is, that an application-centric treats data as a by-product instead of a strategic, permanent business asset.

“There were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every two days.”

Eric Schmidt

1. Application Centric Data Is At Best The Output, At The Worst A By-Product.

The problem, or perhaps an opportunity, was that these applications left a wasteland of data. Initially, the data was small and just a by-product of these software applications. The problem is that after many decades, or even months for recent business startups, companies are now swimming in data. Furthermore, some of this data is good and some is not so good.  Now, the opportunity of having all this data is evident, but the opportunity is limited when the data is just part of a standalone software application. Worse, these software applications become obsolete fairly quickly, locking businesses and their data into a situation where they are no longer competitive. 

2. You Can’t Be Both Application Centric And Data Centric.

In summary, many companies today employ an “application-centric” business strategy. Although data marts and Business Intelligence (BI) reporting tools offer assistance, they merely serve as a temporary solution to a larger issue. That issue is having tons of data, some of which is relevant, locked in outdated software systems. Consequently, many businesses struggle to access their data, which limits them from innovating, both operationally and technically, which is crucial for maintaining competitiveness and relevance.

“You can have all of the fancy tools, but if [your] data quality is not good, you’re nowhere.”

Veda Bawo

Now that you have a better understanding of data centric and what it is not, see my article, A Data Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation, for a more detailed discussion of the benefits of a data centric business.

A Data Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation. Is your business struggling to manage the flood of data available in today’s competitive world? Data silos, information duplication, and inaccuracies only complicate the matter further. However, a data centric approach can help! By adopting this mindset, your organization can gain agility, establish a Single Source of Truth (SSOT), streamline automation processes, and reignite innovation.

Click here for the benefits of a data centric approach, how it differs from data-driven, and how to balance application-centric and data-centric approaches. It’s time to re-think your business’ data strategy!

For more articles from SC Tech Insights’, see postings on data.

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