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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, and definitely 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 catchphrases as “data-driven” or “application-centric.”

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

Jay Baer

1. 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 software 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 information 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 concept of running a data centric business when it comes to software, tech, and hype, read my article, Being A Data Centric Business: It’s Going Beyond The Frenzy Of More Big Data And High Tech.

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

The term “data-driven” gets thrown around a lot, but let’s be real — it’s kind of moot these days. With every business already wired into computers and smartphones, relying on data isn’t optional; it’s just how things work now. The real challenge isn’t about having data, but about how we use data.

a. A Data-Driven Approach Creates Data Overload and Data Silos.

The real problem with a “data driven” only approach is that the data can easily overwhelm a business, resulting in unintended consequences. In particular, a “data-driven” mentality creates data silos and multiple copies of data. As a result, business becomes more rigid and complicated. 

b. Data as a Business Asset, Not a By-Product.

At best, a “data driven” approach enhances decision-making and typically outshines impromptu strategies such as “flying by the seat of your pants”. On the other hand, 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. Indeed, 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.

c. Data Centric Vs Data Driven Architecture Definitions

Next, let’s look at how a business’ Data architecture is different depending on their perspective: data-driven or data-centric. The following definitions clarify this distinctions.

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.

Indeed, these two data architecture definitions draw out the difference between “data centric” and “data driven”. Moreover, it drives home the point: our data is a most valuable business asset that you do not constrain within legacy or enterprise software. For a more detailed discussion on the differences between data-centric versus data-driven architectures, see 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.

“We live in a world where there is more and more information, and less and less meaning.”

Jean Baudrillard

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

In the latter half of the 20th century, a software boom significantly increased business efficiency. Indeed, enterprise software, particularly within supply chains, automated numerous processes and streamlined operations, enhancing service delivery. Today, businesses continue to adopt this software application-centric approach as the preferred solution for innovation and competitiveness. Concurrently, these same systems generate vast amounts of data. However, most of this software continues to treat data as a by-product, used once and then forgotten. This is the problem with an application-centric approach—it regards data as a by-product rather than a strategic and enduring business asset.

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

Enterprise systems do what they are designed to do. Namely, they are a system of record for processing business transactions. Within their functional silos, these systems are not designed for generating innovative insights, nor automatically prescribing how to adapt to new business conditions. Thus, when attempting to draw insights from these systems’ data by-products, especially multiple systems, it is like a data wasteland. Worse for day-to-day decision-making, the result is information overload. To top it off, these software applications become obsolete fairly quickly, hobbling businesses and locking up their data. As a result, businesses are no longer competitive. For more details, see my article, Agile Supply Chain Decision-Making: First You Need to Know The Truth About Enterprise Software.

b. 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 that businesses have tons of data, much of it relevant, locked in outdated transactional 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 and tips for adopting a data centric approach in your business. Also, if you are convinced that a data-centric approach is the way to go, see my article, A Data-Centric Business Strategy Checklist: The Way To Energize A Digital Enterprise To Be More Agile, Bold, And Simplified to get started.

A Data-Centric Business Strategy Checklist: The Way To Energize A Digital Enterprise To Be More Agile, Bold, And Simplified.

Many modern organizations are overwhelmed by data that yields few insights. This is because their business data is often disjointed, duplicated, ambiguous, inaccurate, and incomplete. However, more innovative companies are starting to make a critical shift to bring order to this data mess.

So, how can executives transform their organization into a data-centric business? Click here and I’ll provide you a data-centric business strategy checklist to assist with leading your organization’s shift to datacentricity. First, I’ll stress the need and compelling benefits as reasons for corporate leadership to commit to data centricity. Then, I’ll detail the critical executive-level tasks required for success. This includes establishing enterprise-wide data-centric criteria for IT projects and driving consensus on key business terminology. This checklist will also provide tips for executive to keep a data centric strategy on track to better manage an organization’s data. Finally, I’ll provide tips on how executives can prioritize IT projects to swiftly realize the benefits of data centricity.

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