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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? Or, worse, are your legacy applications restricting access to your data? This is a most difficult predicament for most businesses. 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. In this article, I’ll explain the 6 benefits of a data-centric approach, how it differs from data-driven and application-centric approaches. It’s time to re-think your business’ data strategy!

“Data is a precious thing and will last longer than the systems themselves.”

Tim Berners-Lee

Understanding Data Centric Business Technology And Processes.

In today’s business world, being technologically savvy is a must for most business managers. For example, most supply chain managers are no strangers to data-rich software such as:

  • Enterprise Software. For instance, ERP, TMS, and WMS.
  • Office Productivity Software. For example, MS Excel.
  • Business Intelligence (BI) Dashboards. Most managers know the value of data analytics and BI reports. Further, they can use them to guide important decisions.

However, using software like ERPs, MS Excel, and BI may be data-driven, but that does not make you data-centric. Indeed, being data centric is different. It is about treating your data as an asset rather than as a by-product of your enterprise systems or other software processes. 

“… using software like ERPs, MS Excel, and BI may be data-driven, but that does not make you data-centric.”

A key advantage of adopting a “data-centric” approach in business is the ability to start immediately. As time progresses, this mindset will usher in an automation transformation within your business that centers on data, not on software applications. However, before we explore the transformational benefits of being “data-centric” versus “application-centric,” it is essential to define what being data-centric truly means. By understanding this concept clearly, we can appreciate its merits and differentiate it from other business strategies.

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

“… data is a permanent business asset … not … constrained within any particular technology or software application.”

I like this definition because it defines data as a key permanent asset for businesses. Specifically, this definition tells us that technology, software applications, and automation will come and go, but our 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.

In this data-rich world, a data centric mindset is critical to stay competitive. Data is no longer just a product or by-product of software applications. Indeed, it is the most valuable business asset. It’s time for businesses to recognize that software and business methodologies come and go, but the data will always be there. For a more detail look at the challenges of dealing with data overload, the pitfalls of being software centric, and the concept of running a data centric business, see my article, Being A Data Centric Business: It’s Going Beyond The Frenzy Of More Big Data And High Tech.

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

Jay Baer

The 6 Benefits Of A Data-Centric Business.

Now that we have an idea what “data centric” means, what are the benefits of a business taking this approach? To detail, there are many benefits that I’ll describe below.

1. Superior Business Agility: Not Chained To Data Silos Or Legacy Applications.

data centric

For any business, being agile is crucial for staying competitive in a rapidly changing market. By being data-centric, businesses can quickly adapt to changes in customer behavior, market trends, and emerging technologies. Especially for enterprise-size businesses, they can more easily take advantage of new opportunities. Indeed, no longer will legacy systems constrain a business’ data. Further, data silos will not need to exist that businesses can only partially access. For example, a large “data-centric” retailer can easily analyze sales data generated by multiple systems and across multiple channels. This results in business leaders making informed decisions about inventory management and marketing strategies.

2. High Confidence In Data: There Is A Single Source Of Truth (SSOT) Vs Multiple Versions Or Copies.

Large businesses often have multiple departments or teams working with different sets of data. Having one single source of truth (SSOT) ensures that everyone is working with the same accurate information. For example, a large financial institution that is data-centric can ensure that all its employees are working with the same customer data, reducing the risk of errors and improving customer service.

Today, many businesses and their employees lack confidence in the data that resides in their particular system. Thus, many times the data is either copied or entered over and over again in different systems. Personally as a customer myself, I cannot tell you how many times I have had to re-enter or tell a business’ employee to re-enter my customer information into their business systems multiple times.

“Data that is loved tends to survive.”

Kurt Bollacker

3. Improved Decision-Making With High-Quality Data: Complete, Accurate, Timely.

Large businesses make decisions based on complex data sets that require careful analysis. If a business is data centric, business leaders will make better decisions because their data is complete, accurate, and timely. For example, a large healthcare provider that is data-centric can use patient data to identify patterns and trends in health outcomes and make informed decisions about treatment options. No more do employees have to work with partial data sets or out-of-date information. Moreover, decision-making is not just improved, but streamline. No longer do employees waste time coordinating with other departments to gather and compare data from different systems.

“There are lies, damned lies and statistics.”

Mark Twain

4. Simplified Software: Lowers Costs, Increases Reuse Of Code.

Large businesses often have complex IT systems that require constant maintenance, updates, and worse, large software subscription fees. Many times these software updates are because the business has to make use of new types of data. Thus, they must make programming changes in the software code.

With a data centric approach to software, a lot of “bloated” code can be done away with. This is because a “data centric” business software application can just focus on the software functions. For example, the software does not need a lot of “if” statements to deal with data content as that is handled in the data structure itself. As a result, this reduces development time and costs while improving the quality of software products.

By leveraging existing code, businesses can focus on innovation rather than reinventing the wheel.  See Yehonathan Sharvit’s blog posting, Principles of Data-Oriented Programming for more on how “data centric” software simplifies coding.  

5. Better Leverage And Adopt New Technology Such As AI And IoT.

Data-centric businesses are better equipped to leverage new technologies such as artificial intelligence (AI) and Internet of Things (IoT). These technologies rely heavily on data, making them a natural fit for data-centric businesses. By adopting emerging technologies early on, businesses can gain a competitive advantage and stay ahead of the curve. To detail, see below.

  • Artificial Intelligence. AI is best leveraged if it has access to large, quality data sets. The more a business and its automation is data centric, the better it can quickly leverage the latest AI technologies. See Neptune.AI’ Data-Centric Approach vs Model-Centric Approach in Machine Learning for a detailed explanation of the importance of taking a data centric approach with AI and machine learning (ML).
  • IoT Devices And Systems. Many times IoT systems are implemented for one purpose and then the data gets locked into one system. With a data centric approach, business users across the entire organization can access data for a wide variety of other purposes, now and in the future. For example, a large logistics company that is data-centric can use IoT sensors to track shipments. However, later they can use that same data for optimizing delivery routes, vehicle procurement planning, and so on. For more information on IoT, see my article Internet Of Things Examples – Hidden Technology Automating Logistics.

6. Simplifies Data Security, Integration, And Analysis.

Being data-centric simplifies data security, integration, portability, and analysis by providing a centralized approach for managing data. This data centric approach allows businesses to implement standardized security measures to protect their data from unauthorized access or breaches. It also makes it easier for software applications to access different data sources.

For example, a large ecommerce company that is data-centric can use a centralized approach to store customer information securely and analyze it to improve marketing campaigns. A centralized approach makes it easier to share customer data with other systems such as inventory management or shipping systems. Overall, businesses that are data-centric simplify the management of their data and make better use of their information assets.

For more on the technical aspects a data centric approach, see Dan DeMers’ post The Shift from an App-Centric to Data-Centric Architecture and Tam Tran-The’s Data Oriented Programming With Python.

“Data really powers everything that we do.”

Jeff Weiner

What Data Centric Is Not.

To get a better understanding of what “data centric” means, in the following article I’ll provide some examples of what data centric is not. Specifically, this will include how it is different from “data driven” and  “application centric”. To detail, see my article, You Need To Think Data Centric To Be A Successful Business: Stop Being Data Driven, Application Centric.

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

To help you understand in more detail what it means to have a “data-centric” perspective, click here and I will explain. In particular, we will dive into what “data centric” is not as well as how it varies from being “data-driven” or “application-centric.”

Also, for more details and perspectives on businesses taking a data centric approach, see Kevin Doubleday blog posting Introduction to Data-Centricity.

Additionally, for more articles from SC Tech Insights, see the latest postings on data.

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