Data Architecture: What It Is And Why You Need It

In today’s digital economy, enterprises strive to maximize the value of data for improved business performance. Data architecture is a key enabler for an enterprise to become data driven. It is the practice of designing, building and optimizing data-driven systems by incorporating the company’s vision, strategies, business rules, standards, and capabilities to manage the data. While many progressive and proactive organizations have the data architecture capability within the role of chief data officer (CDO) function, there are still some organizations that are yet to take that plunge. This article aims to demonstrate the importance and need for a good data architecture in an enterprise by answering two simple questions. First, what would the business gain from a data architecture? Second, what would a business lose by not having a data architecture?

First things first. Why should the business care for a data architecture? At the highest level, data architecture offers solid strategies for companies to manage their data in the entire data lifecycle of data capture, integration, analytics and visualization. Specifically, data architecture offers three key benefits to the business:

1. STRONG DATA STRATEGY. Strategy in general involves considering alternatives and making trade-offs to pick the best option. A strong data strategy needs to be underpinned by a flexible and scalable data architecture that aligns with company strategies, compliance requirements, business rules, capability and IT standards reflecting the current and the future states. These aspects are reflected in the data strategy and data architecture that presents the data landscape as enterprise data model (EDM). EDM is a holistic representation of the data created and consumed across the entire organization.

2. IMPROVED COMMUNICATION AND COLLABORATION. A typical enterprise has various stakeholders with different roles, needs, priorities, and constraints across multiple lines of business (LoB). Also, for the most part, enterprises operate within various assumptions and constraints. All this often results in data silos in the company. So, when stakeholders from various functions, geographies, LoBs and competing needs come together, you need a data architecture that can provide a common language for improved communication, collaboration, and data literacy.

3. CREATE OPTIMAL INFORMA- TION FLOWS. As data architecture provides a holistic view of the data flows in the enterprise — current and future — it provides opportunities for creating lean and optimal in formation flows by eliminating complexity, reusing data, and minimizing data and system redundancy. This ultimately results in reduced cost, minimized risk and faster time to market for the products and services.

On the contrary, what will the business lose by not having a good data architecture? While data can be an asset, it can even become a liability very quickly. There are three situations where data can become a liability to the company and the root cause of it can be traced to a lack of good data architecture:

1. UNDEFINED PURPOSE. Without a good data architecture, companies often collect data without a clear business objective. Collecting data without a defined purpose will result in increased cost and missed business opportunities. According to Forrester, 73% of data in a company is never used strategically [1]. While the time and effort to acquire, store and secure data is significant, the opportunity cost of not utilizing the data collected in today’s digital world is massive.

2. POOR COMPLIANCE WITH LAWS, RULES AND ETHICS. Data architecture provides solutions to address compliance with laws, business rules, industry standards and even ethics. With the rise of cybercrime and data breaches, companies today are faced with the task of ensuring strong data security and privacy. Data security and privacy are key considerations in a data architecture. In 2017, when hackers accessed millions of customer records from the credit reporting agency Equifax, the company spent $1.4 billion to transform the security infrastructure as the root cause of the issue was tied to Equifax’s poor data and security architecture [2].

3. INCREASED COSTS. Without an enterprise-level data architecture, companies will potentially spend unnecessary time and effort in maintaining redundant data in the data lifecycle, including duplicate customers, products, assets., etc. Apart from labor costs, data management consumes a lot of data center electricity, thereby increasing the carbon footprint of the company. In 2018, data centers consumed about 1.1% of total global electricity [3].

The volume of data generated by businesses today is unprecedented. As this growth continues, so do the opportunities for organizations to derive business results from their data. Stephen Covey, author of international bestseller, “The 7 Habits of Highly Effective People,” said, “Start with the end in mind.” Do you build a skyscraper without architecture? In today’s data-centric business world, the digital journey for the business should start with a solid foundation — the data architecture. The foundation itself has little value to the business; but the foundation helps to build scalable and robust data-driven systems for business productivity and sustainable competitive advantage.

REFERENCES:

1.https://go.forrester.com/blogs/ha-doop-is-datas-darling-for-a-reason/

2.https://www.wired.com/story/equifax-security-overhaul-year-after-breach/

3.https://www.computerworld.com/article/3431148/why-data-centres-are-the-new-frontier-in-the-fight-against-climate-change.html

Dr. Prashanth H. Southekal is the managing principal of DBP-Institute, a data analytics consulting and education company. He brings over 20 years of information management experience from companies such as SAP, Shell, Apple, P&G, SAS and General Electric. He sits on the advisory board of SAS (Western Canada) and Grihasoft (India). He is the author of two books, “Data for Business Performance” and “Analytics Best Practices”. Dr. Southekal is an adjunct faculty of data analytics at the University of Calgary (Canada) and IE Business School (Spain). He holds a Ph.D. from ESC Lille (FR) and an MBA from Kellogg School of Management (US). 

Santosh Raju is a principal consultant at DBP-Institute (www.dbp-institute.com), a data analytics consulting firm. He brings over 20 years of experience providing data analytics, connected and digital solutions. He has extensive experience shaping and delivering innovative digital solutions across various industry verticals and advising Fortune 2000 customers. Raju is a speaker at several industry events and advisor to several start-ups. Santosh lives in London, United Kingdom (UK).