One thing is certain in today’s world: more data is being generated every day than many organizations can consume, it is arriving at a faster pace than most organizations can manage, and it is difficult to quickly separate the signal from the noise. Data is becoming more complex, from more sources, with higher demand and with more scrutiny, including growing regulations.

Worldwide Growth of Data Estimated and Projected


Even the ways that data is being used has expanded and transformed in recent years, from reporting and BI to artificial intelligence and machine learning models, customer experience, employee experience, chatbots, large language models/generative AI, edge computing, and the list goes on.

In this context, the industry of Data Management has been transforming to address rapidly changing business requirements. Companies have come to grips with the fact that hiring resources to perform traditional data management activities will not yield enough capacity to handle everything that organizations aspire to achieve. Tooling that augments knowledge workers, with more built-in automation and ML-assisted capabilities are being introduced in every area of data management, allowing greater scaling and improved accuracy, requiring less organizational energy to be spent to achieve better results.

Prevailing thoughts on the most effective ways to implement Data Management have advanced along with the technical advances and the competitive landscape, including business units taking greater ownership of producing, managing, and publishing Data Products that follow centralized guidelines. This is what is driving the Modern Data Management and Architecture concepts that have become industry buzzwords.

Evolving Data Architectures

The volume of data, variety of sources, rapid innovation, explosion of AI, and the democratization of access means that outdated methods for data management, governance, and analytics are inadequate.

The modern data organization is:

Focused on business outcomes

Data literate

Digital and AI enabled


Taking advantage of these emerging technological and process best practices are critical to getting the most business value out of data, staying ahead of competitors, and ensuring enough of an innovative environment to attract and retain the best talent. But it can feel overwhelming. At Wavestone we strongly advocate driving changes within the delivery of use cases, defined and prioritized with business leaders; and, to achieve continuous, incremental progress along the journey. Our frameworks, built on experience and best practices guide and accelerate our ability to deliver value for our clients.

Wavestone Data Management Architecture & Ecosystem Framework

At Wavestone, we can help you evaluate your current maturity against the specific and unique goals and objectives of your organization, and help you put a practical plan together that will allow you to achieve real value over time in a way that is congruous with what your organization has set out to achieve with its business plan.

Example Deliverables, depending on engagement type:

Maturity Assessment, customized to your business and its goals

Prioritization and Practical, Achievable Roadmap

Operating Model Design

Engagement Model

Change Management Plan

Driving a Data Product Mindset

Data & Technical Architecture

Business Data Modeling

Migration Approaches (including Cloud)

Ecosystem Tooling Recommendations

Implementation Leadership

Agile Transformation & Coaching for Data Programs and Products


Faster time-to-market for data-enabled business goals

Increased business value from enabling high-value use cases

Greater efficiency & ability to scale with more effective processes

Greater business agility and ability to make big decisions quickly

Stronger compliance with internal policies and external regulators

Wavestone can also help oversee the implementation of the roadmap in conjunction with your internal teams, business units, and other external partners. We bring practical, real-world experience and can aid you in navigating through organizational obstacles to help drive real change through solid Data Management, Architecture, and Ecosystem delivery.

Case Study: Data Management and Architecture to Drive Retail Revenue

Major US retailer recently hired a Chief Data Officer to build the organization’s first data team. Data had been widely decentralized, unmanaged, and of inferior quality. Consistent errors and SLA breaches caused significant data-monetization-revenue penalties. Wavestone provided a business-oriented strategy and path forward, using modern, ML-assisted tooling and processes, along with achievable crawl-walk-run milestones.

A new operating model based on the unique needs of that business was established and we aided in hiring the full-time team that the organization needed. Measurement, monitoring, and remediation processes were created to ensure data issues were identified and actioned early to avoid business losses. And an automation program simplified and unified data governance, privacy, compliance, and information security.

Strategy Brief

Preempt disruption and gain a competitive edge.

Learn how the role of IT leaders is rapidly changing.

Featured Expert

  • Featured Expert -  John Dabek

    John Dabek

    Managing Principal

    • John is an award-winning technology executive with over 30 years’ experience in M&A, organizational design, and IT leadership.
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