Data Maturity

Is Your Data Working for You?

Many organizations possess vast amounts of data, but only a few effectively leverage it to create value.

Understanding your position on the data maturity curve is the crucial first step towards unlocking the full potential of your data.

At Levi9, we assist you in assessing, benchmarking, and enhancing your data maturity. Through a structured approach, we identify your strengths, reveal any gaps, and guide you in developing a data-driven culture and infrastructure. This transformation will support smarter decision-making, foster innovation, and promote sustainable growth.

Low maturity = high risk 

Inconsistent data practices, siloed systems, and unclear ownership stall digital initiatives and reduce trust in insights.

Higher maturity = higher ROI 

Organizations with higher data maturity see better business outcomes, according to research by Harvard Business Review. 

Our approach - Data Maturity Assessment consists of 5 key areas:

01

Strategy:

We examine the alignment between your business goals and your data strategy, where key questions are how data is used in decision-making processes, the impact you expect data initiatives to have, and the long-term vision for data within your organization.

02

Collection:

Our review of data collection focuses on the volume, velocity, veracity, variety, and validity of your data. In this process, we look at how data is gathered, the types of data available, and the processes you have in place for integrating and maintaining data quality. We also consider whether you have the necessary permissions to use external data and how your data collection process handles potential failures.

03

Storage:

Where and how data is stored, accessibility and scalability are some of the focus points. Since security is a major focus in this category, we evaluate compliance with regulations such as GDPR, HIPAA, and CCPA, as well as encryption practices and regular security audits.

04

Processing:

We assess to which level these processes are automated, their scalability, and how effectively bottlenecks or failures are managed. Additionally, we examine the high-level design of your data pipelines and whether there are continuous improvement processes in place for your data workflows.

05

Visualization:

The final category focuses on how well your organization transforms data into actionable insights. This is done by reviewing your reporting and dashboarding capabilities, the tools used for business intelligence, and the accessibility of these insights to decision-makers across the organization.

WHAT YOU GAIN: KEY OUTCOMES & DELIVERABLES 

Clarity on where you stand and what’s possible
Improved data governance, accessibility, and trust
Actionable steps to reach your target maturity level
Stronger foundation for AI, analytics, and digital transformation

June 26th

The Cost of Choice

Most companies spend up to 40% to much on cloud, are you? Cut spend, not options. Smart standardizations win.

Cloud cost overruns and growing technical debt rarely stem from tooling alone—they are symptoms of architectural and operational choices. This session looks at how senior technical leaders can regain control by connecting cloud spend directly to business value. We’ll explore unit‑economics thinking, ownership models, and lifecycle management practices that reduce waste while preserving delivery speed. You’ll learn how to combine FinOps principles with technical‑debt controls to create a cloud environment that is financially sustainable and technically healthy.

May 28th

AI AGENTS DESERVE AI PLATFORM

Portable patterns for Azure, AWS and GCP that survive the next upgrade

AI agents are moving rapidly from experimentation into real production use cases, but architectures vary widely across cloud platforms. In this webinar, we compare practical patterns for building and running AI agents on Azure, AWS, and Google Cloud Platform. We’ll focus on what to standardize, where to embrace cloud‑native capabilities, and how to design for security, observability, and future change. The goal is not to pick a winner, but to help leaders understand how to scale agent‑based solutions without locking themselves into fragile designs.

April 23rd

Winning on Repeat: Product Engineering in the Age of AI

Cadence, quality and outcomes over output

Delivering a successful solution once is no longer enough. In the age of AI, organizations need product engineering models that enable them to win consistently across teams, releases, and markets. This session explores how leading organizations evolve from project‑centric delivery to product‑centric execution, supported by AI‑augmented engineering practices. We’ll look at cadence, quality, and accountability, and how leadership decisions shape sustainable delivery performance over time.

April 2nd

GOVERNING AI IN PRODUCTION

Designing cloud and data platforms that survive real-world pressure

Many organizations succeed in building AI proofs of concept, far fewer succeed in scaling them safely into production. This webinar focuses on what it takes to move from experimentation to reliable, governed AI platforms. We’ll discuss platform architecture choices, model governance, security, and policy patterns that enable teams to deploy AI at scale without slowing down delivery. Designed for senior technical leaders, this session provides practical guidance on turning AI initiatives into durable capabilities that deliver value beyond the first demo

March 5th

Navigating Digital Sovereignty and Strategic Cloud Choices

How Organizations Can Balance Innovation, Compliance, and Control in a Multi-Cloud World

In today’s rapidly evolving digital landscape, organisations face increasing pressure to ensure business continuity, maintain public trust, and comply with complex regulations like NIS2, DORA, and GDPR. This webinar explores the critical concepts of digital and operational sovereignty, the strategic importance of hybrid and sovereign cloud models, and the risks of vendor lock-in.