Data, no longer just an operational necessity, is recognized as a core strategic asset. Organizations that effectively leverage AI-driven data products gain a competitive advantage by making informed decisions. However, businesses struggle with three key obstacles in utilizing data effectively: complexity, time, and cost.
1. Complexity. Complexity with organizations can be broken down into two components:
The technology landscape for organizations is forever fragmenting, whether that be legacy systems or modern systems. In addition, organizations desire to utilize new technologies, at speed, without constantly spending capital to reengineering to utilize those technologies.
Talent. The ever-changing landscape of technology has resulted in the need to hire specialized technical talent. This talent is hard to find, hard to train, and expensive.
2. Time. The time to market for data required to make decisions is accelerating. Business users can’t wait for weeks or months for central teams to deliver requests to support business activities. In addition, the demand on these central teams (data teams, IT teams, or data science teams) is ever increasing, so the need to increase efficiency and productivity is real.
3. Cost. The time to market for data projects has always been a challenge. The sheer nature of data projects makes them expensive. These costs are increasing, even when using modern and cloud-based technologies, costs are becoming prohibitive and a barrier. This is exasperated further for AI use cases, where the data effort can be up to 100x the AI effort to deliver such use cases.
Why Data Products Matter More Than Ever
In my earlier blog, "Why Crafting Data into Products is Essential," I discussed how business teams struggle to turn raw data into actionable insights because of their reliance on centralized data teams.
"Data products allow organizations to democratize data access and bring value faster, making the shift from traditional data management approaches to insight-driven business models." – Gartner.
However, many companies still lack the right tools to create and manage data products without extensive IT intervention. This is where Latttice changes the game.
Latttice was designed to address this. It allows organizations to empower domain experts to create AI-powered data products without technical complexity.
How Latttice Solves These Obstacles
Latttice was specifically designed to build data products, based on data mesh principles. By nature, Latttice addresses the challenges of complexity, time, and cost through its innovative approach to data integration, governance, and automation. Here's how Lattice mitigates each of these challenges:
1. Complexity
a. Technology
Interoperability. Latttice connects disparate data sources (legacy and modern) without requiring extensive reengineering. With its stable of connectors, it enables organizations to adopt new technologies seamlessly without significant capital expenditure.
AI Powered, Zero Code. Latttice reduces the dependency on custom development by offering a user-friendly, configuration-driven approach to data processing and management. This broadens the number of users that can be involved in data activities and increases adoption.
Unified Metadata and Governance. Instead of relying on fragmented tools, Latttice provides a consistent, centralized metadata layer, allowing for better data discoverability and lineage tracking.
b. Talent.
Automated Data Engineering: Latttice’s AI-driven automation enable the “citizen data engineer”, reducing reliance on specialized engineering talent by deploying hyper automation, enabling those data engineering teams to focus on more complex tasks.
Self-Service Capabilities: Business users can leverage Latttice to create, configure, and collaborate with data products without needing deep technical expertise, reducing the dependency on scarce technical talent.
2. Time
a. Self-Serve Data Product Creation
Latttice enables business users to discover, create, configurate, and collaborate on data products without waiting on central teams, significantly reducing turnaround time.
b. Automated Data Lineage & Quality Checks
Latttice ensures data is available and trustworthy by providing automated recommendations for data quality and data privacy.
c. Speed to Market
User can create data products within minutes, not weeks or months, enabling better decisions.
3. Cost
a. Productivity
The increased productivity of more people being able to do more with less, coupled with the ability to use existing data infrastructure, provides a significant ROI boost to existing data platforms without additional capital outlay.
b. Efficiency
The way in which data products are created within Latttice results in a 90% increase in the reuse of such data products across multiple domains and decisions, drastically reducing the cost of delivering subsequent data requirements.
Latttice isn’t just another data tool—it’s an AI-powered ecosystem that simplifies data product creation, governance, and analytics in one unified platform.
By removing technical barriers and decentralizing data ownership, Latttice enables organizations to scale data-driven decision-making efficiently.
As I noted in my earlier blog:
“Traditionally, creating data products required heavy IT involvement - long turnaround times, complex queries, and limited access for business users. Latttice changes this by putting data product creation in the hands of domain experts.”
This shift removes bottlenecks and accelerates the journey from raw data to actionable insights.
Cameron Price, in his blog "Latttice: Empowering Businesses with AI-Driven Data Products," illustrates how Latttice removes traditional data bottlenecks by putting control directly in the hands of users.
How Latttice Could Transform Decentralized Data Management: A Use Case
In my earlier blog, I introduced Sarah, a regional retail manager who struggled to access the data she needed to optimize inventory and sales. While Sarah is a hypothetical example, her challenges reflect real-world problems many businesses face.
Sarah’s Old Reality: Bottlenecks & Outdated Insights
Dependent on IT teams – Sarah had to request reports from centralized data teams, leading to delays.
Fragmented systems – Data was scattered across sales, inventory, and supply chain platforms, making it hard to get a full picture.
Missed opportunities – By the time Sarah received her reports, the data was outdated, forcing her to react instead of proactively plan.
What If Sarah’s Organization Adopted Latttice?
With Latttice, Sarah’s company could decentralize data management, allowing business users to create, own, and manage their own data products while still maintaining strong governance.
Sarah’s team could access and combine data instantly – no more waiting on IT.
AI-driven governance could ensure security – while still allowing domain teams to self-serve insights.
Predictive analytics could help forecast inventory needs – reducing stockouts and excess inventory.
Data products could be shared across teams – meaning finance, logistics, and marketing could all leverage quality, trusted insights.
"If Sarah’s organization adopted Latttice, they could eliminate bottlenecks, decentralize data access, and empower teams to make faster, more informed decisions."
The Bigger Picture: The Shift to Decentralized Data Strategies
Sarah’s scenario reflects a growing shift in data management—moving away from centralized bottlenecks toward decentralized data ownership.
As McKinsey reports:
"Organizations that empower domain teams with self-service data access are twice as likely to be industry leaders in data-driven decision-making."
Latttice is designed to support this shift, ensuring businesses can scale their data operations without losing governance or security.
Why AI-Driven Data Mesh & Latttice Are the Future
Cameron Price, in his blog "Agentic-Driven Data Mesh: A Shift to Autonomous Data Management,", explores how AI-powered agents are transforming data mesh architectures by removing manual complexity and enhancing scalability.
AI-Powered Governance & Automation
As Gartner (2023) states:
"The increasing adoption of decentralized data ecosystems requires AI-driven mechanisms to manage complexity, scale operations, and ensure quality at every level of the data lifecycle."
How Latttice Embodies This Shift:
AI-driven automation manages data governance, compliance, and optimization without manual intervention.
Automated metadata management and schema validation reduce operational overhead and ensure accuracy.
Eliminating Bottlenecks in Data Access
Cameron Price highlights how traditional governance models create friction by relying on centralized IT teams. Instead, AI-driven agents ensure secure and autonomous data access.
As AWS (2023) notes:
"AI-powered agents provide proactive solutions for scaling infrastructure and ensuring data accessibility, making them essential for modern decentralized data platforms."
How Latttice Enhances Data Accessibility:
Federated governance ensures compliance without restricting access to domain teams.
Business users can securely access data products without waiting for IT approvals.
Scalability Without Complexity
AI-driven automation is crucial for making data mesh architectures scalable. By removing manual intervention, AI enhances governance, predicts infrastructure needs, and ensures data products remain high-quality and up-to-date.
How Latttice Supports Scalable Data Strategies:
Predictive analytics automates infrastructure scaling, ensuring business continuity.
AI-powered insights enable organizations to respond dynamically to market shifts and operational needs.
From Chaos to Clarity: The Future of Data with Latttice
When I wrote my earlier blog, I wanted to emphasize that crafting data into products isn’t just important—it’s mission-critical. What I’ve seen since then is that Latttice takes this concept even further, allowing organizations to eliminate complexity, reduce costs, and empower domain teams to take full control of their data—without IT bottlenecks.
As McKinsey hightlights:
"Companies that harness the power of their data are twice as likely to be in the top quartile of financial performance within their industries, and five times as likely to make faster decisions."
Latttice ensures businesses aren’t just collecting data—they’re transforming it into a strategic advantage.
"With Latttice, you don’t need to compromise on data timeliness or access; it seamlessly delivers both." – Cameron Price, Founder of Data Tiles
If you’re ready to move beyond fragmented systems and fully embrace data ownership, it’s time to explore Latttice.
Let’s start a data conversation,
Lili Marsh.
References:
Gartner (2023). Harnessing Data and Analytics to Deliver Value. Retrieved from Gartner
McKinsey & Company (2023). The Age of Analytics: Competing in a Data-Driven World. Retrieved from McKinsey & Company
AWS (2023). AI-Powered Agents for Modern Data Platforms. Retrieved from AWS
Cameron Price (2023). Agentic-Driven Data Mesh: A Shift to Autonomous Data Management. Retrieved from Data Tiles
Cameron Price (2023). Latttice: Empowering Businesses with AI-Driven Data Products. Retrieved from Data Tiles
Lili Marsh (2023). Why Crafting Data into Products is Essential: My Perspective as a Data Consultant. Retrieved from Data Tiles