The Simplicity of Creating Data Products with Latttice

Data, no longer just an operational necessity, is now recognized as a core strategic asset. Organizations that effectively leverage AI-driven data products gain a competitive advantage by making informed decisions. Yet most businesses still struggle with three persistent obstacles: complexity, time, and cost.

Technology landscape. The technology landscape inside organizations is forever fragmenting, legacy systems alongside modern ones, while teams are expected to adopt the next wave of technologies at speed without constantly spending capital re-engineering to use them.

Talent. The ever-changing landscape has created demand for specialized technical talent that is hard to find, hard to train, and expensive to retain.

The time-to-market for data needed to make decisions is accelerating. Business users can't wait weeks or months for central teams to deliver requests. Meanwhile, demand on data, IT and data-science teams keeps climbing. Efficiency and productivity aren't optional.

Data projects have always been expensive, and even modern cloud platforms haven't broken the curve. For AI use cases this is amplified. The data effort can be up to 100× the AI effort needed to deliver the use case.

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 to insight-driven business models.

Gartner

Many companies still lack the right tools to create and manage data products without extensive IT intervention. This is where Latttice changes the game, empowering domain experts to create AI-powered data products without technical complexity.

Latttice was specifically built for data products on data-mesh principles. By design, it addresses complexity, time and cost through interoperability, AI-driven automation and unified governance.

• Interoperability. Connectors for legacy and modern sources, no re-engineering required.
• AI-powered, zero-code. Configuration replaces custom development, broadening who can build.
• Unified metadata & governance. One layer for discoverability, lineage and trust.
• Automated data engineering. Hyper-automation lets engineers focus on harder problems.
• Self-service. Business users create, configure and collaborate without deep technical skill.

With Latttice, business users discover, create, configure and collaborate on data products without waiting on central teams. Automated lineage and quality recommendations make the result trustworthy from day one.

Users can create data products within minutes, not weeks or months, enabling better decisions, on time.

The increased productivity of more people doing more, with less, coupled with the ability to use existing data infrastructure, provides a significant ROI uplift to platforms you've already paid for, with no additional capital outlay.

The way Latttice creates data products drives a 90% increase in reuse across domains and decisions, drastically reducing the cost of delivering subsequent data requirements.

In an 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 hypothetical, her challenges reflect very real business problems.

Sarah's old reality

• Dependent on IT teams. Reports requested from central data teams, and delayed.
• Fragmented systems. Sales, inventory and supply-chain data scattered across platforms.
• Missed opportunities. By the time reports arrived the data was already outdated.

If Sarah's organization adopted Latttice

• Her team accesses and combines data instantly. No more waiting on IT.
• AI-driven governance keeps it secure while enabling self-service.
• Predictive analytics forecasts inventory needs. Fewer stockouts, less excess.
• Data products are shared so finance, logistics and marketing leverage the same trusted insights.

If Sarah's organization adopted Latttice, they could eliminate bottlenecks, decentralize data access, and empower teams to make faster, more informed decisions.

Sarah's scenario reflects a growing shift in data management, moving away from centralized bottlenecks toward decentralized data ownership.

Organizations that empower domain teams with self-service data access are twice as likely to be industry leaders in data-driven decision-making.

McKinsey

Latttice is designed to support this shift, ensuring businesses can scale their data operations without losing governance or security.

AI-powered agents are transforming data-mesh architectures by removing manual complexity and enhancing scalability.

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.

Gartner (2023)

• AI-powered governance & automation. Compliance and optimization without manual intervention.
• Federated governance. Compliance without restricting domain access.
• Secure access. Business users get to data products without waiting on IT approvals.
• Predictive analytics. Automates infrastructure scaling for business continuity.

AI-powered agents provide proactive solutions for scaling infrastructure and ensuring data accessibility, making them essential for modern decentralized data platforms.

AWS (2023)

Crafting data into products isn't just important. It's mission-critical. Latttice takes the concept further, eliminating complexity, reducing cost, and empowering domain teams to take full control of their data without IT bottlenecks.

Companies that harness the power of their data are twice as likely to be in the top quartile of financial performance, and five times as likely to make faster decisions.

McKinsey

With Latttice, you don't need to compromise on data timeliness or access. It seamlessly delivers both.

Cameron Price, Founder of Data Tiles

Latttice ensures businesses aren't just collecting data. They're transforming it into strategic advantage.

1. Gartner. (2023). Harnessing Data and Analytics to Deliver Value.
2. McKinsey & Company. (2023). The Age of Analytics: Competing in a Data-Driven World.
3. AWS. (2023). AI-Powered Agents for Modern Data Platforms.