Understanding Total Cost of Ownership (TCO) for Data Delivery Platforms—and How Incorta Lowers It

Organizations rely on efficient data delivery platforms to extract insights, drive decisions, and maintain a competitive edge. However, the Total Cost of Ownership (TCO) of these platforms goes far beyond initial licensing fees—it includes infrastructure, maintenance, personnel, and hidden inefficiencies.

In this article, we'll explore

• What TCO means for a data delivery platform
• How traditional solutions drive up costs
• Why Incorta reduces TCO with its Direct Data Mapping engine
• Real-world examples from Incorta customers

What Is Total Cost of Ownership (TCO) for a Data Delivery Platform?

TCO encompasses all direct and indirect costs associated with deploying and maintaining a data analytics solution over its lifecycle. For a data delivery platform, this includes:

1. Software Licensing & Subscription Costs – Upfront and recurring fees.
2. Infrastructure & Cloud Costs – Storage, compute power, and scaling needs.
3. Data Engineering & IT Labor – Time spent on ETL/ELT pipelines, maintenance, and troubleshooting.
4. Performance & Latency Costs – Delays in insights due to slow queries or complex transformations.
5. Opportunity Costs – Missed revenue or efficiency gains from delayed decision-making.

Traditional data platforms (like legacy data warehouses or BI tools) often have high TCO due to complex data modeling, excessive ETL processes, and reliance on IT teams for every change.

How Incorta Lowers TCO

Incorta’s Direct Data Mapping architecture eliminates many of the costly inefficiencies found in traditional platforms. Here’s how:

1. No ETL/ELT Overhead → Lower Labor & Infrastructure Costs

• Traditional approach: Data must be transformed, modeled, and loaded before analysis (requiring weeks of engineering effort).
• Incorta’s approach: Directly accesses raw data with no pre-aggregation, reducing ETL pipelines by up to 90% (as seen with Broadcom, which cut data prep time from weeks to hours).

2. Reduced Storage & Compute Costs

• Incorta’s columnar indexing and in-memory optimizations require less storage and compute power than traditional warehouses.

3. Faster Time-to-Insight → Lower Opportunity Costs

• With Incorta, business users can self-serve analytics without IT dependency.
• Case in point: Shutterfly reduced reporting time from days to minutes, accelerating decision-making.

4. Simplified Architecture = Fewer Licenses & Tools

• Incorta consolidates data ingestion, transformation, and analytics in one platform, reducing the need for multiple vendors (e.g., separate ETL tools, data lakes, and BI layers).

Real-World TCO Savings with Incorta

• Broadcom: Slashed data pipeline costs by 80% and improved reporting speed 100x.
• Shutterfly: Reduced data prep effort by 75%, freeing up IT resources.

When evaluating a data delivery platform, TCO is a critical factor. Traditional solutions burden organizations with hidden costs—slow queries, complex pipelines, and excessive cloud bills.

Incorta’s Direct Data Mapping eliminates these inefficiencies, delivering:
✅ Lower infrastructure costs (less storage/compute needed)
✅ Reduced labor costs (minimal ETL and IT dependency)
✅ Faster insights (real-time analytics without delays)

For businesses looking to cut costs while accelerating analytics, Incorta provides a proven, high-performance alternative to legacy systems.

Want to see how much you could save? See Incorta in action.

‍