SAP: The Software Everyone Uses But No One Loves
Liberating Your Enterprise's Most Valuable Hostage from the World's Most Expensive Database
Tarush Aggarwal
March 31, 2025
At Outside the Valley, we talk a lot about making data and AI work in the real world. And in that world SAP is just part of life.
SAP is everywhere. If your shoes, coffee, airline, or toothbrush came from a major global company—there’s a good chance SAP played a role somewhere in the supply chain. For decades, SAP has been the quiet, complex backbone of enterprise operations. It handles finance, procurement, HR, inventory, and more. But despite its reach, SAP rarely wins hearts.
SAP frustration stems from a perfect storm of dated UIs that feel teleported from the 90s, astronomical implementation costs that routinely run into millions, and a notoriously arrogant sales team that treats customers like they should be grateful just for the meeting. Despite powering 92% of the Fortune 2000, it's the enterprise software everyone relies on but nobody enjoys using - creating an adversarial relationship where companies feel trapped by a vendor who knows you can't leave
From the perspective of this blog we have no beef against SAP. We are only focussed on helping business get the most out of data and on that subject there is only one undeniable truth.
You need to move your data outside SAP
No matter how hard SAP tries to convince you their ecosystem is all you need for data and AI, the reality is painfully clear - you cannot build a serious data strategy or AI capability while keeping your data imprisoned in SAP's complex, closed architecture. The path forward isn't more SAP tools, it's liberating your business data and bringing it into environments actually designed for analytics and AI.
Here's the unfiltered truth on why:
🧠 1. SAP Was Built for Operations, Not Modern Analytics
SAP shines at running the business—finance, supply chain, HR—not at analyzing the business. Its core strength is transactional consistency, not exploratory analysis or machine learning.
SAP reports tend to be rigid, tabular, and slow.
Modern analytics requires slicing, dicing, and visualizing data from multiple systems, not just SAP.
🌐 2. Cross-System Analysis Needs a Unified View
Companies today run on a stack of apps: Salesforce, HubSpot, Marketo, NetSuite, Snowflake, Postgres, Jira, Stripe, Zendesk—you name it.
SAP is just one system of record.
To answer real questions (“Why did churn spike?”, “What drives net revenue retention?”), you need to blend SAP data with other sources.
Modern data warehouses and lakehouses are designed for this purpose. SAP is not.
🚀 3. Modern Tools > SAP’s Native Analytics
Tools like Snowflake, BigQuery, Databricks give you scale, flexibility, and speed.
Tools like Looker, Power BI, Tableau let analysts and business users explore data independently.
Tools like dbt, Apache Airflow, or ML frameworks bring in transformation, automation, and modeling power that SAP just doesn’t support natively.
End to end platforms like 5X give you all of the above in a single platform build for data and AI