# Most companies think they have a data strategy. What they actually have is da...
Canonical: https://social-archive.org/tgroenwals/C8Dg9u5ZYG
Original URL: https://www.linkedin.com/posts/ashish--joshi_most-companies-think-they-have-a-data-strategy-share-7467416268900503552-SEXX/
Author: Ashish Joshi
Platform: linkedin
## Content
Most companies think they have a data strategy. What they actually have is data everywhere. Different tools. Different pipelines. Different definitions of truth. And when leadership asks for insight, the organization spends weeks reconciling numbers. The problem is rarely analytics. It is architecture. Behind every modern product, AI system, and business decision sits a Big Data architecture that determines how fast the company can think. 𝐀𝐭 𝐬𝐜𝐚𝐥𝐞, 𝐭𝐡𝐞 𝐟𝐥𝐨𝐰 𝐮𝐬𝐮𝐚𝐥𝐥𝐲 𝐥𝐨𝐨𝐤𝐬 𝐥𝐢𝐤𝐞 𝐭𝐡𝐢𝐬: • 𝐃𝐚𝐭𝐚 𝐒𝐨𝐮𝐫𝐜𝐞𝐬 Product events, CRM systems, IoT signals, third-party APIs. The raw signals of the business. • 𝐃𝐚𝐭𝐚 𝐈𝐧𝐠𝐞𝐬𝐭𝐢𝐨𝐧 Batch pipelines for historical analysis. Streaming pipelines for operational decisions. • 𝐃𝐚𝐭𝐚 𝐒𝐭𝐨𝐫𝐚𝐠𝐞 Warehouses, lakes, and distributed systems designed for scale, reliability, and flexible queries. • 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 & 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 Statistical models, ML systems, and experimentation layers that turn raw signals into decisions. • 𝐃𝐚𝐭𝐚 𝐂𝐨𝐧𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧 Dashboards, APIs, alerts, and internal tools that bring insights directly to teams. • 𝐃𝐚𝐭𝐚 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 Ownership, lineage, privacy, and access control. Without this, scale creates chaos. The organizations winning with AI today did not start with models. They started with data architecture that moves fast without breaking trust. P.S. Which layer of the data stack do you think most companies underestimate today? Curious to hear how others are thinking about this. Follow Ashish Joshi for more insights