9 Predictions for Knowledge in 2023 by @ttunguz

Yesterday, on the Monte Carlo Affect Summit I shared my 9 Predictions for Knowledge in 2023. Listed below are the slides & I’ve embedded them beneath.

These are my 9 predictions. A yr from now, I’ll rating them to see how I did.

  1. Cloud knowledge warehouses (CDW) will course of 75% of workloads by 2024. Within the final 5 years, CDWs have grown from 20% of the workloads to 50%, with on-prem databases constituting the rest. In the meantime, the business has grown from $36b to $80b throughout that point.
  2. Knowledge workloads will phase by use case into three teams. First, in-memory databases like DuckDB will develop to dominate native evaluation even for large information. CDWs will retain basic BI & exploration makes use of. Cloud knowledge lakehouses will serve jobs working on large knowledge & jobs that don’t require the quickest latency – and do it at half the storage worth.
  3. Metrics layers will unify the info stack. Right this moment, there are two completely different forks in knowledge. The primary fork makes use of ETL to pump knowledge right into a CDW, then to a BI or knowledge exploration software. The second fork, the machine studying stack, is similar save for the outputs: mannequin serving & mannequin coaching. The metric layer will develop into the one place metrics & options are outlined, unifying the stack & probably shifting mannequin serving & coaching into the database.
  4. Massive language machine studying fashions will change the position of information engineers. I recorded a video of myself writing code to supply charts & embedded it within the presentation. The video exhibits Github Copilot magically making a chart for the DuckDB star progress. Copilot ingests a remark, writes the code, even provides my customized theme perform. After I execute the code, it really works. Applied sciences like this can push knowledge engineering work to a better aircraft of abstraction.
  5. WebAssembly or WASM will develop into an important a part of end-user going through knowledge apps. WASM is a know-how that accelerates browser software program. Pages load quicker, knowledge processing is speedier & customers are happier. Each main browser helps WASM & consequently, anybody producing a knowledge app for an finish person will use it.
  6. Notebooks will win 20% of Excel customers. Of the 1b world Excel customers, 20% will develop into prosumers, writing Python/SQL to research knowledge. They may do it in notebooks like Jupyter, that are simply shared, reproducible & model managed. These notebooks will develop into knowledge apps utilized by finish customers inside corporations, changing brittle Excel & Google Sheets.
  7. SaaS purposes will use the CDW as a backend for each studying & writing. Right this moment, gross sales, advertising, & finance knowledge exist in disparate methods. ETL methods use APIs to push that knowledge into the CDW for evaluation. Sooner or later, software program merchandise will construct their apps on prime of the CDW to benefit from centralized safety, quicker procurement processes, & adjoining knowledge. These methods will even write again to the CDW.
  8. Knowledge Observability turns into a Should Have. Software program engineers measure the success of their efforts via up-time. 99.9% or three-nines of up-time means just one incident per 1000 hours. Right this moment’s knowledge groups see 70 incidents per 1000 tables. Knowledge groups will align on knowledge uptime/accuracy metrics & drive to the three-nines equal, utilizing knowledge observability instruments to measure their efficiency.
  9. The Decade of Knowledge Continues. Knowledge startups raised greater than $60b in whole in 2021 greater than 20% of all enterprise {dollars} raised. We’re nonetheless within the early innings of this foundational motion.

Thanks to the Monte Carlo staff for the chance & the viewers for the good questions on the finish. I’ll submit the video of the presentation when it’s stay.

Leave a Reply