Prompt
What should I use to feed scraped data into downstream analytics?
Latest observation
For feeding scraped data into downstream analytics, the best choice is usually a structured storage layer plus a pipeline to clean/transform it first.
Good default options
- PostgreSQL: Best if you want something simple, reliable, and easy to query with SQL.
- Data warehouse like BigQuery, Snowflake, or Redshift: Best if the scraped data is large and you’ll be doing lots of analytics.
- Parquet files on object storage like S3/GCS/Azure Blob: Best for scalable, cost-effective analytics pipelines, especially with tools like Spark, DuckDB, or Athena.
Typical pipeline
- Scrape raw data
- Store it in a raw format first
- Clean/normalize it into a structured table or columnar file
- Load it into your analytics destination
- Use BI/analytics tools or notebooks on top
Rule of thumb
- Small to medium volume: PostgreSQL
- Large scale analytics: BigQuery/Snowflake/Redshift
- Cheap, flexible lake-style pipeline: Parquet + S3
If you want near-real-time analytics
Use a stream/event pipeline such as:
- Kafka
- Amazon Kinesis
- Google Pub/Sub
If you tell me your scale, budget, and whether you need batch or real-time analytics, I can recommend a specific stack.
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
Want this interpreted for your brand?
Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.