Video wird geladen...

Video konnte nicht geladen werden

Beim Laden dieses Videos ist ein Problem aufgetreten. Dies könnte an einem vorübergehenden Netzwerkproblem liegen oder das Video ist möglicherweise nicht verfügbar.

Does your team rely on Snowflake or BigQuery as your data warehouse? We built the step that every other onchain data provider skips. Transform first, deliver only what you need. dbt Connector → Datashare is now live. Query against 130+ chains ➡️ Transform with dbt on DuneSQL ➡️ Deliver... show more

Dune

406,274 subscribers

31,177 Aufrufe • vor 2 Monaten •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

📣 Launching today: Kalshi and Polymarket data, unified on Dune — for macro and equity research. How this dataset is different: ✅ Hourly candles — not daily snapshots. Kalshi back to June 2021, Polymarket back to November 2022. ✅ One schema across Polymarket and Kalshi — not five integrations to maintain. ✅ Per-fill trades on both venues. Polymarket fills traceable onchain to the wallet. Access via SQL on Dune, Datashare into Snowflake, BigQuery, or Databricks, or MCP. Explore the data collection:

📣 Launching today: Kalshi and Polymarket data, unified on Dune — for macro and equity research. How this dataset is different: ✅ Hourly candles — not daily snapshots. Kalshi back to June 2021, Polymarket back to November 2022. ✅ One schema across Polymarket and Kalshi — not five integrations to maintain. ✅ Per-fill trades on both venues. Polymarket fills traceable onchain to the wallet. Access via SQL on Dune, Datashare into Snowflake, BigQuery, or Databricks, or MCP. Explore the data collection:

Dune

804,879 Aufrufe • vor 25 Tagen

Frictionless onchain data access for AI agents. Live today on Dune, built on MPP with Stripe and Tempo 🌊 No subscription. No account. No human in the loop. Agents pay per query across 130+ chains — stablecoin flows, DEX volumes, wallet activity, and more. Tempo chain data coming to Dune soon.

Frictionless onchain data access for AI agents. Live today on Dune, built on MPP with Stripe and Tempo 🌊 No subscription. No account. No human in the loop. Agents pay per query across 130+ chains — stablecoin flows, DEX volumes, wallet activity, and more. Tempo chain data coming to Dune soon.

Dune

45,266 Aufrufe • vor 2 Monaten

.Alessandro Losi shows off the new Dune | We Are Hiring! DBT connector to bring your own data engineering toolkit to Dune

.Alessandro Losi shows off the new Dune | We Are Hiring! DBT connector to bring your own data engineering toolkit to Dune

Solana

22,343 Aufrufe • vor 6 Monaten

What if you and your agent had all the data that always stays fresh? Structured, on demand, never stale. Introducing BigSet. Describe the data you need in plain English → get a structured dataset built from the live web, that refreshes regularly. It's live and open-source.

What if you and your agent had all the data that always stays fresh? Structured, on demand, never stale. Introducing BigSet. Describe the data you need in plain English → get a structured dataset built from the live web, that refreshes regularly. It's live and open-source.

TinyFish

208,376 Aufrufe • vor 13 Tagen

Computer now connects to Snowflake. Run end-to-end work against live warehouse data and get answers with SQL, source tables, filters, and metrics. It’s like a personal data science team, on call with accurate answers from live company data.

Computer now connects to Snowflake. Run end-to-end work against live warehouse data and get answers with SQL, source tables, filters, and metrics. It’s like a personal data science team, on call with accurate answers from live company data.

Perplexity

77,377 Aufrufe • vor 1 Monat

Qullamaggie Motivation - One Bull Market to Change your Finances Forever “Guys, you only need one bull market to get rich and change your financial futures. You only need one bull market. Learn the setups. Learn what moves markets. Learn how stocks move. Learn what moves stocks. Memorize the patterns. You only need one bull market to change your finances forever. I'm talking about this specific breakout and earnings strategy. There are obviously other strategies I use too, but right now I don't have any shorts on or any mean reversion trades on.”

Qullamaggie Motivation - One Bull Market to Change your Finances Forever “Guys, you only need one bull market to get rich and change your financial futures. You only need one bull market. Learn the setups. Learn what moves markets. Learn how stocks move. Learn what moves stocks. Memorize the patterns. You only need one bull market to change your finances forever. I'm talking about this specific breakout and earnings strategy. There are obviously other strategies I use too, but right now I don't have any shorts on or any mean reversion trades on.”

Lone

12,561 Aufrufe • vor 11 Monaten

Here's how I would learn data engineering basics in 2025: - Find a data source you care about (examples: gaming APIs, stock market, web scraping, etc) - Use Python to interact and ingest your source. Initially just write the data to a CSV. - Setup an account with Snowflake or Google BigQuery. - update your Python script to load a table in Snowflake/BigQuery - schedule your script with CRON in the cloud with a service like Heroku. - build aggregations and visualizations on top of your ingested data Only thing this misses is data quality and complex job orchestration which you can learn later! How would you learn data engineering nowadays?

Here's how I would learn data engineering basics in 2025: - Find a data source you care about (examples: gaming APIs, stock market, web scraping, etc) - Use Python to interact and ingest your source. Initially just write the data to a CSV. - Setup an account with Snowflake or Google BigQuery. - update your Python script to load a table in Snowflake/BigQuery - schedule your script with CRON in the cloud with a service like Heroku. - build aggregations and visualizations on top of your ingested data Only thing this misses is data quality and complex job orchestration which you can learn later! How would you learn data engineering nowadays?

Zach Wilson

20,368 Aufrufe • vor 11 Monaten

Need to transform messy data into actionable insights for your organization? Enterprise FluxAI got you!

Need to transform messy data into actionable insights for your organization? Enterprise FluxAI got you!

Flux I Decentralized Cloud

13,096 Aufrufe • vor 1 Jahr

Dune CLI & Skills are live 🔔 130+ chains of onchain data, now agent-native. Your AI agents can now: ✅ Discover onchain tables and schemas ✅ Write and execute DuneSQL ✅ Search Dune docs ✅ Handle errors automatically ✅ Optimizing costs More context-efficient than MCP for terminals ( Claude Code, OpenCode, Cursor) and agents ( OpenClaw🦞, NanoClaw, IronClaw , etc).

Dune CLI & Skills are live 🔔 130+ chains of onchain data, now agent-native. Your AI agents can now: ✅ Discover onchain tables and schemas ✅ Write and execute DuneSQL ✅ Search Dune docs ✅ Handle errors automatically ✅ Optimizing costs More context-efficient than MCP for terminals ( Claude Code, OpenCode, Cursor) and agents ( OpenClaw🦞, NanoClaw, IronClaw , etc).

Dune

75,468 Aufrufe • vor 3 Monaten

Amazon Redshift RG, powered by AWS Graviton, deliver better performance - running data warehouse and data lake workloads up to 2.4x as fast as previous generation RA3 at 30% lower cost per vCPU. Run SQL analytics across your data warehouse and data lake from a single engine — including on open formats such as Apache Iceberg and Apache Parquet. Built to meet the demands of today’s analytics and agentic AI workloads.

Amazon Redshift RG, powered by AWS Graviton, deliver better performance - running data warehouse and data lake workloads up to 2.4x as fast as previous generation RA3 at 30% lower cost per vCPU. Run SQL analytics across your data warehouse and data lake from a single engine — including on open formats such as Apache Iceberg and Apache Parquet. Built to meet the demands of today’s analytics and agentic AI workloads.

Amazon Web Services

13,389 Aufrufe • vor 1 Monat

You need to be competent with your handgun. Your handgun is not "what you use to fight for your rifle" or some bullshit like that. The only thing you will likely have is your Handgun. You need to be proficient.

You need to be competent with your handgun. Your handgun is not "what you use to fight for your rifle" or some bullshit like that. The only thing you will likely have is your Handgun. You need to be proficient.

Flat Ranger - UT

58,398 Aufrufe • vor 7 Monaten

Available to everyone: The new analytics lets you query your data directly from a report in real time using ShopifyQL, for more dynamic and customizable reporting. Everyone has a data warehouse now!

Available to everyone: The new analytics lets you query your data directly from a report in real time using ShopifyQL, for more dynamic and customizable reporting. Everyone has a data warehouse now!

tobi lutke

12,097 Aufrufe • vor 1 Jahr

📣 Launching today: the onchain data stack for audit, tax, and financial reconciliation. 🧮 ✅ Token Transfers — normalized across Ethereum EVM, Solana, Stellar, Ripple, Aptos, Sui, and Tempo. Every row traceable to source tx. One schema, every chain. ✅ Decoded Logs (EVM) — every contract event decoded and standardized. The evidence layer. ✅ Labels — add-on. Known addresses resolved to named entities. Help your accounting team out with the best production-grade onchain data.

📣 Launching today: the onchain data stack for audit, tax, and financial reconciliation. 🧮 ✅ Token Transfers — normalized across Ethereum EVM, Solana, Stellar, Ripple, Aptos, Sui, and Tempo. Every row traceable to source tx. One schema, every chain. ✅ Decoded Logs (EVM) — every contract event decoded and standardized. The evidence layer. ✅ Labels — add-on. Known addresses resolved to named entities. Help your accounting team out with the best production-grade onchain data.

Dune

42,536 Aufrufe • vor 1 Monat

What will the Moon look like on your birthday? With data from our Lunar Reconnaissance Orbiter, we’ve created a detailed animation that will let you see what phase the Moon will be in on your special day – or any other day in 2025.

What will the Moon look like on your birthday? With data from our Lunar Reconnaissance Orbiter, we’ve created a detailed animation that will let you see what phase the Moon will be in on your special day – or any other day in 2025.

NASA

777,568 Aufrufe • vor 1 Jahr

We can finally say it! is launching today! We spent a year building the data substrate for the agent economy, one MCP that allows your agents to query the world as a DB, so you can skip the data and focus on building what matters! Cala

We can finally say it! is launching today! We spent a year building the data substrate for the agent economy, one MCP that allows your agents to query the world as a DB, so you can skip the data and focus on building what matters! Cala

Elisenda Bou-Balust

18,499 Aufrufe • vor 1 Monat

AI Data Control - SDG Model V1 Live on SecureGPT! We are thrilled to announce that Selective Data Guard (SDG) v1 is now live on SecureGPT for our beta testers! SecureGPT has always ensured your personal information remains protected during AI interactions, but now, we're taking it a step further. With the SDG model, you gain the power to choose the data you wish to expose. SDG leverages proprietary algorithms to intelligently analyze and cluster similar entities, validating them against the custom rules you define. You now have the ability to specify what data to expose and what data to filter. This allows you to interact with AI agents seamlessly, with full control over your privacy. Your data, your rules—take control of AI interactions like never before!

AI Data Control - SDG Model V1 Live on SecureGPT! We are thrilled to announce that Selective Data Guard (SDG) v1 is now live on SecureGPT for our beta testers! SecureGPT has always ensured your personal information remains protected during AI interactions, but now, we're taking it a step further. With the SDG model, you gain the power to choose the data you wish to expose. SDG leverages proprietary algorithms to intelligently analyze and cluster similar entities, validating them against the custom rules you define. You now have the ability to specify what data to expose and what data to filter. This allows you to interact with AI agents seamlessly, with full control over your privacy. Your data, your rules—take control of AI interactions like never before!

ZKCrypt AI

12,416 Aufrufe • vor 1 Jahr

Introducing Instant Apps — your Tasklet agent can now build live, interactive apps for you on-demand. Describe what you need & get the perfect custom UI in seconds — connected to your real, live data. 🧵

Introducing Instant Apps — your Tasklet agent can now build live, interactive apps for you on-demand. Describe what you need & get the perfect custom UI in seconds — connected to your real, live data. 🧵

Tasklet

12,599,053 Aufrufe • vor 3 Monaten

Building Data Pipelines has levels to it: - level 0 Understand the basic flow: Extract → Transform → Load (ETL) or ELT This is the foundation. - Extract: Pull data from sources (APIs, DBs, files) - Transform: Clean, filter, join, or enrich the data - Load: Store into a warehouse or lake for analysis You’re not a data engineer until you’ve scheduled a job to pull CSVs off an SFTP server at 3AM! level 1 Master the tools: - Airflow for orchestration - dbt for transformations - Spark or PySpark for big data - Snowflake, BigQuery, Redshift for warehouses - Kafka or Kinesis for streaming Understand when to batch vs stream. Most companies think they need real-time data. They usually don’t. level 2 Handle complexity with modular design: - DAGs should be atomic, idempotent, and parameterized - Use task dependencies and sensors wisely - Break transformations into layers (staging → clean → marts) - Design for failure recovery. If a step fails, how do you re-run it? From scratch or just that part? Learn how to backfill without breaking the world. level 3 Data quality and observability: - Add tests for nulls, duplicates, and business logic - Use tools like Great Expectations, Monte Carlo, or built-in dbt tests - Track lineage so you know what downstream will break if upstream changes Know the difference between: - a late-arriving dimension - a broken SCD2 - and a pipeline silently dropping rows At this level, you understand that reliability > cleverness. level 4 Build for scale and maintainability: - Version control your pipeline configs - Use feature flags to toggle behavior in prod - Push vs pull architecture - Decouple compute and storage (e.g. Iceberg and Delta Lake) - Data mesh, data contracts, streaming joins, and CDC are words you throw around because you know how and when to use them. What else belongs in the journey to mastering data pipelines?

Building Data Pipelines has levels to it: - level 0 Understand the basic flow: Extract → Transform → Load (ETL) or ELT This is the foundation. - Extract: Pull data from sources (APIs, DBs, files) - Transform: Clean, filter, join, or enrich the data - Load: Store into a warehouse or lake for analysis You’re not a data engineer until you’ve scheduled a job to pull CSVs off an SFTP server at 3AM! level 1 Master the tools: - Airflow for orchestration - dbt for transformations - Spark or PySpark for big data - Snowflake, BigQuery, Redshift for warehouses - Kafka or Kinesis for streaming Understand when to batch vs stream. Most companies think they need real-time data. They usually don’t. level 2 Handle complexity with modular design: - DAGs should be atomic, idempotent, and parameterized - Use task dependencies and sensors wisely - Break transformations into layers (staging → clean → marts) - Design for failure recovery. If a step fails, how do you re-run it? From scratch or just that part? Learn how to backfill without breaking the world. level 3 Data quality and observability: - Add tests for nulls, duplicates, and business logic - Use tools like Great Expectations, Monte Carlo, or built-in dbt tests - Track lineage so you know what downstream will break if upstream changes Know the difference between: - a late-arriving dimension - a broken SCD2 - and a pipeline silently dropping rows At this level, you understand that reliability > cleverness. level 4 Build for scale and maintainability: - Version control your pipeline configs - Use feature flags to toggle behavior in prod - Push vs pull architecture - Decouple compute and storage (e.g. Iceberg and Delta Lake) - Data mesh, data contracts, streaming joins, and CDC are words you throw around because you know how and when to use them. What else belongs in the journey to mastering data pipelines?

Zach Wilson

16,688 Aufrufe • vor 1 Jahr

$Data encryption is now live on Veilnet. Available in @veilnet/mcp-server@0.3.0. Any blob — file, dataset, config, recovery codes, contract draft, research note, agent memory — can now be encrypted on your device, shipped to Veilnet as ciphertext, and fetched back later without the decryption key ever leaving your machine. Three new MCP tools are live: data_store({ label, data }) encrypt + store data on Veilnetdata_fetch({ id }) fetch + decrypt locallydata_list() list stored ids With labels kept encrypted, the flow is simple: user data → encrypted locally → ciphertext stored on Veilnet → key remains on user device → agent fetches when needed → local decryption onlyVeilnet sees encrypted blobs. Your AI agent gets persistent private memory and secure storage.The provider does not need the raw data. This works in Claude Code, Claude Desktop, Cursor, Continue, and Cline. Install: npm i -g @veilnet/mcp-server Bootstrap your key at: → Agent tab Then ask any MCP-aware agent:“store this encrypted on Veilnet.”Docs:docs.veilnet.toPrivate prompts protected what users ask. Private MCP protected what agents run. Wallet Context protected what agents read. Encrypted data storage now protects what agents remember and reuse. All powered by $VEILNET$

Data encryption is now live on Veilnet. Available in @veilnet/[email protected]. Any blob — file, dataset, config, recovery codes, contract draft, research note, agent memory — can now be encrypted on your device, shipped to Veilnet as ciphertext, and fetched back later without the decryption key ever leaving your machine. Three new MCP tools are live: data_store({ label, data }) encrypt + store data on Veilnetdata_fetch({ id }) fetch + decrypt locallydata_list() list stored ids With labels kept encrypted, the flow is simple: user data → encrypted locally → ciphertext stored on Veilnet → key remains on user device → agent fetches when needed → local decryption onlyVeilnet sees encrypted blobs. Your AI agent gets persistent private memory and secure storage.The provider does not need the raw data. This works in Claude Code, Claude Desktop, Cursor, Continue, and Cline. Install: npm i -g @veilnet/mcp-server Bootstrap your key at: → Agent tab Then ask any MCP-aware agent:“store this encrypted on Veilnet.”Docs:docs.veilnet.toPrivate prompts protected what users ask. Private MCP protected what agents run. Wallet Context protected what agents read. Encrypted data storage now protects what agents remember and reuse. All powered by $VEILNET

Veilnet

11,608 Aufrufe • vor 13 Tagen

The time is now: Walrus Mainnet is officially LIVE. We’re here to fundamentally transform how apps use and engage with data — empowering you to do more with your data, blob by blob. Ready to build? Go 👇

The time is now: Walrus Mainnet is officially LIVE. We’re here to fundamentally transform how apps use and engage with data — empowering you to do more with your data, blob by blob. Ready to build? Go 👇

Walrus 🦭/acc

67,501,756 Aufrufe • vor 1 Jahr