Narrator的封面图片
Narrator

Narrator

软件开发

Brooklyn,NY 3,165 位关注者

Answer data requests in minutes with only one table

关于我们

Narrator powers self-service analytics across all your data. It allows anyone to get answers in minutes instead of weeks, using the same data as your data team. Narrator helps your data team build a full customer 360 that covers every interaction customers have with your business (opened emails, paid invoices, new support tickets, etc...), which provides the foundation for a comprehensive self-service experience for your company. Anyone can answer quick questions and self-serve requests across all your data without needing SQL and then integrate that data with your existing tools (spreadsheets, BI, and SaaS tools like email providers).

网站
https://www.narratordata.com
所属行业
软件开发
规模
11-50 人
总部
Brooklyn,NY
类型
私人持股
创立
2017
领域
Data Engineering、Analytics、Artificial Intelligence和Insights

地点

Narrator员工

动态

  • Narrator转发了

    查看Ahmed Elsamadisi的档案

    Founder/CEO @ OpLevel AI | Creator of the Activity Schema?? | Forbes 30u30 | YC S19

    Who is Text-To-SQL for? I've been talking to a lot of companies using AI, and there's this persistent feedback: "Text-to-SQL isn't for me." So, who is it for? Here’s what I've learned and would love to hear your thoughts too. - End Users: These are the business folks who don’t know SQL but want to ask questions in natural language and get answers directly. They love the idea of bypassing the data team, but hit a wall when it comes to verifying if the SQL generated is correct. They end up asking the data team anyway or just not trusting it. - SQL Analysts: These are the data engineers and analysts who know SQL but want to speed up their workflow. The dream here is having SQL auto-generated to save time. But the reality? The SQL often doesn’t match their style, is hard to read, and can take more time to debug than writing it from scratch. - The Dilemma: Text-to-SQL aims to bridge the gap between natural language and data querying, but it often falls short in both camps. The initial promise is there, but the implementation lacks polish, leaving many users skeptical and reverting to traditional methods. We need to rethink who exactly benefits from text-to-SQL and refine the approach to truly add value. If you’ve cracked the code or have a unique use case, I'd love to hear about it! Like, share, and comment if you found this insightful – let’s keep the conversation going! Full Video: https://lnkd.in/gR5sryB9 #genai #data #texttosql #sql #datamodelling #ai

    Who is Text-to-SQL for?

    Who is Text-to-SQL for?

    https://www.loom.com

  • 查看Narrator的组织主页

    3,165 位关注者

    Interested in AI SQL agents or Text to SQL. Ahmed Elsamadisi talks about the challenges with their scalability here

    查看Ahmed Elsamadisi的档案

    Founder/CEO @ OpLevel AI | Creator of the Activity Schema?? | Forbes 30u30 | YC S19

    Why do AI SQL agents not scale? SQL agents struggle to scale due to challenges in contextual understanding and metadata balance, making it hard for them to reliably convert questions into accurate SQL queries. Key points ?? 1. SQL Agent Definition: SQL agents convert written questions into SQL queries. Their complexity arises from the need to understand and navigate large, nuanced datasets. 2. Context Limitations: Human analysts remember context and nuances from conversations and interactions. SQL agents struggle because providing extensive context makes them inconsistent and prone to confusion. 3. RAG (Retrieval-Augmented Generation) Approach: RAG involves providing SQL agents with only relevant, similar context, but this often fails due to the nuanced nature of data. 4. Metadata Issues: Effective use of metadata (descriptions of tables and columns) is crucial but challenging. Poorly written metadata can cause confusion, while overly detailed metadata can obscure key differences. 5. Balancing Metadata: Companies often struggle to balance metadata detail, which impacts the SQL agent's ability to understand and utilize data effectively. Full Video Answer: https://lnkd.in/gGM8Z8WK #data #datamodelling #ai #genai #sqlagents #agents #sql #datascience

    Why SQL agents don’t scale?

    Why SQL agents don’t scale?

    https://www.loom.com

  • 查看Narrator的组织主页

    3,165 位关注者

    Ahmed Elsamadisi is back, help guide him on how to share content you find interesting.

    查看Ahmed Elsamadisi的档案

    Founder/CEO @ OpLevel AI | Creator of the Activity Schema?? | Forbes 30u30 | YC S19

    I am back! It has been a while since I posted on LinkedIn, but I am excited to start sharing content. I would love some guidance on how to make these posts interesting, helpful, and timely. METHOD: - Short posts - Long detailed posts - Videos of me discussing a topic - Short post with blog post CONTENT: - Data Modeling - AI on top of data warehouse - Business questions that should be answered - Industry-specific insights - Implementation details in data + AI (ex. consistency vs context size) - Cost-saving approaches in data warehousing Please comment with your recommendations, thoughts, or desires. If you want my thoughts on anything else, please let me know. If you want me to stop sharing, please share why as well. #data #ai #modelling #datawarehouse

  • 查看Narrator的组织主页

    3,165 位关注者

    Unlocking the Power of Event Data: Why Every Company Should Prioritize It ?? In today's data-driven landscape, companies are constantly seeking ways to gain deeper insights and make smarter decisions. Amidst this quest for knowledge, one treasure trove often overlooked is event data. ?? Event data is the heartbeat of your business, capturing every interaction, transaction, and engagement across platforms and channels. ?? By harnessing event data, companies can uncover valuable patterns, trends, and correlations that traditional data sources may miss. ?? Whether it's understanding customer behavior, optimizing marketing campaigns, or enhancing product experiences, event data holds the key to unlocking actionable insights at scale. ?? Don't underestimate the power of event data! Embrace it, leverage it, and watch your business soar to new heights of success. #DataDriven #EventData #BusinessInsights #MavisAI #Narrator #Data

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