Беседы о бизнес-аналитике Fluent использует искусственный интеллект для упрощения анализа данных.
Британский стартап Fluent собрал 7,5 миллионов долларов на сид-раунде для использования LLM-технологий в бизнес-базах данных, упрощающих процесс запросов.
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LLMs will help streamline clunky business intelligence tools to be more user-friendly and quicker to use.
🔖 Summary: Business intelligence (BI) tools have become essential for large organizations to gain insights into their operations. However, these tools often require technical skills and take time to set up and use. UK startup Fluent aims to change that by leveraging AI-based Large Language Models (LLMs) to make business databases more accessible and easily queryable. By acting as a “conversational layer” on top of existing data warehouses, Fluent translates natural language queries into SQL and delivers fast, accurate answers to users, regardless of their technical skills or business context.
The Lumbering Giants of Business Intelligence
Large organizations have long relied on “business intelligence” (BI) tools to make sense of the vast amounts of data generated within their operations. These tools connect to business databases, use SQL to create visualizations, and build out BI dashboards. Companies like Tableau, Power BI, Looker, and QuickSight dominate this space, offering powerful solutions to analyze and understand business data.
Fluent Takes on the Challenge with AI-Powered Conversational Analytics
Fluent, a UK-based startup, has recently secured a $7.5 million seed investment to revolutionize the BI landscape. Rather than adding another heavyweight tool to the mix, Fluent wants to be a “conversational layer” powered by AI. By utilizing Large Language Models (LLMs), Fluent aims to make data warehouses easier to interrogate for the average person.
The key idea behind Fluent’s approach is to enable anyone, regardless of technical skills or business context, to ask questions in plain English and obtain valuable insights from their data. By translating natural language queries into SQL and generating quick, accurate responses, Fluent helps users overcome the challenges of traditional BI tools. This conversational approach significantly shortens response times, empowering users to extract insights on their own terms.
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Implications and Benefits: Faster Insights, More Engaged Teams
Fluent’s conversational approach to BI analytics has far-reaching implications. By reducing the barriers between users and their data, Fluent enables faster decision-making processes and increases overall data utilization in organizations. Consultants, for example, can move from waiting weeks for insights to receiving answers in just seconds. This means they can ask more questions and leverage data effectively in their work, ultimately driving better outcomes.
One of Fluent’s clients, Bain & Company, has already benefitted from their platform. Ian Weber, a partner at Bain & Company, emphasized how Fluent allows their consultants to quickly obtain the precise insights they need from large complex datasets. It eliminates the dependency on pre-built data dashboards and opens the door to more customized and specific queries.
The Rise of Natural Language Querying
The emergence of natural language querying is a recent development in the BI market. While there are existing players like Metabase and Einblick, Fluent brings a unique focus on the business market, making it stand out from the competition. Einblick leans toward technical users within data teams, whereas Fluent emphasizes serving the broader business audience.
Thoughtspot, another major player in the space, has also ventured into natural language querying. This highlights the growing recognition of conversational analytics as a powerful tool to democratize data access and exploration.
Q&A: Addressing Readers’ Concerns
Q: How does Fluent’s conversational layer differ from traditional BI tools?
A: Fluent acts as an AI-powered “conversational layer” on top of a company’s data warehouse, making data easily accessible through natural language queries. Unlike traditional BI tools that require technical skills and time-consuming setup, Fluent allows anyone to ask questions in plain English and receive accurate insights quickly.
Q: Can Fluent handle complex and specific queries that may not be covered by pre-built data dashboards?
A: Absolutely! Fluent’s platform leverages Large Language Models (LLMs) to handle complex queries and deliver precise insights from large and intricate datasets. This means that even if queries are highly specific or require detailed analysis, Fluent can generate the accurate answers needed.
Q: Will Fluent’s approach replace data teams or make their roles redundant?
A: Not at all! Fluent’s goal is to empower non-technical users to access and explore data more effectively. Data teams still play a crucial role in managing and maintaining data warehouses, ensuring data quality, and supporting more advanced analytics tasks. Fluent complements their work by simplifying data access and fostering a more data-driven culture across organizations.
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Взгляд в будущее: Будущее разговорного бизнес-интеллекта
AI-подход Fluent – это только начало того, что предполагает будущее для разговорного бизнес-интеллекта. Поскольку развитие естественного языкового запроса продолжается, мы можем ожидать еще более значительных достижений в доступности данных, анализе и принятии решений. Потенциальный рынок для решений, подобных Fluent, огромен, причем глобальный рынок бизнес-интеллекта прогнозируется достичь более 54 миллиардов долларов к 2030 году.
Поскольку ИИ и крупные языковые модели (LLMs) становятся более широко применяемыми в области бизнес-интеллекта, мы можем ожидать дальнейших нарушений и инноваций. Разговорная аналитика, вероятно, станет стандартом в бизнес-операциях, давая организациям всех размеров возможность свободно использовать свои данные и обрести конкурентные преимущества.
Ссылки
- Отчет о глобальном рынке бизнес-интеллекта
- Tableau: Мощный инструмент визуализации данных Salesforce
- Power BI: Инструмент бизнес-аналитики и визуализации данных Microsoft
- Looker: Платформа Google для бизнес-аналитики и аналитики данных
- QuickSight: Инструмент бизнес-интеллекта на основе облачных вычислений Amazon
- Metabase: Open-source приложение для аналитики и бизнес-интеллекта
- Einblick: Приобретен Databricks, ориентирован на будущий рост
- ThoughtSpot: Инновации с использованием естественного языкового запроса в бизнес-аналитике
Общайтесь с нами в комментариях ниже! Поделитесь своими мыслями о разговорном бизнес-интеллекте и как вы представляете его воздействие на организации. Не забудьте нажать на кнопку “Поделиться”, чтобы распространить знания и вдохновить других принять будущее, основанное на данных! ✨🚀📊
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