Artwork

コンテンツは EM360 によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、EM360 またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal
Player FM -ポッドキャストアプリ
Player FMアプリでオフラインにしPlayer FMう!

Like Peanut Butter and Jam: the Synergies of AI and Master Data

25:15
 
シェア
 

Manage episode 453426640 series 1432815
コンテンツは EM360 によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、EM360 またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal

The convergence of Master Data Management (MDM) and Artificial Intelligence (AI) is transforming how businesses harness data to drive innovation and efficiency. MDM provides the foundation by organising, standardising, and maintaining critical business data, ensuring consistency and accuracy across an organisation.

When paired with AI, this clean and structured data becomes a powerful asset, enabling advanced analytics, predictive insights, and intelligent automation. MDM and AI help businesses uncover hidden patterns, streamline operations, and make more informed decisions in real-time.

By integrating MDM with AI, organisations can move beyond simply managing data to actively leveraging it for competitive advantage. AI algorithms thrive on high-quality, well-structured data, and MDM ensures just that—minimising errors and redundancies that could compromise results. This synergy empowers companies to personalise customer experiences, optimise supply chains, and respond proactively to market changes.

In this episode, Kevin Petrie, VP of Research at BARC US, speaks to Jesper Grode, Director of Product Innovation at Stibo Systems, about the intersection between AI and MDM.

Key Takeaways:

  • AI and master data management should be integrated for better outcomes.
  • Master data improves the quality of inputs for AI models.
  • Accurate data is crucial for training machine learning models.
  • Generative AI can enhance product launch processes.
  • Prompt engineering is essential for generating accurate AI responses.
  • AI can optimise MDM processes and reduce operational costs.
  • Fast prototyping is vital for successful AI implementation.

Chapters:

00:00 - Introduction to AI and Master Data Management

02:59 - The Synergy Between AI and Master Data

05:49 - Generative AI and Master Data Management

09:12 - Leveraging Master Data for Small Language Models

11:58 - AI's Role in Optimizing Master Data Management

14:53 - Best Practices for Implementing AI in MDM

  continue reading

129 つのエピソード

Artwork
iconシェア
 
Manage episode 453426640 series 1432815
コンテンツは EM360 によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、EM360 またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal

The convergence of Master Data Management (MDM) and Artificial Intelligence (AI) is transforming how businesses harness data to drive innovation and efficiency. MDM provides the foundation by organising, standardising, and maintaining critical business data, ensuring consistency and accuracy across an organisation.

When paired with AI, this clean and structured data becomes a powerful asset, enabling advanced analytics, predictive insights, and intelligent automation. MDM and AI help businesses uncover hidden patterns, streamline operations, and make more informed decisions in real-time.

By integrating MDM with AI, organisations can move beyond simply managing data to actively leveraging it for competitive advantage. AI algorithms thrive on high-quality, well-structured data, and MDM ensures just that—minimising errors and redundancies that could compromise results. This synergy empowers companies to personalise customer experiences, optimise supply chains, and respond proactively to market changes.

In this episode, Kevin Petrie, VP of Research at BARC US, speaks to Jesper Grode, Director of Product Innovation at Stibo Systems, about the intersection between AI and MDM.

Key Takeaways:

  • AI and master data management should be integrated for better outcomes.
  • Master data improves the quality of inputs for AI models.
  • Accurate data is crucial for training machine learning models.
  • Generative AI can enhance product launch processes.
  • Prompt engineering is essential for generating accurate AI responses.
  • AI can optimise MDM processes and reduce operational costs.
  • Fast prototyping is vital for successful AI implementation.

Chapters:

00:00 - Introduction to AI and Master Data Management

02:59 - The Synergy Between AI and Master Data

05:49 - Generative AI and Master Data Management

09:12 - Leveraging Master Data for Small Language Models

11:58 - AI's Role in Optimizing Master Data Management

14:53 - Best Practices for Implementing AI in MDM

  continue reading

129 つのエピソード

Tüm bölümler

×
 
Loading …

プレーヤーFMへようこそ!

Player FMは今からすぐに楽しめるために高品質のポッドキャストをウェブでスキャンしています。 これは最高のポッドキャストアプリで、Android、iPhone、そしてWebで動作します。 全ての端末で購読を同期するためにサインアップしてください。

 

クイックリファレンスガイド

探検しながらこの番組を聞いてください
再生