Discover the latest in AI data storage technology, from reliable SQL databases to cutting-edge graph computing. Dive in to explore how modern databases are revolutionising data science and analytics.
- In large enterprises, multiple groups from different geographies and business units face common dilemmas, but knowledge graphs are boosting innovation initiatives.
- Data quality struggles are real in enterprises, and dbt Labs is helping organisations transform their data.
- Knowledge graphs, combined with LLMs, are enhancing AI efficiency and trust, according to data governance expert Malcolm Chisholm.
- Kwaai’s Personal AI OS offers a new way to interact with technology and personal data. Insights from conversations with experts reveal fascinating details.
In large enterprises, different groups from various regions and business units often face common issues. However, knowledge graphs are playing a massive role in boosting innovation initiatives.
Enterprises are constantly battling with data quality struggles. In March 2024, dbt Labs, a freemium platform and tools provider, aimed at aiding organisations with their data transformation.
Data governance expert Malcolm Chisholm posed an interesting question on LinkedIn: ‘Is the Cloud the biggest boost to AI efficiency and trust?’ He highlighted the significant role of knowledge graphs and LLMs in this domain.
During a chat on the AI Think Tank podcast, Kwaai’s Toby Morning and Karsten Wade shared insights on their Personal AI OS. They envision an AI that respects privacy, enhances autonomy, and redefines the interaction between technology and personal data.
In a world where data is constantly evolving, modern AI data stores and databases are at the forefront, meeting the needs of data science and analytics. Whether it’s SQL workhorses or advanced graph computing, the innovation is unsurpassed.
Modern AI data stores are crucial in revolutionising the data science and analytics landscape.
Source: Datasciencecentral
