Retrieval-augmented generation (RAG) techniques are employed to combine the generative power of LLMs with the retrieval ...

Interest is growing in the data mesh approach—an organizational and architectural approach to share, access, and manage analytics data in complex and large-scale environments where data ownership is ...

According to TDWI research, generative AI will be the top analytics investment area in 2025, unlocking fresh innovations and perspectives and creating valuable opportunities for organizations. For ...

Data engineering is essential to achieving innovation in AI, analytics, and data-rich business applications. Data engineers ensure that data is fit for today’s data-driven organizations. Data ...

Self-service analytics continues to be a top priority for organizations, according to TDWI research. Yet many teams still struggle with adoption. Business users want direct access to data to support ...

Modern business depends on sophisticated decision support, advanced analytics, and artificial intelligence (AI) applications. Therefore, modern businesses need next-generation data intelligence ...

Successful modern data infrastructure encompasses more than just storage and staging options. Organizations must take a holistic approach with key data management practices including data quality, ...

Visit the CBIP group at tdwi.org/linkedin/cbip. Since 2003, TDWI and the ICCP have provided the CBIP certification to global business and industry through their ...