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Tackling AI’s data challenges with IBM databases on AWS

IBM Journey to AI blog

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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dbt Labs’ Coalesce 2023 Recap

phData

Join us as we navigate the key takeaways defining the future of data transformation. dbt Mesh Enterprises today face the challenge of managing massive, intricate data projects that can slow down innovation. In mid-2023, many companies were wrangling with more than 5,000 dbt models. Figure 5: dbt Cloud CLI.

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How to Ingest Salesforce Data into Snowflake Using Salesforce Sync Out

phData

Salesforce Sync Out is a crucial tool that enables businesses to transfer data from their Salesforce platform to external systems like Snowflake, AWS S3, and Azure ADLS. Warehouse for loading the data (start with XSMALL or SMALL warehouses).

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Journey to AI blog

Overall, this partnership enables the retailer to make data-driven decisions, improve supply chain efficiency and ultimately boost customer satisfaction, all in a secure and scalable cloud environment. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

AWS 79
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IBM to help businesses scale AI workloads, for all data, anywhere

IBM Journey to AI blog

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data?

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How to Build a Data Mesh in Snowflake

phData

A data mesh is a decentralized approach to data architecture that’s been gaining traction as a solution to the challenges posed by large and complex data ecosystems. It’s all about breaking down data silos, empowering domain teams to take ownership of their data, and fostering a culture of data collaboration.