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Unlock gen AI’s potential in Retail: Start with a cloud data foundation

Snowflake

There’s no question which technology everyone’s talking about in retail. Since then, we’ve seen an explosion of new and improved gen AI models hitting the market, opening powerful new use cases across retail. Retail has a long history of leading on AI. An advisor for retail employees It’s an exciting time.

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5 Steps to Data Diversity: More Diverse Data Makes for Smarter AI

Snowflake

An end-user-facing data catalog or marketplace can improve discoverability and access. Transform unstructured data to expand available internal data. To ensure that all data is made available, organizations must adopt tools to transform unstructured data into usable formats.

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Get to Know Your Retail Customer: Accelerating Customer Insight and Relevance

Cloudera

There are lessons to be learned from the brick and mortar or pure-play digital retailers that have been successful in the Covid-19 chaos. Since the bulk of the retail season is upon us, I wanted to reflect on the four basic pillars of retail that we see successful companies embody. Personalized Interactions Driven by Data.

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Maximizing Supply Chain Agility through the “Last Mile” Commitment

Cloudera

Now that we have established tailored demand, we need to figure out how to fulfill demand though a robust and capable supply chain, let’s drive into building an agile retail supply chain. Data today has a shelf life much like produce and needs to be updated in real-time to be relevant.

Retail 91
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Ingest Data Faster, Easier and Cost-Effectively with New Connectors and Product Updates

Snowflake

Bringing in batch and streaming data efficiently and cost-effectively Ingest and transform batch or streaming data in <10 seconds: Use COPY for batch ingestion, Snowpipe to auto-ingest files, or bring in row-set data with single-digit latency using Snowpipe Streaming.

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Streaming Edge Data Collection and Global Data Distribution

Cloudera

With support for more than 400 processors, CDF-PC makes it easy to collect and transform the data into the format that your lakehouse of choice requires.

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Data Warehouse vs. Data Lake

Precisely

We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data. They may want to look at those numbers on a daily or weekly basis.