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SNOWFLAKE LAUNCHES DATA CLOUD FOR RETAIL INDUSTRY

Shubham Sharma@shubham_719
March 28, 2022 6:00 AM
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Image Credit: Reuters

To further strengthen our commitment to providing industry-leading coverage of
data technology, VentureBeat is excited to welcome Andrew Brust and Tony Baer as
regular contributors. Watch for their articles in the Data Pipeline.

In another move to help enterprises better mobilize their data, Snowflake has
announced the launch of data cloud for retail.

The offering comes days after the launch of healthcare and life sciences (HCLS)
data cloud and aims to serve as a dedicated platform to address the challenges
retail industry stakeholders – retailers, manufacturers, distributors and
consumer packaged goods (CPG) vendors – face while trying to extract value from
their datasets. 

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Not all Data is Created Equal Personalization in the time of a global privacy
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TOP ARTICLES







Not all Data is Created Equal Personalization in the time of a global privacy
movement


“The way that consumers, retailers and brands interact is quickly changing, and
the data that organizations need to understand and adapt is not as available or
easy to work with as it needs to be. Whether a business is working to deliver
more personalized purchase experiences or adjusting amid supply chain, shortage,
or inflation challenges – among others – the needed data is spread across
internal and external stakeholder,” Rosemary Hua, Snowflake’s GTM lead for
retail and CPG industries, told VentureBeat.


HOW DOES RETAIL DATA CLOUD HELP?

The new Retail Data Cloud solves this challenge by bringing together
industry-specific datasets and various partner solutions on a single platform.
This way, it drives industry-wide collaboration, enabling the stakeholders to
not only access their own data (which can be siloed due to legacy systems) but
also new information from other, external sources. 

“Our new Retail Data Cloud breaks down data silos within and across
organizations and offers retail organizations the specific AI and analytics
tools they need to make quick, insight-driven decisions to overcome obstacles
and adapt to trends across functions – from manufacturing to logistics,
marketing, merchandising and beyond. In short, regardless of where precisely in
the retail ecosystem an organization lives, we’re making more data more
available and easier to work with so they can optimize every part of their
business,” Hua said.

Snowflake notes that enterprises using the Retail Data Cloud can share data
across the ecosystem in real-time across all major public cloud platforms. To
ensure strict data governance and regulatory compliance, the company employs a
suite of easily managed security capabilities, including data clean rooms,
double-blind joins, restricted queries, centralized RBAC (role-based access
control) and row/columnar level obfuscation that enables data to be shared
without movement and risk of revealing personally identifiable information.


SOLUTIONS FOR INDUSTRY-SPECIFIC PROBLEMS

On the partner solutions’ side, the Retail Data Cloud provides enterprises with
applications/products, curated by Snowflake’s technology, consulting and data
partners, to solve industry-specific problems and reduce the time to value.

“We are announcing new joint solutions that are being brought to the market
starting Monday, March 28th,” Hua said.

“One such example is AWS bringing Vendor Central and improved PO forecasting
data onto Snowflake for consumer product brands that sell through Amazon.com’s
marketplace. Another example is Numerator (Snowflake data marketplace partner)
bringing a new product called Secure Enrich, which is built on Snowflake data
clean room. Retailers and brands will be able to consume and join these new
datasets directly in their native Snowflake environment, making it seamless to
manage inventory and enrich customer data,” she added.

Currently, the Retail Data Cloud is being used by players such as 84.51°,
Albertsons, Kraft Heinz and Rakuten. Overall, Snowflake claims more than 1,000
retail and CPG companies have signed up for its platform, which supports six key
workloads – data engineering, data sharing, data warehousing, data application
development, data lake and data science.

Notably, a similar offering has also been curated by Databricks and Dremio as
part of what they call the data lakehouse approach. Databricks, in particular,
has been strengthening its offering with partner integrations and
vertical-specific offerings. The company was last valued at $38 billion, while
Snowflake’s current (as of March 25) market capitalization stands at about $66
billion.

Author
Shubham Sharma
Topics
Data infrastructure







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