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Snowflake Data Clean Rooms: Securely Collaborate to Unlock Insights and Value

In December 2023, Snowflake announced its acquisition of data clean room technology provider Samooha. Samooha’s intuitive UI and focus on reducing the complexity of sharing data led to it being named one of the most innovative data science companies of 2024 by Fast Company. Now, Samooha’s offering is integrated into Snowflake and launched as Snowflake Data Clean Rooms, a Snowflake Native App on Snowflake Marketplace, generally available to customers in AWS East, AWS West and Azure West.

The Essential Role of a Data Steward in Modern Business Intelligence

At the intersection of data management and business strategy lies the data steward. Tasked with safeguarding data integrity and enabling informed business intelligence, data stewards are fundamental to modern organizations. They ensure data is clean, compliant, and utilized effectively. Our exploration will detail the crucial role of data stewardship in navigating and leveraging an enterprise’s data landscape.

Data Architecture and Strategy in the AI Era

At a time when AI is exploding in popularity and finding its way into nearly every facet of business operations, data has arguably never been more valuable. More recently, that value has been made clear by the emergence of AI-powered technologies like generative AI (GenAI) and the use of Large Language Models (LLMs).

Best CFO KPIs and Dashboards for the 2024 CFO

What is kpi in business? A CFO Key Performance Indicator (KPI) or metric is a quantifiable high level measure of financial performance. These KPIs can be considered a specific subset of financial KPIs, used to help a CFO make informed decisions that steer their company in the right direction. These performance metrics can also be used to measure a company’s financial performance relative to competitors in the same industry.

Snowflake Invests in Observe to Expand Observability in the Data Cloud

As organizations seek to drive more value from their data, observability plays a vital role in ensuring the performance, security and reliability of applications and pipelines while helping to reduce costs. At Snowflake, we aim to provide developers and engineers with the best possible observability experience to monitor and manage their Snowflake environment. One of our partners in this area is Observe, which offers a SaaS observability product that is built and operated on the Data Cloud.

Predict Known Categorical Outcomes with Snowflake Cortex ML Classification, Now in Public Preview

Today, enterprises are focused on enhancing decision-making with the power of AI and machine learning (ML). But the complexity of ML models and data science techniques often leaves behind organizations without data scientists or with limited data science resources. And for those organizations with strong data analyst resources, complex ML models and frameworks may seem overwhelming, potentially preventing them from driving faster, higher-quality insights.

Connecting Space and Data: NASA's Asteroid Dust Quest and AI Innovation

Perhaps it's the awe-inspiring films about space exploration (my personal favorite – Apollo 13) that evoke the image of NASA as a place buzzing with activity, filled with screens displaying data, charts, and ALWAYS a big countdown clock. However, one of NASA's most recent challenges may surprise you - the task of cracking open a billion-dollar canister filled with ancient asteroid dust.

insightsoftware Platform - Multi Environment Feature

Efficiency means doing things right. The multi-environment feature introduced in the insightsoftware Platform underlines this. It enables you to assign licenses per environment to a specific user, ensuring the most efficient distribution your licenses that suits your unique requirements.

Qlik AutoML Update - March 2024

Automated free text feature engineering uses sophisticated algorithms under the hood to allows far better prediction from free text fields. This complements the date feature engineering capability we released last year, which automatically parses dates into usable features. Organizations now have role-based access control for AutoML users. We’ve added two new user roles to support AutoML – experiment contributors and deployment contributors, which can be assigned to specific users or groups. With this, you can now control and limit access to AutoML to the right types of users.