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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.

What is the Augmented Consumer? Understanding Users of AI Analytics

The rise of AI-powered features in today’s analytics solutions has increasingly displaced our reliance on dashboards by making it easier for business people to analyze their data. With this rising paradigm shift, a new label has emerged: The augmented consumer. On a surface-level, the word ‘augmented’ may conjure up a variety of different interpretations. AI-based dashboard assistants? Natural language-led reporting?

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.

Don't Get Left Behind in the AI Race: Your Easy Starting Point is Here

The ongoing progress in Artificial Intelligence is constantly expanding the realms of possibility, revolutionizing industries and societies on a global scale. The release of LLMs surged by 136% in 2023 compared to 2022, and this upward trend is projected to continue in 2024. Today, 44% of organizations are experimenting with generative AI, with 10% having already implemented it in operational settings. Companies must act now in order to stay in the AI Race.

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.