Data Science vs Data Analytics: What’s the Difference?
Introduction Organizations are constantly looking for ways to leverage their data to save time, reduce costs, and accelerate innovation. However, there are many different approaches to consider for generating valuable insights with data. By understanding which approach better suits specific use cases, you can maximize the impact of future data and AI initiatives. Data science […]
Comparing Data Science and AI: Where They Overlap and Differ
Introduction Two terms that often arise in discussions around leveraging data are data science and machine learning. While these concepts are closely related (and sometimes mistaken to be the same), it’s important to understand the differences between data science and machine learning and their distinct characteristics and applications. Understanding the ways in which data science and machine Machine learning is a […]
Automate Your Analysis with Snowflake and Anaconda
About This Webinar Learn the power of Snowflake SQL and Anaconda Python packages to simplify tasks that often require advanced tools or technical expertise. Get straightforward examples that help you implement these workflows with confidence. Understand how Snowflake can streamline analytics, unlocking new capabilities. Key topics include How to segment customers effectively (using requests) How […]
Top 14 Enterprise AI Use Cases in 2025
In recent years, AI has become an essential component of many companies’ technology stacks. While there’s no shortage of hype surrounding AI tools, understanding their real-world applications is key for organizations looking to maximize their ROI. This article explores practical examples of enterprise AI use cases across industries, offering insights to help you identify how […]
The Future of Data Science: 8 Trends to Watch
Data science is evolving at a breakneck pace, with AI quickly transforming the way businesses operate and deliver value to customers. This rapid change brings fresh challenges and exciting opportunities for both newcomers and seasoned data pros. To thrive and stay competitive in this dynamic landscape, keeping up with these advancements is essential. That’s why […]
State of Data Science 2024 Report
State of Data Science 2024 Report AI and Open Source at Work This 7th annual report reveals insights about the data science community’s demographics, industry use cases, and trends related to artificial intelligence (AI), and open source at work. Learn more about these themes in the report: AI-Powered Transformation 87% of practitioners are increasing AI […]
Building an OSS Governance Program for ML in the Enterprise
About this Webinar Open-source software (OSS) is at the heart of many of the innovations in machine learning (ML) due to its accessibility, flexibility, and active community support. As a result, many enterprise organizations are adopting or seeking to adopt OSS into their operations, product development, and marketable solutions. However, as with any software, OSS […]
Graph Analytics for Data Scientists
Analyzing data using conventional statistical methods involves looking at tabular data where data points are independent of each other, e.g. a person’s age is independent of any other person’s age. These approaches limit the insight that can be gained as there’s often knowledge hidden in how one data point relates to another. For example, two […]
Deploying Machine Learning to Apple Devices with coremltools
About this Webinar Machine learning has gone beyond the data center and is now being deployed to the devices we carry with us every day. It is becoming increasingly important for data scientists to understand how to prepare models for use on mobile devices and wearables. In this on-demand webinar, we will show you how […]
Efficient Data Preparation with Python
About this report Data discovery and data preparation have always been among the most time-intensive steps of a research project and for good reason: If there are unaddressed errors in data, or if the wrong version of data is used, there will be errors in the resulting analysis or model. In some cases these errors […]