Dashboard Reporting: What It Is, Why It Matters, Best Practices, and More
Use dashboard reporting to improve your results within available resources, without spending hours creating reports or exceeding your budget.
The Future of Machine Learning with Tal Shaked
Tal Shaked has a long history with machine learning and AI, and he's brought all that experience and energy to Snowflake. Felipe Hoffa talks to Tal about why he's excited about building on Snowflake, making ML accessible to everyone, and enabling customers to use ML/AI to help grow their businesses. Want the inside track on Snowflake's approach to ML and the newest tech announcements? Tune in to Snowflake's YouTube, LinkedIn, or Twitter channels June 14-16 for exclusive livestreams direct from Snowflake Summit in Las Vegas.
Cloudera's Applied ML Prototype Catalog Continues to Grow
Here at Cloudera, we’re committed to helping make the lives of data practitioners as painless as possible. For data scientists, we continue to provide new Applied Machine Learning Prototypes (AMPs), which are open source and available on GitHub. These pre-built reference examples are complete end-to-end data science projects. In Cloudera Machine Learning (CML), you can deploy them with the single click of a button, bringing data scientists that much closer to providing value.
Protecting Your Excel Reporting by Connecting Directly to Your SAP Data
SAP’s library of pre-defined reports for Finance and Controlling (FICO) is great for addressing some of the core tasks associated with finance and accounting. Those reports align well with accounting standards under GAAP and IFRS. Unfortunately, they rarely do a good job of addressing the kind of reporting needed to make informed managerial decisions.
Bringing BigQuery data into Vertex AI Workbench
Want to bring data from BigQuery into your Google Cloud AI models? In this video, we’ll show you how quickly you can start exploring your BigQuery data using Vertex AI Workbench. Watch to see how you can set up a single interface for your model development needs!
How to simplify AI models with Vertex AI and BigQuery ML
Did you know there is native integration between Vertex AI and BigQuery ML? With unified cloud data, your machine learning pipelines will have multiple options for training and storing/accessing data. Watch along and learn about the new native integrations between Vertex AI and BigQuery ML for Google Cloud.
The 4 benefits of retail analytics
Retail analytics is transforming the bricks and mortar and e-commerce landscapes. From Amazon drones delivering your favorite cupcake the moment your sweet tooth starts to tingle to your local shop stocking the new GoPro just before you set up on a new adventure. In this article, we will explore the guiding principles of how data can be used to improve your retail business. But we will also make it actionable.
How to Use Data Integration to Streamline Your Ecommerce Business
Our five key points: Most (if not all) Ecommerce businesses have a lot of data to keep track of. Sales data, inventory data, customer data, and more. If you're not careful, all that data can quickly become overwhelming. That's where data integration comes in. Data integration allows you to streamline your business by consolidating all your data into one easy-to-use system. This can help you make better decisions about your business and improve your overall efficiency.
Hello, Spark! An intro to Apache Spark using PySpark in the Cloud
If you’re new to the world of large-scale data analytics, this session is for you! We'll cover the basics of what problems Apache Spark can solve, why and when to use Spark, and how Spark enables efficient use of time and computing hardware. We’ll also demonstrate how easy it is to run a PySpark job in the public cloud using the Data Science Workbench and Cloudera Data Engineering Products.
The Easiest Way to Track Data Science Experiments with MLRun
As a very hands-on VP of Product, I have many, many conversations with enterprise data science teams who are in the process of developing their MLOps practice. Almost every customer I meet is in some stage of developing an ML-based application. Some are just at the beginning of their journey while others are already heavily invested. It’s fascinating to see how data science, a once commonly used buzz word, is becoming a real and practical strategy for almost any company.