Failover Across Clouds

In this extended demo, Sahaj Saini shows you how Snowflake can replicate data and account metadata (like users, roles, compute resources, resource monitors, etc...) and failover these over across cloud providers on demand. For the fictional company, Style Me Up, he'll demonstrate how to set up replication with failover groups and trigger a failover and redirect client applications.

Get started with Salesforce and Heroku

Salesforce is an excellent CRM tool with many features to help you manage your business' workflows. Heroku is a cloud platform that enables developers to build, run and operate great apps. Whether you’re running a small business or managing 1,000 employees, either of these tools can be beneficial for your organization. Here are some ways to get started with Salesforce and Heroku.

Choosing the Right Evaluation Metric

Is your model ready for production? It depends on how it’s measured. And measuring it with the right metric can unlock even better performance. Evaluating model performance is a vital step in building effective machine learning models. As you get started on Continual and start building models, understanding evaluation metrics helps to productionize the best performing model for your use case.

Budget Forecasting: What It Is and How To Do It

We often hear different terms used to describe forward-looking versions of a company’s financial statements. People frequently use these terms interchangeably, with some having a deeper understanding of the nuances in terminology than others. Forward-looking financial documents may include budgets, projections, forecasts, and pro forma financials.

Top 5 ETL Tools For Heroku

When dealing with large data sets, it is not feasible to manage data transfers without tools that can efficiently scale. Heroku provides effective data management resources for managing data sets in your cloud data warehouse, but you still need tools that can make the ETL process simpler and as automated as possible. Here are the top five ETL tools for Heroku.

The Complete Guide to Using the Iguazio Feature Store with Azure ML - Part 4

Last time in this blog series, we provided an overview of how to leverage the Iguazio Feature Store with Azure ML in part 1. We built out a training workflow that leveraged Iguazio and Azure, trained several models via Azure's AutoML using the data from Iguazio's feature store in part 2. Finally, we downloaded the best models back to Iguazio and logged them using the experiment tracking hooks in part 3. In this final blog, we will.