Assisted Insights is a powerful tool built-in the Yellowfin embedded analytics suite that provides organizations with automated and intuitive insights derived from their data. Using automation and machine learning capabilities, Yellowfin Assisted Insights helps users to uncover hidden patterns, trends, and correlations in their data, enabling them to make better informed and data-driven business decisions.

Data integration is essential for analytics, regression analysis and your first forays into generative AI.

Are you trying to move your data from Google Analytics to BigQuery? Are you confused about how to do this easily? If yes, then you are in the right place. This blog covers various methods to connect Google Analytics to BigQuery in a few simple steps.

Cloud transformation is ranked as the cornerstone of innovation and digitalization. The legacy IT infrastructure to run the business operations—mainly data centers—has a deadline to shift to cloud-based services. Agility, innovation, and time-to-value are the key differentiators cloud service providers (CSP) claim to help organizations speed up digital transformation projects and business objectives.

We are excited to announce the general availability of Snowflake Event Tables for logging and tracing, an essential feature to boost application observability and supportability for Snowflake developers. In our conversations with developers over the last year, we’ve heard that monitoring and observability are paramount to effectively develop and monitor applications. But previously, developers didn’t have a centralized, straightforward way to capture application logs and traces.

To ensure a frictionless AI/ML development lifecycle, ClearML recently announced extensive new capabilities for managing, scheduling, and optimizing GPU compute resources. This capability benefits customers regardless of whether their setup is on-premise, in the cloud, or hybrid. Under ClearML’s Orchestration menu, a new Enterprise Cost Management Center enables customers to better visualize and oversee what is happening in their clusters.

Every business that analyzes their operational (or transactional) data needs to build a custom data pipeline involving several batch or streaming jobs to extract transactional data from relational databases, transform it, and load it into the data warehouse. In this post, we show how you can leverage Amazon Aurora zero-ETL integration with Amazon Redshift and ThoughtSpot for GenAI driven near real-time operational analytics.