Analytics

Build AI-driven near-real-time operational analytics with Amazon Aurora zero-ETL integration with Amazon Redshift and ThoughtSpot

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.

COMING SOON: Uncover Opportunities In Your Data With New Visualizations and More Powerful Charts

Data is not just a buzzword; it’s a strategic asset. From sales figures to customer engagement metrics, data plays an important role in helping your business grow. But here’s the catch: without the right visualization, uncovering actionable insights can be a challenge. For example, let’s say you want to know which marketing channels are driving the highest amount of website traffic and conversions.

Kensu extends Data Observability support for Microsoft users with its Azure Data Factory integration

Kensu announces an integration with Azure Data Factory, the serverless data integration service. With this integration, teams can observe data within their Azure Data Factory pipelines and receive valuable insights into data lineage, schema changes, and performance metrics. As one of the few Data Observability providers available to support customers on-premise, multi-cloud, or hybrid environments, Kensu is broadening access to Data Observability for Microsoft users.

Prevent data issues from cascading and deliver reliable insights with Kensu + Azure Data Factory

38% of data teams spend between 20% and 40% of their time fixing data pipelines¹. Combating these data failures is a costly and stressful activity for those looking to deliver reliable data to end users. Organizations using Azure Data Factory can now benefit from the integration with Kensu to expedite this process. Their data teams can now observe data within their Azure Data Factory pipelines and receive valuable insights into data lineage, schema changes, and performance metrics.

Think Like a Data Scientist: The Importance of Building a Data-Driven Company Culture

We’ve all heard that data helps businesses make better decisions. The good news? This isn’t just speculation: research shows that companies who use data to drive decision making increase revenues by an average of more than 8%, are 23 times more likely to attract new customers, and are 19 times more likely to be profitable as a result.

How Healthcare and Life Sciences Can Unlock the Potential of Generative AI

A patient interaction turned into clinician notes in seconds, increasing patient engagement and clinical efficiency. Novel compounds designed with desired properties, accelerating drug discovery. Realistic synthetic data created at scale, expediting research in rare under-addressed disease areas.