Fivetran supports Amazon S3 as a destination with Apache Iceberg
Our new offering accelerates data delivery to Amazon S3 with secure, fully managed pipelines and comprehensive compliance.
Managing the Cost and Complexity of Hybrid Cloud Infrastructure
More enterprises are striving to become data-driven so they deliver greater value to their customers, shareholders, employees and society at large. But many are still struggling with data infrastructure. To reap the benefits, learn how companies are solving key challenges, from managing the rapid growth of data to ensuring security and compliance, in this discussion with Dan McConnell, SVP of product management, Enterprise Infrastructure.
SaaS in 60 - Qlik Sense Mobile Improvements & Capacity Consumption Monitoring
This week we have added improvements to Qlik Sense Mobile and the ability to monitor capacity-based resource consumption for Qlik Cloud subscriptions in the Qlik Cloud Management Console.
Fivetran Demo: Landing data into Amazon S3 with Fivetran
Learn how to move data into S3 as a destination with Fivetran.
Lenses 5.1 - A 1st class ticket to be event-driven in AWS
Hello again. We strive to improve the productivity of developers building event-driven applications on the technology choices that best fit your organization. AWS continues to be a real powerhorse for our customers. Not just for running the workloads, but in supporting them with their native services: MSK Kafka, MSK Connect and now increasingly Glue Schema Registry. This is bringing a strong alternative to Confluent and their Kafka infrastructure offerings.
Secret rotation for Kafka Connect connectors with AWS Secret Manager
With version 5.1, Lenses is now offering enterprise support for our popular open-source Secret Provider to customers. In this blog, we’ll explain how secrets for Kafka Connect connectors can be safely protected using Secret Managers and walk you through configuring the Lenses S3 Sink Connector with the Lenses Secret Provider plugin and AWS Secret Manager.
Solving key challenges in the ML lifecycle with Unravel and Databricks Model Serving
Machine learning (ML) enables organizations to extract more value from their data than ever before. Companies who successfully deploy ML models into production are able to leverage that data value at a faster pace than ever before. But deploying ML models requires a number of key steps, each fraught with challenges.
Open Data Lakehouse powered by Iceberg for all your Data Warehouse needs
Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), we are excited to see customers testing their analytic workloads on Iceberg.
Selecting the right data pipeline tools
Data integration is the process of combining data from different sources and formats to create a unified and consistent view of the data. This involves merging data from multiple databases, applications, and other sources into a single repository, and transforming and formatting data so that it can be easily accessed and analyzed. Data assets need quality controls to ensure they are valid and reliable as many teams within an organization leverages the same data for different purposes.
Struggling with Inefficient Processes? Process Mining Can Help
Every organization contends with numerous moving parts that drive business forward. But they can be inefficient and convoluted – in fact, Forrester research shows that 71% of organizations use 10 or more applications for a single business process. To make matters worse, only 16% of companies have complete visibility over their own processes. This is where process mining can help. How can you gain more clarity so you can improve efficiency within your organization?