Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. Whether it’s a cloud data warehouse or a mainframe, look for vendors who have a wide range of capabilities that can adapt to your changing needs.

Data Governance 52

Data Governance Data Pipeline Data Quality Cloud Data 52

IBM Journey to AI blog

FEBRUARY 12, 2024

It offers businesses the capability to capture and process real-time information from diverse sources, such as databases, software applications and cloud services. This restricts real-time event accessibility to a select few, increasing costs for companies as they support highly technical teams.

Apache Kafka 86

Apache Kafka EDA SQL Database 86

DataRobot Blog

MARCH 10, 2022

With, now, native Python support delivered through Snowpark for Python, developers can leverage the vibrant collection of open-source data science and machine learning packages that have become household names, even at leading AI/ML enterprises. Native Python Support for Snowpark. Learn More About AI Cloud for Manufacturing.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

phData

APRIL 18, 2024

We will ingest data using Confluent Kafka and enable Schema detection in the Kafka connector. In the current process, Snowflake supports detection and evolution for CSV, Parquet, and JSON in files and JSON within streaming data from Kafka. This is very helpful during batch loading using the COPY command or while using Snowpipe.

Clustering 52

Clustering Data Engineering Data Engineer Data Engineering 52

ODSC - Open Data Science

MAY 31, 2023

Commonly used technologies for data storage are the Hadoop Distributed File System (HDFS), Amazon S3, Google Cloud Storage (GCS), or Azure Blob Storage, as well as tools like Apache Hive, Apache Spark, and TensorFlow for data processing and analytics. About the author/ODSC Europe speaker: Kai Waehner is Field CTO at Confluent.

Data Lakes 131

Data Lakes Machine Learning Machine Learning Apache Kafka 131