Monte Carlo

JUNE 26, 2023

After launching our partnership with Databricks last year, Monte Carlo has aggressively expanded our native Databricks and Apache Spark™ integrations to extend data observability into the Delta Lake and Unity Catalog, and in the process, drive even more value for Databricks customers.

Data Lake 52

Data Lake Metadata Bytes Google Cloud 52

Ascend.io

MAY 24, 2023

Healthcare Data Pipeline Evolution: From SQL to Spark The SQL Era In the early days of our data journey, pipelines were crafted in many mySQL databases. Every data mapping configuration found its home in mySQL tables, with enormous SQL scripts designated for each admin, financial, and clinical dataset.

Healthcare 52

Healthcare Data Pipeline Hospitality Datasets 52

Confluent

JUNE 13, 2019

The LSST is expected to detect about 10 million transient objects each night, an order of magnitude more than ZTF, with a nightly data stream size of 1–2 TB of messages. There were a number of factors we considered in designing an alert distribution for ZTF. Alert data pipeline and system design.

Kafka 102

Kafka Bytes Data Pipeline Python 102

Confluent

APRIL 30, 2019

However, as a programming interface, such a tedious development cycle should not be the design philosophy of the Streams DSL. Instead, it should try to hide as much of the topology generation details from the developer as possible.

Kafka 90

Kafka Coding Process Bytes 90

ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Data Processing: This is the final step in deploying a big data model. No reliability exists.

Big Data 52

Big Data Hadoop AWS Relational Database 52