Cloudera

SEPTEMBER 15, 2022

A key area of focus for the symposium this year was the design and deployment of modern data platforms. Mark: The first element in the process is the link between the source data and the entry point into the data platform. Luke: Let’s talk about some of the fundamentals of modern data architecture.

Data Lake 83

Data Lake Analytics Application Cloud Storage Architecture 83

Cloudera

DECEMBER 1, 2022

Full-stack observability is a critical requirement for effective modern data platforms to deliver the agile, flexible, and cost-effective environment organizations are looking for. For example, historically the process of acquiring data from the source systems to populate the data lake was plagued by schema drift.

Data Lake 84

Data Lake Data Pipeline Analytics Application Architecture 84

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. This development was crucial for enabling both batch and streaming data workflows in dynamic environments, ensuring consistency and durability in big data processing.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Rockset

AUGUST 18, 2020

Analysts predict that by 2025 more than 30% of data will be real-time in nature, and by 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.

Data Lake 40

Data Lake Data Schemas BI Kafka 40

Rockset

AUGUST 4, 2021

Organizations that depend on data for their success and survival need robust, scalable data architecture, typically employing a data warehouse for analytics needs. Snowflake is often their cloud-native data warehouse of choice. This makes the data available sooner.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Architecture 40

Knowledge Hut

JUNE 30, 2023

Key Benefits and Takeaways: Understand data intake strategies and data transformation procedures by learning data engineering principles with Python. Investigate alternative data storage solutions, such as databases and data lakes. Key Benefits and Takeaways: Learn the core concepts of big data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

ProjectPro

FEBRUARY 16, 2023

SQL in Big Data SQL is not just limited to data warehousing and traditional relational database management systems (RDBMS). To analyze big data and create data lakes and data warehouses , SQL-on-Hadoop engines run on top of distributed file systems.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52