Women in Big Data

OCTOBER 9, 2024

Refer to Unlocking the Power of Big Data Article to understand the use case of these data collected from various sources. Data Ingestion: Data is collected and funneled into the pipeline using batch or real-time methods, leveraging tools like Apache Kafka, AWS Kinesis, or custom ETL scripts.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

Pickl AI

DECEMBER 25, 2024

This article helps you choose the right path by exploring their differences, roles, and future opportunities. Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently. They must also stay updated on tools such as TensorFlow, Hadoop, and cloud-based platforms like AWS or Azure.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Pickl AI

JANUARY 12, 2025

Summary: The article explores the differences between data driven and AI driven practices. To confirm seamless integration, you can use tools like Apache Hadoop, Microsoft Power BI, or Snowflake to process structured data and Elasticsearch or AWS for unstructured data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

Precisely

MARCH 9, 2023

In this article, we’ll focus on a data lake vs. data warehouse. We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

Pickl AI

NOVEMBER 4, 2024

This article explores the key fundamentals of Data Engineering, highlighting its significance and providing a roadmap for professionals seeking to excel in this vital field. Among these tools, Apache Hadoop, Apache Spark, and Apache Kafka stand out for their unique capabilities and widespread usage.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

IBM Journey to AI blog

JANUARY 18, 2023

This article endeavors to alleviate those confusions. This is an architecture that’s well suited for the cloud since AWS S3 or Azure DLS2 can provide the requisite storage. While this is encouraging, it is also creating confusion in the market. The concepts and values are overlapping. The concepts will be explained.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Pickl AI

JULY 25, 2023

In this comprehensive article, we will delve into the differences between Data Science and Data Engineering, explore the roles and responsibilities of Data Scientists and Data Engineers, and address some frequently asked questions in the domain. ETL Tools: Apache NiFi, Talend, etc. Big Data Processing: Apache Hadoop, Apache Spark, etc.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52