IBM Journey to AI blog

JANUARY 8, 2024

In modern enterprises, where operations leave a massive digital footprint, business events allow companies to become more adaptable and able to recognize and respond to opportunities or threats as they occur. Teams want more visibility and access to events so they can reuse and innovate on the work of others.

EDA 92

EDA Apache Kafka Clustering Data Governance 92

IBM Journey to AI blog

NOVEMBER 21, 2023

Apache Kafka is a well-known open-source event store and stream processing platform and has grown to become the de facto standard for data streaming. A schema describes the structure of data. Apache Kafka transfers data without validating the information in the messages. What’s next?

Apache Kafka 116

Apache Kafka Clustering Data Quality Data Governance 116

Pickl AI

NOVEMBER 4, 2024

Key Takeaways Data Engineering is vital for transforming raw data into actionable insights. Key components include data modelling, warehousing, pipelines, and integration. Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

JULY 30, 2024

Flow-Based Programming : NiFi employs a flow-based programming model, allowing users to create complex data flows using simple drag-and-drop operations. This visual representation simplifies the design and management of data pipelines. Guaranteed Delivery : NiFi ensures that data delivered reliably, even in the event of failures.

ETL 52

ETL Data Lakes Big Data Big Data 52

Pickl AI

AUGUST 9, 2024

Data Streaming Learning about real-time data collection methods using tools like Apache Kafka and Amazon Kinesis. Students should understand the concepts of event-driven architecture and stream processing. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

DagsHub

APRIL 7, 2024

Flexibility: Airflow was designed with batch workflows in mind; it was not meant for permanently running event-based workflows. Also, while it is not a streaming solution, we can still use it for such a purpose if combined with systems such as Apache Kafka. Miscellaneous Workflows are created as directed acyclic graphs (DAGs).

Machine Learning 59

Machine Learning Machine Learning ML ML 59

DagsHub

OCTOBER 23, 2024

Data Processing Tools These tools are essential for handling large volumes of unstructured data. They assist in efficiently managing and processing data from multiple sources, ensuring smooth integration and analysis across diverse formats. It allows unstructured data to be moved and processed easily between systems.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52