IBM Journey to AI blog

AUGUST 29, 2024

Event-driven businesses across all industries thrive on real-time data, enabling companies to act on events as they happen rather than after the fact. This is where Apache Flink shines, offering a powerful solution to harness the full potential of an event-driven business model through efficient computing and processing capabilities.

Apache Kafka 45

Apache Kafka Hadoop ETL Data Pipeline 45

ODSC - Open Data Science

JULY 22, 2023

We had bigger sessions on getting started with machine learning or SQL, up to advanced topics in NLP, and how to make deepfakes. Expo Hall ODSC events are more than just data science training and networking events. Top Sessions With sessions both online and in-person in Boston, there was something for everyone. What’s next?

Apache Kafka 52

Apache Kafka Machine Learning Machine Learning Data Science 52

AWS Machine Learning Blog

APRIL 19, 2023

Streaming ingestion – An Amazon Kinesis Data Analytics for Apache Flink application backed by Apache Kafka topics in Amazon Managed Streaming for Apache Kafka (MSK) (Amazon MSK) calculates aggregated features from a transaction stream, and an AWS Lambda function updates the online feature store.

ML 89

ML ML Apache Kafka SQL 89

Data Science Dojo

JULY 24, 2023

Spark provides a high-level API in multiple languages like Scala, Python, Java, and SQL, making it accessible to a wide range of developers. Unlike traditional batch processing, where data is processed in fixed intervals, stream processing enables organizations to gain insights and respond to events as they happen in real-time.

Big Data 195

Big Data Big Data Data Engineering Data Engineering 195

Pickl AI

NOVEMBER 4, 2024

Various types of storage options are available, including: Relational Databases: These databases use Structured Query Language (SQL) for data management and are ideal for handling structured data with well-defined relationships. SQL SQL is crucial for querying and managing relational databases.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

phData

SEPTEMBER 27, 2024

In this guide, we will explore concepts like transitional modeling for customer profiles, the power of event logs for customer behavior, persistent staging for raw customer data, real-time customer data capture, and much more. Rich Context: Each event carries with it a wealth of contextual information. What is Activity Schema Modeling?

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

AWS Machine Learning Blog

JANUARY 6, 2023

The rules in this engine were predefined and written in SQL, which aside from posing a challenge to manage, also struggled to cope with the proliferation of data from TR’s various integrated data source. As the users are interacting with TR’s applications, they generate clickstream events, which are published into Amazon Kinesis Data Streams.

AWS 79

AWS Data Warehouse ML ML 79

The MLOps Blog

MARCH 15, 2023

Data Ingestion : Involves raw data collection from origin and storage using architectures such as batch, streaming or event-driven. Enables users to trigger their custom transformations via SQL and dbt. Best data pipeline tools: Talend | Source Categorization Open Source Batch data processing Pros Apache license makes it free to use.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

Pickl AI

AUGUST 9, 2024

Understanding the differences between SQL and NoSQL databases is crucial for students. 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.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

DagsHub

OCTOBER 23, 2024

Here’s the structured equivalent of this same data in tabular form: With structured data, you can use query languages like SQL to extract and interpret information. Apache Kafka Apache Kafka is a distributed event streaming platform for real-time data pipelines and stream processing.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

DagsHub

APRIL 7, 2024

Thanks to its various operators, it is integrated with Python, Spark, Bash, SQL, and more. Flexibility: Airflow was designed with batch workflows in mind; it was not meant for permanently running event-based workflows. This also means that it comes with a large community and comprehensive documentation.

Machine Learning 59

Machine Learning Machine Learning ML ML 59