IBM Journey to AI blog

MARCH 14, 2024

Apache Kafka stands as a widely recognized open source event store and stream processing platform. One key advantage of opting for managed Kafka services is the delegation of responsibility for broker and operational metrics, allowing users to focus solely on metrics specific to applications.

Apache Kafka 92

Apache Kafka Data Pipeline 92

phData

MARCH 7, 2023

While building a whole new application might sound like a lot of work, if you’re already using Kafka to connect to Snowflake, you can upgrade your connection to version 1.8 and have your Kafka connector use the Streaming Ingest SDK instead of writing messages or streams to an internal stage.

Data Warehouse 98

Data Warehouse Database 98

phData

MARCH 1, 2024

In our role as Solution Architects , we engage in various discussions with clients regarding data ingestion, transformation, and related topics. Fortunately, the client has opted for Snowflake Data Cloud as their target data warehouse. For the older records, the value will be set to NULL. Validate the data by querying the table.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

NOVEMBER 9, 2023

Apache Kafka is a high-performance, highly scalable event streaming platform. To unlock Kafka’s full potential, you need to carefully consider the design of your application. It’s all too easy to write Kafka applications that perform poorly or eventually hit a scalability brick wall.

Apache Kafka 68

Apache Kafka Algorithm Clustering 68

Pickl AI

JULY 20, 2023

NLP techniques help extract insights, sentiment analysis, and topic modeling from text data. Real-time Data Stream Analysis: Use Python with libraries like Apache Kafka and Apache Spark to process and analyze real-time data streams from sources like Twitter, sensors, or website logs.

Analytics 40

Analytics Analytics Big Data Big Data 40

Snorkel AI

JUNE 27, 2023

And that’s the topic that we will talk about today. So I’ll cover three topics: first, online predictions, and then continual learning, and then real-time monitoring, which is extremely important to enable continual learning. We work with a lot of B2B companies and for B2B companies, they work with multiple customers or clients.

AI 52

AI AI Data Warehouse Machine Learning 52

Snorkel AI

JUNE 27, 2023

And that’s the topic that we will talk about today. So I’ll cover three topics: first, online predictions, and then continual learning, and then real-time monitoring, which is extremely important to enable continual learning. We work with a lot of B2B companies and for B2B companies, they work with multiple customers or clients.

AI 52

AI AI Data Warehouse Machine Learning 52