IBM Journey to AI blog

NOVEMBER 29, 2023

IBM Event Automation is a fully composable solution, built on open technologies, with capabilities for: Event streaming : Collect and distribute raw streams of real-time business events with enterprise-grade Apache Kafka. Event endpoint management : Describe and document events easily according to the Async API specification.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence Apache Kafka AI 105

Pickl AI

NOVEMBER 4, 2024

They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes. Data Modelling Data modelling is creating a visual representation of a system or database. Physical Models: These models specify how data will be physically stored in databases.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

AUGUST 4, 2023

The focus of this investigation revolves around understanding their industry distribution, age demographics, developer types, and their adoption of various programming languages, databases, platforms, web frameworks, miscellaneous technologies, technical tools, new collaboration tools, and AI-powered search tools. NET Framework (1.0–4.8)’

Database 52

Database Apache Kafka SQL AI 52

Pickl AI

DECEMBER 9, 2024

Variety Data comes in multiple forms, from highly organised databases to messy, unstructured formats like videos and social media text. What is Apache Hive? Hive is a data warehouse tool built on Hadoop that enables SQL-like querying to analyse large datasets. What are the Key Features of Apache Hive?

Big Data 52

Big Data Big Data Hadoop Apache Kafka 52

Pickl AI

JULY 8, 2024

Database Extraction: Retrieval from structured databases using query languages like SQL. Common options include: Relational Databases: Structured storage supporting ACID transactions, suitable for structured data. NoSQL Databases: Flexible, scalable solutions for unstructured or semi-structured data.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 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. Data can come from different sources, such as databases or directly from users, with additional sources, including platforms like GitHub, Notion, or S3 buckets.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Pickl AI

AUGUST 9, 2024

Variety It encompasses the different types of data, including structured data (like databases), semi-structured data (like XML), and unstructured formats (such as text, images, and videos). Understanding the differences between SQL and NoSQL databases is crucial for students.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

The MLOps Blog

MARCH 15, 2023

Typical examples include: Airbyte Talend Apache Kafka Apache Beam Apache Nifi While getting control over the process is an ideal position an organization wants to be in, the time and effort needed to build such systems are immense and frequently exceeds the license fee of a commercial offering. Talend Free to use.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

phData

SEPTEMBER 27, 2024

It often involves specialized databases designed to handle this kind of atomic, temporal data. Instead of simple SQL queries, we often need to use more complex temporal query languages or rely on derived views for simpler querying. It’s precise but can impact database performance.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 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 98

ML ML Apache Kafka SQL 98

Pickl AI

DECEMBER 4, 2024

Apache Kafka), organisations can now analyse vast amounts of data as it is generated. Grasp the Fundamentals of Data Analysis and Management Build a strong foundation in Data Analysis by learning data manipulation techniques using SQL and Excel. Focus on Python and R for Data Analysis, along with SQL for database management.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 23, 2025

Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. Real-Time Data Analysis: Connects seamlessly with various databases for live analysis.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52