DagsHub

OCTOBER 23, 2024

This article will discuss managing unstructured data for AI and ML projects. You will learn the following: Why unstructured data management is necessary for AI and ML projects. How to properly manage unstructured data. The different tools used in unstructured data management. What is Unstructured Data?

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

ODSC - Open Data Science

JULY 14, 2023

AI and Bias: How to Detect It and How to Prevent It Sandra Wachter, PhD | Professor, Technology and Regulation | Oxford Internet Institute, University of Oxford In recognition of the extensive biases and inequality that are present in training data, there has been much work done to test for bias in machine learning and AI systems.

Machine Learning 52

Machine Learning Machine Learning Apache Kafka Data Science 52

Pickl AI

DECEMBER 2, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

SEPTEMBER 18, 2024

Read More: How Airbnb Uses Big Data and Machine Learning to Offer World-Class Service Netflix’s Big Data Infrastructure Netflix’s data infrastructure is one of the most sophisticated globally, built primarily on cloud technology. petabytes of data. What Technologies Does Netflix Use for Its Big Data Infrastructure?

Big Data 52

Big Data Big Data Apache Kafka Big Data Analytics 52

ODSC - Open Data Science

OCTOBER 9, 2024

The rapid evolution of AI is transforming nearly every industry/domain, and software engineering is no exception. Well, the thing is that AI technologies are doing a few things. If you’re not leveraging AI yet, it’s time to start. At West, you’ll learn even more about AI’s role in reshaping software engineering.

Apache Kafka 40

Apache Kafka AI AI Machine Learning 40

Pickl AI

JULY 30, 2024

Organizations can monitor the lineage of data as it moves through the system, providing visibility into data transformations and ensuring compliance with data governance policies. Integration with Big Data Ecosystems NiFi integrates seamlessly with Big Data technologies such as Apache Hadoop, Apache Kafka, and Apache Spark.

ETL 52

ETL Data Lakes Big Data Big Data 52

Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

AUGUST 9, 2024

APIs Understanding how to interact with Application Programming Interfaces (APIs) to gather data from external sources. Data Streaming Learning about real-time data collection methods using tools like Apache Kafka and Amazon Kinesis. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 8, 2024

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 Warehouses : Centralised repositories optimised for analytics and reporting.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

The MLOps Blog

MARCH 15, 2023

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. Provides data security using AI & blockchain technologies.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

ODSC - Open Data Science

MAY 24, 2023

Building a Business with a Real-Time Analytics Stack, Streaming ML Without a Data Lake, and Google’s PaLM 2 Building a Pizza Delivery Service with a Real-Time Analytics Stack The best businesses react quickly and with informed decisions. Here’s a use case of how you can use a real-time analytics stack to build a pizza delivery service.

Data Lakes 52

Data Lakes ML ML Analytics 52

AWS Machine Learning Blog

MARCH 30, 2023

For every xSaves prediction, it produces a message with the prediction as a payload, which then gets distributed by a central message broker running on Amazon Managed Streaming for Apache Kafka (Amazon MSK). The information also gets stored in a data lake for future auditing and model improvements.

Machine Learning 101

Machine Learning Machine Learning AWS ML 101

phData

SEPTEMBER 27, 2024

Technologies like Apache Kafka, often used in modern CDPs, use log-based approaches to stream customer events between systems in real-time. Both persistent staging and data lakes involve storing large amounts of raw data. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52