insideBIGDATA

JUNE 25, 2024

In this contributed article, Sijie Guo, Founder and CEO of Streamnative, believes that with remote work entrenched in the post-pandemic enterprise, organizations are restructuring their technology stack and software strategy for a new, distributed workforce.

Apache Kafka 217

Apache Kafka Big Data Big Data Analytics 217

Women in Big Data

OCTOBER 9, 2024

With the explosive growth of big data over the past decade and the daily surge in data volumes, it’s essential to have a resilient system to manage the vast influx of information without failures. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

ODSC - Open Data Science

JULY 14, 2023

Originally posted on OpenDataScience.com Read more data science articles on OpenDataScience.com , including tutorials and guides from beginner to advanced levels! The session participants will learn the theory behind compound sparsity, state-of-the-art techniques, and how to apply it in practice using the Neural Magic platform.

Machine Learning 52

Machine Learning Machine Learning Apache Kafka Data Science 52

Pickl AI

OCTOBER 21, 2024

Summary: This article highlights the significance of Database Management Systems in social media giants, focusing on their functionality, types, challenges, and future trends that impact user experience and data management. They provide flexibility in data models and can scale horizontally to manage large volumes of data.

Database 52

Database Apache Kafka Machine Learning Machine Learning 52

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. They must also ensure that data privacy regulations, such as GDPR and CCPA , are followed.

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Big Data Big Data Data Engineer Data Engineering 91

Pickl AI

JULY 20, 2023

Text Analytics and Natural Language Processing (NLP) Projects: These projects involve analyzing unstructured text data, such as customer reviews, social media posts, emails, and news articles. NLP techniques help extract insights, sentiment analysis, and topic modeling from text data.

Analytics 40

Analytics Analytics Big Data Big Data 40

The MLOps Blog

FEBRUARY 5, 2023

There are many platforms and sources that generate this kind of data. In this article, we will go through the basics of streaming data, what it is, and how it differs from traditional data. We will also get familiar with tools that can help record this data and further analyse it.

Machine Learning 72

Machine Learning Machine Learning Data Pipeline Apache Kafka 72

The Data Administration Newsletter

FEBRUARY 15, 2022

Most large technology businesses collect data from their consumers in a variety of methods, and the majority of the time, this data is in its raw form. However, when data is presented in an understandable and accessible style, it may assist and drive business requirements.

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Apache Kafka Big Data Big Data Business Intelligence 52

The MLOps Blog

MARCH 15, 2023

Listed below are some of the common types of data pipeline tools: Commercial vs open-source data pipeline tools When a business needs full control over the development process and wants to build highly customizable complex solutions, open-source tools come in handy. No built-in data quality functionality. No expert support.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

Mlearning.ai

MAY 16, 2023

Data engineering is a rapidly growing field that designs and develops systems that process and manage large amounts of data. There are various architectural design patterns in data engineering that are used to solve different data-related problems.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. How to properly manage unstructured data.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Alation

AUGUST 4, 2022

It’s been one decade since the “ Big Data Era ” began (and to much acclaim!). Analysts asked, What if we could manage massive volumes and varieties of data? Yet the question remains: How much value have organizations derived from big data? Big Data as an Enabler of Digital Transformation.

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Big Data Big Data Apache Kafka Data Lakes 95

The MLOps Blog

AUGUST 11, 2023

1 Data Ingestion (e.g., Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., Conclusion This article covered various aspects, including pipeline architecture, design considerations, standard practices in leading tech corporations, common patterns, and typical components of ML pipelines. 2022, January 18).

ML 52

ML ML Machine Learning Machine Learning 52