Analytics Vidhya

SEPTEMBER 22, 2022

This article was published as a part of the Data Science Blogathon. Dale Carnegie” Apache Kafka is a Software Framework for storing, reading, and analyzing streaming data. The post Build a Simple Realtime Data Pipeline appeared first on Analytics Vidhya. Introduction “Learning is an active process.

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Data Science Dojo

JULY 24, 2023

The generation and accumulation of vast amounts of data have become a defining characteristic of our world. This data, often referred to as Big Data , encompasses information from various sources, including social media interactions, online transactions, sensor data, and more. databases), semi-structured data (e.g.,

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IBM Journey to AI blog

NOVEMBER 3, 2023

It allows your business to ingest continuous data streams as they happen and bring them to the forefront for analysis, enabling you to keep up with constant changes. Apache Kafka boasts many strong capabilities, such as delivering a high throughput and maintaining a high fault tolerance in the case of application failure.

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Data Science Blog

JUNE 27, 2023

Big Data Analytics stands apart from conventional data processing in its fundamental nature. In the realm of Big Data, there are two prominent architectural concepts that perplex companies embarking on the construction or restructuring of their Big Data platform: Lambda architecture or Kappa architecture.

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IBM Journey to AI blog

SEPTEMBER 4, 2024

Apache Kafka is an open-source , distributed streaming platform that allows developers to build real-time, event-driven applications. With Apache Kafka, developers can build applications that continuously use streaming data records and deliver real-time experiences to users. How does Apache Kafka work?

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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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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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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.

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Pickl AI

DECEMBER 9, 2024

Summary: This article provides a comprehensive guide on Big Data interview questions, covering beginner to advanced topics. Introduction Big Data continues transforming industries, making it a vital asset in 2025. The global Big Data Analytics market, valued at $307.51 What is Big Data?

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Pickl AI

SEPTEMBER 18, 2024

Summary: Netflix’s sophisticated Big Data infrastructure powers its content recommendation engine, personalization, and data-driven decision-making. As a pioneer in the streaming industry, Netflix utilises advanced data analytics to enhance user experience, optimise operations, and drive strategic decisions.

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Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

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Pickl AI

DECEMBER 2, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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Pickl AI

NOVEMBER 25, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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Analytics Vidhya

JUNE 27, 2020

Overview There are a plethora of data science tools out there – which one should you pick up? The post 22 Widely Used Data Science and Machine Learning Tools in 2020 appeared first on Analytics Vidhya. Here’s a list of over 20.

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Precisely

DECEMBER 28, 2023

How do streaming data pipelines work? The first step in a streaming data pipeline is where information enters the pipeline. One very popular platform is Apache Kafka , a powerful open-source tool used by thousands of companies. Interested in learning more about streaming data pipelines for your organization?

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insideBIGDATA

JUNE 25, 2024

Real-time data streaming has emerged as a necessary and cost efficient way for enterprises to scale in an agile way.

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insideBIGDATA

JUNE 25, 2024

Real-time data streaming has emerged as a necessary and cost efficient way for enterprises to scale in an agile way.

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IBM Journey to AI blog

NOVEMBER 29, 2023

How event processing fuels AI By combining event processing and AI, businesses are helping to drive a new era of highly precise, data-driven decision making. Events as fuel for AI Models: Artificial intelligence models rely on big data to refine the effectiveness of their capabilities.

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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.

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Pickl AI

JULY 29, 2024

It utilises the Hadoop Distributed File System (HDFS) and MapReduce for efficient data management, enabling organisations to perform big data analytics and gain valuable insights from their data. In a Hadoop cluster, data stored in the Hadoop Distributed File System (HDFS), which spreads the data across the nodes.

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AWS Machine Learning Blog

MARCH 30, 2023

How it’s implemented Positional data from an ongoing match, which is recorded at a sampling rate of 25 Hz, is utilized to determine the time taken to recover the ball. This allows for seamless communication of positional data and various outputs of Bundesliga Match Facts between containers in real time.

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ODSC - Open Data Science

JULY 14, 2023

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.

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Pickl AI

DECEMBER 4, 2024

This explosive growth is driven by the increasing volume of data generated daily, with estimates suggesting that by 2025, there will be around 181 zettabytes of data created globally. The field has evolved significantly from traditional statistical analysis to include sophisticated Machine Learning algorithms and Big Data technologies.

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Pickl AI

JULY 30, 2024

Its architecture includes FlowFiles, repositories, and processors, enabling efficient data processing and transformation. With a user-friendly interface and robust features, NiFi simplifies complex data workflows and enhances real-time data integration.

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Pickl AI

JULY 20, 2023

Defining clear objectives and selecting appropriate techniques to extract valuable insights from the data is essential. Here are some project ideas suitable for students interested in big data analytics with Python: 1. Implement real-time analytics to monitor trends or anomalies in the data.

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Pickl AI

NOVEMBER 4, 2024

Introduction Data Engineering is the backbone of the data-driven world, transforming raw data into actionable insights. As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. million by 2028.

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ODSC - Open Data Science

OCTOBER 9, 2024

Efficient Incremental Processing with Apache Iceberg and Netflix Maestro Dimensional Data Modeling in the Modern Era Building Big Data Workflows: NiFi, Hive, Trino, & Zeppelin An Introduction to Data Contracts From Data Mess to Data Mesh — Data Management in the Age of Big Data and Gen AI Introduction to Containers for Data Science / Data Engineering (..)

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The MLOps Blog

FEBRUARY 5, 2023

The machine learning model is part of the Stream processing engine, and it provides the logic that helps the streaming data pipeline expose features within the stream and potentially within a historical data store. It can be used to collect, store, and process streaming data in real-time.

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Pickl AI

OCTOBER 21, 2024

They provide flexibility in data models and can scale horizontally to manage large volumes of data. NoSQL is well-suited for big data applications and real-time analytics, allowing organisations to adapt to rapidly changing data landscapes. Examples include MongoDB, Cassandra, and Redis.

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Mlearning.ai

MAY 16, 2023

The events can be published to a message broker such as Apache Kafka or Google Cloud Pub/Sub. The message broker can then distribute the events to various subscribers such as data processing pipelines, machine learning models, and real-time analytics dashboards.

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DagsHub

OCTOBER 23, 2024

Data Lakes Data lakes are centralized repositories designed to store vast amounts of raw, unstructured, and structured data in their native format. They enable flexible data storage and retrieval for diverse use cases, making them highly scalable for big data applications.

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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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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.

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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.

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The MLOps Blog

AUGUST 11, 2023

1 Data Ingestion (e.g., Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., Today different stages exist within ML pipelines built to meet technical, industrial, and business requirements. This section delves into the common stages in most ML pipelines, regardless of industry or business function.

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Pickl AI

FEBRUARY 23, 2025

Summary: Big Data tools empower organizations to analyze vast datasets, leading to improved decision-making and operational efficiency. Ultimately, leveraging Big Data analytics provides a competitive advantage and drives innovation across various industries.

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Pickl AI

MARCH 13, 2025

Choosing between them depends on your systems needsRabbitMQ is best for workflows, while Kafka is ideal for event-driven architectures and big data processing. Two of the most popular message brokers are RabbitMQ and Apache Kafka. Kafka excels in real-time data streaming and scalability.

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