Analytics Vidhya

OCTOBER 28, 2021

This article was published as a part of the Data Science Blogathon What is the need for Hive? The official description of Hive is- ‘Apache Hive data warehouse software project built on top of Apache Hadoop for providing data query and analysis.

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Analytics Vidhya

APRIL 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction Apache Hadoop is the most used open-source framework in the industry to store and process large data efficiently. Hive is built on the top of Hadoop for providing data storage, query and processing capabilities.

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Analytics Vidhya

MAY 5, 2022

Introduction This article will discuss the Hadoop Distributed File System, its features, components, functions, and benefits. Hadoop is a powerful platform for supporting an enormous variety of data applications. Both structured and complex data can […].

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Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

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Analytics Vidhya

JANUARY 2, 2023

While not all of us are tech enthusiasts, we all have a fair knowledge of how Data Science works in our day-to-day lives. All of this is based on Data Science which is […]. The post Step-by-Step Roadmap to Become a Data Engineer in 2023 appeared first on Analytics Vidhya.

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Analytics Vidhya

JANUARY 31, 2023

It is designed to be more flexible and generic than the original Hadoop MapReduce system, making it an attractive choice for companies looking to implement Hadoop. It allows companies to process data types and run […] The post YARN for Large Scale Computing: Beginner’s Edition appeared first on Analytics Vidhya.

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Analytics Vidhya

FEBRUARY 14, 2023

Introduction Today we have an abundance of Hadoop jobs that are running in a constant plane, but we can’t schedule these jobs manually, we need some kind of scheduler to handle this flow. Apache Oozie is one such job scheduler that allows users to run, schedule, and manage Hadoop jobs in a distributed environment.

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Pickl AI

AUGUST 1, 2023

Aspiring and experienced Data Engineers alike can benefit from a curated list of books covering essential concepts and practical techniques. These 10 Best Data Engineering Books for beginners encompass a range of topics, from foundational principles to advanced data processing methods. What is Data Engineering?

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Analytics Vidhya

MAY 18, 2022

This article was published as a part of the Data Science Blogathon. Introduction Hadoop facilitates the processing of large datasets in a distributed manner and provides the foundation on which other services and applications can be built. MapReduce and HDFS are the two main components of Hadoop.

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Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

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Analytics Vidhya

FEBRUARY 2, 2023

Introduction Big data processing is crucial today. Big data analytics and learning help corporations foresee client demands, provide useful recommendations, and more. Hadoop, the Open-Source Software Framework for scalable and scattered computation of massive data sets, makes it easy.

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Analytics Vidhya

AUGUST 17, 2022

This article was published as a part of the Data Science Blogathon. Introduction Impala is an open-source and native analytics database for Hadoop. Vendors such as Cloudera, Oracle, MapReduce, and Amazon have shipped Impala. If you want to learn all things Impala, you’ve come to the right place.

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Data Science Blog

MARCH 14, 2023

Big Data tauchte als Buzzword meiner Recherche nach erstmals um das Jahr 2011 relevant in den Medien auf. Big Data wurde zum Business-Sprech der darauffolgenden Jahre. In der Parallelwelt der ITler wurde das Tool und Ökosystem Apache Hadoop quasi mit Big Data beinahe synonym gesetzt.

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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.

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Smart Data Collective

OCTOBER 14, 2019

Businesses need software developers that can help ensure data is collected and efficiently stored. They’re looking to hire experienced data analysts, data scientists and data engineers. With big data careers in high demand, the required skillsets will include: Apache Hadoop. NoSQL and SQL.

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Women in Big Data

OCTOBER 9, 2024

Data Processing (Preparation): Ingested data undergoes processing to ensure it’s suitable for storage and analysis. This phase ensures quality and consistency using frameworks like Apache Spark or AWS Glue. Batch Processing: For large datasets, frameworks like Apache Hadoop MapReduce or Apache Spark are used.

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DagsHub

OCTOBER 23, 2024

General Purpose Tools These tools help manage the unstructured data pipeline to varying degrees, with some encompassing data collection, storage, processing, analysis, and visualization. DagsHub's Data Engine DagsHub's Data Engine is a centralized platform for teams to manage and use their datasets effectively.

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Analytics Vidhya

MARCH 8, 2023

The Biggest Data Science Blogathon is now live! Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon. Knowledge is power. Sharing knowledge is the key to unlocking that power.”―

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Analytics Vidhya

MAY 5, 2022

This article was published as a part of the Data Science Blogathon. Introduction With a huge increment in data velocity, value, and veracity, the volume of data is growing exponentially with time. This outgrows the storage limit and enhances the demand for storing the data across a network of machines.

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AWS Machine Learning Blog

MAY 16, 2024

With Amazon EMR, which provides fully managed environments like Apache Hadoop and Spark, we were able to process data faster. The data preprocessing batches were created by writing a shell script to run Amazon EMR through AWS Command Line Interface (AWS CLI) commands, which we registered to Airflow to run at specific intervals.

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