Analytics Vidhya

JULY 12, 2023

Best Big Data Softwares - Apache Hadoop, Apache Spark, apache Kafka, Apache Storm, Apache Cassandra, Apache Hive, zoho & more.

Apache Kafka 266

Apache Kafka Apache Hadoop Big Data Big Data 266

Analytics Vidhya

MAY 17, 2022

It is developed as a part of the Hadoop ecosystem and runs on top of HDFS. This article was published as a part of the Data Science Blogathon. HBase is an open-source non-relational, scalable, distributed database written in Java. It provides random real-time read and write access to the given data. It is possible to […].

Database 287

Database Hadoop Data Science Analytics 287

Data Science Dojo

OCTOBER 31, 2024

Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Programming Questions Data science roles typically require knowledge of Python, SQL, R, or Hadoop. Their role is crucial in understanding the underlying data structures and how to leverage them for insights.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Analytics Vidhya

JUNE 30, 2022

Introduction Hive is a popular data warehouse built on top of Hadoop that is used by companies like Walmart, Tiktok, and AT&T. This article was published as a part of the Data Science Blogathon. It is an important technology for data engineers to learn and master. It uses a declarative language called HQL, also known […].

Data Warehouse 271

Data Warehouse Hadoop Data Engineering Data Engineering 271

Data Science Dojo

JULY 6, 2023

Apache Hadoop: Apache Hadoop is an open-source framework for distributed storage and processing of large datasets. Hadoop consists of the Hadoop Distributed File System (HDFS) for distributed storage and the MapReduce programming model for parallel data processing.

Data Engineering 195

Data Engineering Data Engineering Data Engineer Data Engineering 195

Data Science Dojo

AUGUST 27, 2024

Python, R, and SQL: These are the most popular programming languages for data science. Hadoop and Spark: These are like powerful computers that can process huge amounts of data quickly. Python, R, and SQL: These are the most popular programming languages for data science. Statistics provides the language to do this effectively.

Data Scientist 273

Data Scientist Data Science Machine Learning Machine Learning 273

Pickl AI

JULY 6, 2023

Here comes the role of Hive in Hadoop. Hive is a powerful data warehousing infrastructure that provides an interface for querying and analyzing large datasets stored in Hadoop. In this blog, we will explore the key aspects of Hive Hadoop. What is Hadoop ? Hive is a data warehousing infrastructure built on top of Hadoop.

Hadoop 52

Hadoop SQL Big Data Big Data 52

AWS Machine Learning Blog

FEBRUARY 21, 2025

Rockets legacy data science environment challenges Rockets previous data science solution was built around Apache Spark and combined the use of a legacy version of the Hadoop environment and vendor-provided Data Science Experience development tools. Apache HBase was employed to offer real-time key-based access to data.

Data Science 74

Data Science AWS Hadoop Data Scientist 74

Pickl AI

SEPTEMBER 19, 2024

Summary: This article compares Spark vs Hadoop, highlighting Spark’s fast, in-memory processing and Hadoop’s disk-based, batch processing model. Introduction Apache Spark and Hadoop are potent frameworks for big data processing and distributed computing. What is Apache Hadoop? What is Apache Spark?

Hadoop 52

Hadoop Big Data Big Data Clustering 52

Data Science Dojo

JANUARY 12, 2023

Hadoop systems and data lakes are frequently mentioned together. Data is loaded into the Hadoop Distributed File System (HDFS) and stored on the many computer nodes of a Hadoop cluster in deployments based on the distributed processing architecture.

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

Data Science Connect

JANUARY 27, 2023

Learn SQL: As a data engineer, you will be working with large amounts of data, and SQL is the most commonly used language for interacting with databases. Understanding how to write efficient and effective SQL queries is essential.

Data Engineering 130

Data Engineering Data Engineering Data Engineer Data Engineering 130

Pickl AI

JUNE 18, 2023

Hadoop has become a highly familiar term because of the advent of big data in the digital world and establishing its position successfully. However, understanding Hadoop can be critical and if you’re new to the field, you should opt for Hadoop Tutorial for Beginners. What is Hadoop? Let’s find out from the blog!

Hadoop 52

Hadoop Big Data Big Data Clustering 52

Smart Data Collective

OCTOBER 14, 2019

With big data careers in high demand, the required skillsets will include: Apache Hadoop. Software businesses are using Hadoop clusters on a more regular basis now. Apache Hadoop develops open-source software and lets developers process large amounts of data across different computers by using simple models. NoSQL and SQL.

Big Data 99

Big Data Big Data Apache Hadoop Hadoop 99

Smart Data Collective

SEPTEMBER 8, 2021

Extract : In this step, data is extracted from a vast array of sources present in different formats such as Flat Files, Hadoop Files, XML, JSON, etc. Here are few best Open-Source ETL tools on the market: Hadoop : Hadoop distinguishes itself as a general-purpose Distributed Computing platform.

ETL 126

ETL Hadoop Data Warehouse Data Pipeline 126

Pickl AI

JANUARY 27, 2025

Hadoop emerges as a fundamental framework that processes these enormous data volumes efficiently. This blog aims to clarify Big Data concepts, illuminate Hadoops role in modern data handling, and further highlight how HDFS strengthens scalability, ensuring efficient analytics and driving informed business decisions.

Hadoop 52

Hadoop Big Data Big Data Clustering 52

Data Science Dojo

JULY 7, 2023

Tools such as Python, R, and SQL help to manipulate and analyze data. Data scientists need a strong foundation in statistics and mathematics to understand the patterns in data. Proficiency in tools like Python, R, SQL, and platforms like Hadoop or Spark is essential for data manipulation and analysis.

Data Science 195

Data Science Data Scientist Python Decision Trees 195

phData

APRIL 26, 2024

One common scenario that we’ve helped many clients with involves migrating data from Hive tables in a Hadoop environment to the Snowflake Data Cloud. Click Create cluster and choose software (Hadoop, Hive, Spark, Sqoop) and configuration (instance types, node count). Configure security (EC2 key pair). Find ElasticMapReduce-master.

Hadoop 52

Hadoop Clustering AWS Database 52

Data Science Dojo

AUGUST 27, 2024

Python, R, and SQL: These are the most popular programming languages for data science. Hadoop and Spark: These are like powerful computers that can process huge amounts of data quickly. Python, R, and SQL: These are the most popular programming languages for data science. Statistics provides the language to do this effectively.

Data Scientist 195

Data Scientist Data Science Machine Learning Machine Learning 195

Smart Data Collective

APRIL 8, 2020

This data is then processed, transformed, and consumed to make it easier for users to access it through SQL clients, spreadsheets and Business Intelligence tools. The company works consistently to enhance its business intelligence solutions through innovative new technologies including Hadoop-based services.

Data Warehouse 144

Data Warehouse Big Data Big Data Big Data Analytics 144

Data Science Dojo

JULY 24, 2023

Hadoop Distributed File System (HDFS) : HDFS is a distributed file system designed to store vast amounts of data across multiple nodes in a Hadoop cluster. Spark provides a high-level API in multiple languages like Scala, Python, Java, and SQL, making it accessible to a wide range of developers.

Big Data 195

Big Data Big Data Data Engineer Data Engineering 195

Towards AI

SEPTEMBER 28, 2023

With PySpark, you can write Python and SQL-like commands to manipulate and analyze data in a distributed processing environment. It leverages Apache Hadoop for both storage and processing. Apache Spark: Apache Spark is an open-source data processing framework for processing large datasets in a distributed manner.

Apache Hadoop 75

Apache Hadoop Hadoop Python SQL 75

Dataconomy

JULY 24, 2023

” Data management and manipulation Data scientists often deal with vast amounts of data, so it’s crucial to understand databases, data architecture, and query languages like SQL. They often use tools like SQL and Excel to manipulate data and create reports. Machine learning Machine learning is a key part of data science.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Smart Data Collective

NOVEMBER 8, 2020

As such, you should begin by learning the basics of SQL. SQL is an established language used widely in data engineering. Just like programming, SQL has multiple dialects. Besides SQL, you should also learn how to model data. As a data engineer, you will be primarily working on databases.

Data Engineering 104

Data Engineering Data Engineering Data Engineer Data Engineering 104

Pickl AI

DECEMBER 25, 2024

Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently. Data Analysts dive deeper into raw data, using tools like Excel, Tableau, and SQL to create reports and dashboards.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Alation

FEBRUARY 20, 2020

We decided to address these needs for SQL engines over Hadoop in Alation 4.0. It is also used across Alation’s applications, such as our SQL query writing interface, Compose, which produces SmartSuggestions. Further, Alation Compose now benefits from the usage context derived from the query catalogs over Hadoop.

Hadoop 52

Hadoop SQL Database Data Analyst 52

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Databases and SQL : Managing and querying relational databases using SQL, as well as working with NoSQL databases like MongoDB.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Analytics Vidhya

JUNE 27, 2020

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

Machine Learning 400

Machine Learning Data Science Machine Learning Analytics 400

Analytics Vidhya

MARCH 8, 2023

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

Data Science 345

Data Science Analytics Analytics Apache Hadoop 345

Analytics Vidhya

JANUARY 2, 2023

Introduction You must have noticed the personalization happening in the digital world, from personalized Youtube videos to canny ad recommendations on Instagram. 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 […].

Data Engineer 329

Data Engineer Data Engineering Data Engineering Data Engineering 329

Analytics Vidhya

MAY 21, 2023

Introduction Not a single day passes without us getting to hear the word “data.” It is almost as if our lives revolve around it. Don’t they? With something so profound in daily life, there should be an entire domain handling and utilizing it. This is precisely what happens in data analytics.

Analytics 357

Analytics Analytics Power BI Hadoop 357

Pickl AI

OCTOBER 27, 2024

Students learn to work with tools like Python, R, SQL, and machine learning frameworks, which are essential for analysing complex datasets and deriving actionable insights1. Big Data Technologies: Familiarity with tools like Hadoop and Spark is increasingly important.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Analytics Vidhya

FEBRUARY 7, 2023

Introduction Data engineering is the field of study that deals with the design, construction, deployment, and maintenance of data processing systems. The goal of this domain is to collect, store, and process data efficiently and efficiently so that it can be used to support business decisions and power data-driven applications.

Data Engineer 318

Data Engineer Data Engineering Data Engineering Data Engineering 318

Analytics Vidhya

JANUARY 8, 2023

Hey, are you the data science geek who spends hours coding, learning a new language, or just exploring new avenues of data science? If all of these describe you, then this Blogathon announcement is for you! Analytics Vidhya is back with its 28th Edition of blogathon, a place where you can share your knowledge about […].

Data Science 328

Data Science Analytics Analytics Hadoop 328

Pickl AI

DECEMBER 9, 2024

Familiarise yourself with essential tools like Hadoop and Spark. What are the Main Components of Hadoop? Hadoop consists of the Hadoop Distributed File System (HDFS) for storage and MapReduce for processing data across distributed systems. What is the Role of a NameNode in Hadoop ? What is a DataNode in Hadoop?

Big Data 52

Big Data Big Data Hadoop Apache Kafka 52

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Big Data Technologies: Hadoop, Spark, etc. ETL Tools: Apache NiFi, Talend, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Analytics Vidhya

SEPTEMBER 23, 2022

This article was published as a part of the Data Science Blogathon. Introduction Hi Everyone, In this guide, we will discuss Apache Sqoop. We will discuss the Sqoop import and export processes with different modes and also cover Sqoop-hive integration. In this guide, I will go over Apache Sqoop in depth so that whenever you […].

Data Science 286

Data Science Analytics Analytics Hadoop 286

Data Science 101

JUNE 10, 2019

Hadoop, SQL, Python, R, Excel are some of the tools you’ll need to be familiar using. Among the skills necessary to become a data scientist include an analytical mindset, mathematics, data visualization, and business knowledge, just to name a few. Each tool plays a different role in the data science process.

Data Science 96

Data Science Data Scientist Data Analyst Data Engineer 96