Data Science Dojo

JULY 12, 2023

Welcome to the world of databases, where the choice between SQL (Structured Query Language) and NoSQL (Not Only SQL) databases can be a significant decision. In this blog, we’ll explore the defining traits, benefits, use cases, and key factors to consider when choosing between SQL and NoSQL databases.

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Analytics Vidhya

MAY 17, 2022

It is developed as a part of the Hadoop ecosystem and runs on top of HDFS. The post Getting Started with NoSQL Database Called HBase appeared first on Analytics Vidhya. 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.

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Data Science Dojo

OCTOBER 31, 2024

Skills and Training Familiarity with ethical frameworks like the IEEE’s Ethically Aligned Design, combined with strong analytical and compliance skills, is essential. Strong analytical skills and the ability to work with large datasets are critical, as is familiarity with data modeling and ETL processes.

Data Science 195

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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. The post Partitioning and Bucketing in Hive appeared first on Analytics Vidhya. It is an important technology for data engineers to learn and master.

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Analytics Vidhya

JULY 12, 2023

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

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Pickl AI

DECEMBER 25, 2024

Summary: Business Analytics focuses on interpreting historical data for strategic decisions, while Data Science emphasizes predictive modeling and AI. Introduction In today’s data-driven world, businesses increasingly rely on analytics and insights to drive decisions and gain a competitive edge. What is Business Analytics?

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Analytics Vidhya

JUNE 27, 2020

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

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Data Science Dojo

JULY 6, 2023

Google BigQuery: Google BigQuery is a serverless, cloud-based data warehouse designed for big data analytics. It integrates well with other Google Cloud services and supports advanced analytics and machine learning features. Apache Spark: Apache Spark is an open-source, unified analytics engine designed for big data processing.

Data Engineering 195

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Analytics Vidhya

MARCH 8, 2023

.”― Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon.

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Data Science Dojo

JANUARY 12, 2023

An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Hadoop systems and data lakes are frequently mentioned together. However, instead of using Hadoop, data lakes are increasingly being constructed using cloud object storage services.

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Data Lakes Data Warehouse Hadoop Machine Learning 221

Analytics Vidhya

JANUARY 8, 2023

Analytics Vidhya is back with its 28th Edition of blogathon, a place where you can share your knowledge about […]. The post Data Science Blogathon 28th Edition appeared first on Analytics Vidhya. Hey, are you the data science geek who spends hours coding, learning a new language, or just exploring new avenues of data science?

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Thats why we use advanced technology and data analytics to streamline every step of the homeownership experience, from application to closing. Apache Hive was used to provide a tabular interface to data stored in HDFS, and to integrate with Apache Spark SQL. Rocket takes a complicated process and uses technology to make it simpler.

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Analytics Vidhya

FEBRUARY 7, 2023

This includes designing and implementing […] The post Most Essential 2023 Interview Questions on Data Engineering appeared first on Analytics Vidhya. 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.

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Analytics Vidhya

JANUARY 2, 2023

The post Step-by-Step Roadmap to Become a Data Engineer in 2023 appeared first on Analytics Vidhya. 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 Engineering 329

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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?

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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.

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How to Learn Machine Learning

APRIL 26, 2025

The processes of SQL, Python scripts, and web scraping libraries such as BeautifulSoup or Scrapy are used for carrying out the data collection. The responsibilities of this phase can be handled with traditional databases (MySQL, PostgreSQL), cloud storage (AWS S3, Google Cloud Storage), and big data frameworks (Hadoop, Apache Spark).

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Smart Data Collective

OCTOBER 14, 2019

From artificial intelligence and machine learning to blockchains and data analytics, big data is everywhere. 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. NoSQL and SQL. Big Data Skillsets.

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Smart Data Collective

MAY 20, 2019

We’re well past the point of realization that big data and advanced analytics solutions are valuable — just about everyone knows this by now. Data processing is another skill vital to staying relevant in the analytics field. For frameworks and languages, there’s SAS, Python, R, Apache Hadoop and many others.

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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!

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Analytics Vidhya

SEPTEMBER 23, 2022

The post A Comprehensive Guide On Apache Sqoop appeared first on Analytics Vidhya. 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

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IBM Journey to AI blog

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Smart Data Collective

SEPTEMBER 8, 2021

ETL is one of the most integral processes required by Business Intelligence and Analytics use cases since it relies on the data stored in Data Warehouses to build reports and visualizations. 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.

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Pickl AI

JANUARY 27, 2025

By co-locating data and computations, HDFS delivers high throughput, enabling advanced analytics and driving data-driven insights across various industries. Hadoop emerges as a fundamental framework that processes these enormous data volumes efficiently. It fosters reliability. billion in 2023 and may grow at a CAGR of 14.9%

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Data Science Dojo

JULY 7, 2023

Tools such as Python, R, and SQL help to manipulate and analyze data. Essential Skills for Coding Coding demands a unique blend of creativity and analytical skills. Mastering a programming language is just the tip of the iceberg. Statistics helps data scientists to estimate, predict and test hypotheses.

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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.

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phData

APRIL 26, 2024

Seamless data transfer between different platforms is crucial for effective data management and analytics. 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. Configure security (EC2 key pair). Review settings and launch the cluster.

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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

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Pickl AI

APRIL 21, 2025

Big Data technologies include Hadoop, Spark, and NoSQL databases. Database Knowledge: Like SQL for retrieving data. Big Data Technologies Enable Data Science at Scale Tools like Hadoop and Spark were developed specifically to handle the challenges of Big Data. Data Science uses Python, R, and machine learning frameworks.

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IBM Journey to AI blog

SEPTEMBER 25, 2023

But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success.

Data Lakes 102

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phData

SEPTEMBER 20, 2023

Snowpark is the set of libraries and runtimes in Snowflake that securely deploy and process non-SQL code, including Python , Java, and Scala. As a declarative language, SQL is very powerful in allowing users from all backgrounds to ask questions about data. What is Snowflake’s Snowpark? Why Does Snowpark Matter?

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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. Regardless, the database uses parallel processing to complete analytical queries.

Data Engineering 104

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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. As a data scientist, you will be instrumental in crafting data-driven business strategies and analytics.

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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. By pursuing a course in Data Science, you can contribute to significant business outcomes and societal advancements through your analytical skills.

Data Science 52

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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.

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Mlearning.ai

MARCH 15, 2023

This article will serve as an ultimate guide to choosing between Data Science and Data Analytics. Some individuals are confused about the right path to choose between the two lucrative careers —  Data Science and Data Analytics. Familiarity with Databases; SQL for structured data, and NOSQL for unstructured data.

Data Science 52

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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

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