Analytics Vidhya

FEBRUARY 6, 2023

Introduction HDFS (Hadoop Distributed File System) is not a traditional database but a distributed file system designed to store and process big data. It is a core component of the Apache Hadoop ecosystem and allows for storing and processing large datasets across multiple commodity servers.

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Analytics Vidhya

OCTOBER 12, 2022

Introduction Since the 1970s, relational database management systems have solved the problems of storing and maintaining large volumes of structured data. With the advent of big data, several organizations realized the benefits of big data processing and started choosing solutions like Hadoop to […].

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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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Analytics Vidhya

AUGUST 17, 2022

Introduction Impala is an open-source and native analytics database for Hadoop. This article was published as a part of the Data Science Blogathon. 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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Analytics Vidhya

AUGUST 1, 2022

Introduction HBase is a column-oriented non-relational database management system that operates on Hadoop Distributed File System (HDFS). This article was published as a part of the Data Science Blogathon. HBase provides a fault-tolerant manner of storing sparse data sets, which are prevalent in several big data use cases.

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Analytics Vidhya

OCTOBER 28, 2021

The official description of Hive is- ‘Apache Hive data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Hive gives an SQL-like interface to query data stored in various databases and […].

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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.

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Analytics Vidhya

MARCH 16, 2023

Apache Oozie is a workflow scheduler system for managing Hadoop jobs. It enables users to plan and carry out complex data processing workflows while handling several tasks and operations throughout the Hadoop ecosystem. Introduction This article will be a deep guide for Beginners in Apache Oozie.

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Smart Data Collective

MARCH 27, 2019

The good news is that a number of Hadoop solutions can be invaluable for people that are trying to get the most bang for their buck. How does Hadoop technology help with key couponing and frugal living? Fortunately, Hadoop and other big data technologies are playing an important role in addressing all of these challenges.

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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. 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 […].

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Analytics Vidhya

JULY 29, 2022

Introduction One of the sources of Big Data is the traditional application management system or the interaction of applications with relational databases using RDBMS. Such RDBMS-generated Big Data is kept in the relational database structure of Relational Database Servers. Big Data storage and analysis […].

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phData

MARCH 7, 2023

The task of keeping multiple databases in sync so that data is accurate, up-to-date, and highly available is every data consumer’s biggest challenge. Oracle is one of the largest IT companies whose flagship product, Oracle Database, is a relational database management system. What is Oracle? What is Oracle GoldenGate?

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Analytics Vidhya

APRIL 26, 2022

Introduction on Big Data & Hadoop The amount of data in our world is growing exponentially. The post Getting Started with Big Data & Hadoop appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. It is estimated that at least 2.5

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Pickl AI

JULY 29, 2024

Summary: A Hadoop cluster is a collection of interconnected nodes that work together to store and process large datasets using the Hadoop framework. Introduction A Hadoop cluster is a group of interconnected computers, or nodes, that work together to store and process large datasets using the Hadoop framework.

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Analytics Vidhya

APRIL 29, 2022

Different organizations make use of different databases like an oracle database storing transactional data, MySQL for storing product data, and many others for different tasks. This article was published as a part of the Data Science Blogathon. storing the data […].

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Pickl AI

SEPTEMBER 17, 2024

In addition to traditional structured data (like databases), there is a wealth of unstructured and semi-structured data (such as emails, videos, images, and social media posts). This section will highlight key tools such as Apache Hadoop, Spark, and various NoSQL databases that facilitate efficient Big Data management.

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Pickl AI

AUGUST 9, 2024

Variety It encompasses the different types of data, including structured data (like databases), semi-structured data (like XML), and unstructured formats (such as text, images, and videos). It is built on the Hadoop Distributed File System (HDFS) and utilises MapReduce for data processing.

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Precisely

MARCH 9, 2023

Hadoop, Snowflake, Databricks and other products have rapidly gained adoption. We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data.

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Analytics Vidhya

SEPTEMBER 18, 2022

Relational databases, enterprise data warehouses, and NoSQL systems are all examples of data storage. This article was published as a part of the Data Science Blogathon. Introduction Apache SQOOP is a tool designed to aid in the large-scale export and import of data into HDFS from structured data repositories.

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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.

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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.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. This is particularly advantageous when dealing with exponentially growing data volumes.

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Smart Data Collective

APRIL 8, 2020

Data warehouse, also known as a decision support database, refers to a central repository, which holds information derived from one or more data sources, such as transactional systems and relational databases. They have undergone significant transformation since then, with modern warehouses housing largescale terabyte capacities.

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Alation

FEBRUARY 20, 2020

We decided to address these needs for SQL engines over Hadoop in Alation 4.0. Alation Connect previously synced metadata and query logs from data storage systems including the Hive Metastore on Hadoop and databases from Teradata, IBM, Oracle, SqlServer, Redshift, Vertica, SAP Hana and Greenplum. In the release of Alation 4.0,

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Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. 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.

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Pickl AI

AUGUST 1, 2023

Data Engineers work to build and maintain data pipelines, databases, and data warehouses that can handle the collection, storage, and retrieval of vast amounts of data. Data Storage: Storing the collected data in various storage systems, such as relational databases, NoSQL databases, data lakes, or data warehouses.

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Smart Data Collective

FEBRUARY 21, 2020

Maintaining product databases. Database Design Electronic System Management. Advanced Communication Data mining tools like Hadoop. Engineers with knowledge of Hadoop and other data mining tools can earn even more. Conducting research programs. Inventing electrical products. Answering questions and requests.

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Big Data Big Data Hadoop Data Mining 111

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 195

Data Science Machine Learning Machine Learning Data Visualization 195

Smart Data Collective

AUGUST 9, 2023

Don’t Be Afraid to Change Database Platforms Picking out the right analytical database can go a long way toward making sense of all the data your organization is collecting. Companies that have revenue information stored in a conventional flat spreadsheet might do well to opt for a relational database like MySQL or Postgres.

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Women in Big Data

SEPTEMBER 7, 2024

Advances in big data technology like Hadoop, Hive, Spark and Machine Learning algorithms have made it possible to interpret and utilize this variety of data effectively. Structured Structured data is quantitative and highly organized, typically managed within relational databases. Examples include HTML files, graphs, and web pages.

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IBM Journey to AI blog

MARCH 21, 2024

Leveraging distributed storage and processing frameworks such as Apache Hadoop, Spark or Dask accelerates data ingestion, transformation and analysis. Additionally, using in-memory databases and caching mechanisms minimizes latency and improves data access speeds.

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Pickl AI

AUGUST 21, 2024

Crawlers then store this information in a database for indexing. Structured data can be easily imported into databases or analytical tools. Lead Generation Companies can scrape contact information from websites to build databases of potential customers. This ensures that the indexed information remains current and accurate.

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Pickl AI

APRIL 6, 2023

In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Sound knowledge of relational databases or NoSQL databases like Cassandra. This includes Database System Management (SQL or Non-SQL), Data Warehousing, Machine Learning, programming basics, and ETL.

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IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science 99

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Smart Data Collective

SEPTEMBER 15, 2021

Apache Hadoop needs no introduction when it comes to the management of large sophisticated storage spaces, but you probably wouldn’t think of it as the first solution to turn to when you want to run an email marketing campaign. Some groups are turning to Hadoop-based data mining gear as a result.

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Smart Data Collective

AUGUST 26, 2021

Also, it extracts historical weather data from various databases. Hadoop has also helped considerably with weather forecasting. For instance, Tomorrow’s weather API retrieves crucial weather data, such as temperature, precipitation, air quality index, pollen index, etc., from various sources.

Analytics 132

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Mlearning.ai

MARCH 15, 2023

Familiarity with Databases; SQL for structured data, and NOSQL for unstructured data. Knowledge of big data platforms like; Hadoop and Apache Spark. Knowledge of big data platforms like; Hadoop and Apache Spark. Experience with machine learning frameworks for supervised and unsupervised learning.

Data Science 52

Data Science Analytics Analytics Data Analyst 52