ProjectPro

MARCH 19, 2015

Relational Databases – The fundamental concept behind databases, namely MySQL, Oracle Express Edition, and MS-SQL that uses SQL, is that they are all Relational Database Management Systems that make use of relations (generally referred to as tables) for storing data.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

FEBRUARY 16, 2023

According to the 8,786 data professionals participating in Stack Overflow's survey, SQL is the most commonly-used language in data science. Despite the buzz surrounding NoSQL , Hadoop , and other big data technologies, SQL remains the most dominant language for data operations among all tech companies.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Knowledge Hut

MARCH 27, 2024

Real-time analytics platforms in big data apply logic and math to gain faster insights into data, resulting in a more streamlined and informed decision-making process. Some open-source technology for big data analytics are : Hadoop. Listed below are the top and the most popular tools for big data analytics : 1.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

AltexSoft

OCTOBER 8, 2021

The tool supports all sorts of data loading and processing: real-time, batch, streaming (using Spark), etc. ODI has a wide array of connections to integrate with relational database management systems ( RDBMS) , cloud data warehouses, Hadoop, Spark , CRMs, B2B systems, while also supporting flat files, JSON, and XML formats.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

JUNE 16, 2023

Data preparation: Because of flaws, redundancy, missing numbers, and other issues, data gathered from numerous sources is always in a raw format. After the data has been extracted, data analysts must transform the unstructured data into structured data by fixing data errors, removing unnecessary data, and identifying potential data.

Programming Language 52

Programming Language Data Science Data Analytics Cloud Computing 52

ProjectPro

AUGUST 24, 2021

Google BigQuery receives the structured data from workers. Finally, the data is passed to Google Data studio for visualization. Learn how to process Wikipedia archives using Hadoop and identify the lived pages in a day. Understand the importance of Qubole in powering up Hadoop and Notebooks.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Note, though, that not any type of web scraping is legal.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Transformation section.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 1- Automating the Lakehouse's data intake.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

APRIL 26, 2016

Table of Contents Hadoop Hive Interview Questions and Answers Scenario based or Real-Time Interview Questions on Hadoop Hive Other Interview Questions on Hadoop Hive Hadoop Hive Interview Questions and Answers 1) What is the difference between Pig and Hive ? Used for Structured Data Schema Schema is optional.

Hadoop 40

Hadoop Metadata SQL Database 40