AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Rockset

MARCH 27, 2019

You have complex, semi-structured data—nested JSON or XML, for instance, containing mixed types, sparse fields, and null values. It's messy, you don't understand how it's structured, and new fields appear every so often. Organizations will typically build hard-to-maintain ETL pipelines to feed data into their SQL systems.

Raw Data 40

Raw Data SQL NoSQL Datasets 40

AltexSoft

JULY 29, 2022

On top of HDFS, the Hadoop ecosystem provides HBase , a NoSQL database designed to host large tables, with billions of rows and millions of columns. To facilitate data ingestion, there are Apache Flume aggregating log data from multiple servers and Apache Sqoop designed to transport information between Hadoop and relational (SQL) databases.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. Big Data analytics processes and tools.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Rockset

SEPTEMBER 3, 2020

PostgreSQL has been gaining a lot of traction recently because of its ability to provide both RDBMS-like and NoSQL-like features which enable data to be stored in traditional rows and columns while also providing the option to store complete JSON objects. To begin with, you can leverage the power of the SQL query language.

MongoDB 40

MongoDB PostgreSQL SQL Database 40

ProjectPro

OCTOBER 28, 2015

Getting data into the Hadoop cluster plays a critical role in any big data deployment. Data ingestion is important in any big data project because the volume of data is generally in petabytes or exabytes. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc.,

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

NOVEMBER 15, 2021

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Trino is a distributed SQL query engine. Trino Source: trino.io

Big Data 52

Big Data Project Metadata Programming Language 52

Netflix Tech

DECEMBER 14, 2018

data access semantics that guarantee repeatable data read behavior for client applications. System Requirements Support for Structured Data The growth of NoSQL databases has broadly been accompanied with the trend of data “schemalessness” (e.g.,

Media 96

Media Database Metadata Data Schemas 96

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

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

Knowledge Hut

DECEMBER 13, 2023

Tech Mahindra Tech Mahindra is a service-based company with a data-driven focus. The complex data activities, such as data ingestion, unification, structuring, cleaning, validating, and transforming, are made simpler by its self-service. It also makes it easier to load the data into destination databases.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59