Knowledge Hut

MARCH 15, 2024

Making decisions in the database space requires deciding between RDBMS (Relational Database Management System) and NoSQL, each of which has unique features. RDBMS uses SQL to organize data into structured tables, whereas NoSQL is more flexible and can handle a wider range of data types because of its dynamic schemas.

NoSQL 52

NoSQL Database-centric Relational Database PostgreSQL 52

ProjectPro

NOVEMBER 14, 2015

Data Migration RDBMSs were inefficient and failed to manage the growing demand for current data. This failure of relational database management systems triggered organizations to move their data from RDBMS to Hadoop. This data can be analysed using big data analytics to maximise revenue and profits.

Hadoop 52

Hadoop Project Big Data Healthcare 52

DareData

JANUARY 30, 2023

For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production. Examples of relational databases include MySQL or Microsoft SQL Server.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

Database 52

Database NoSQL Management Relational Database 52

Rockset

JANUARY 5, 2022

So I don’t fault you for resisting my message, which is that the SQL database that came of age in the 80s still has a critical role to play today in moving data-driven companies from batch to real-time analytics. In many tech circles, SQL databases remain synonymous with old-school on-premises databases like Oracle or DB2.

Database 52

Database SQL NoSQL Raw Data 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

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

MARCH 19, 2015

As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT professionals often debate the merits of SQL vs. NoSQL but with increasing business data management needs, NoSQL is becoming the new darling of the big data movement.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., They enable the connection of various data sources to the Hadoop environment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

JUNE 23, 2016

Thus, this solution is not practically recommended and this is when Apache Sqoop comes to the rescues of users that allows users to import data on HDFS. Apache Sqoop is a lifesaver for people facing challenges with moving data out of a data warehouse into the Hadoop environment. directly into HDFS or Hive or HBase.

Hadoop 40

Hadoop MySQL Relational Database Java 40

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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

Knowledge Hut

JANUARY 11, 2024

Data science is the field of study that deals with a huge volume of data using modern technologically driven tools and techniques to find some sort of pattern and derive meaningful information out of it that eventually helps in business and financial decisions. This work is done by financial data scientists.

Finance 93

Finance Data Science Programming Language Machine Learning 93

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