Rockset

JUNE 7, 2022

. — Editor Databases are a key architectural component of many applications and services. Traditionally, organizations have chosen relational databases like SQL Server, Oracle , MySQL and Postgres. Relational databases use tables and structured languages to store data.

MongoDB 52

MongoDB NoSQL Non-relational Database Relational Database 52

Knowledge Hut

JULY 24, 2023

In this blog, we will talk about the future of database management. Get ready to discover fascinating insights, uncover mind-boggling facts, and explore the transformative potential of cutting-edge technologies like blockchain, cloud computing, and artificial intelligence.

Database 52

Database NoSQL Management Relational Database 52

AltexSoft

JUNE 26, 2023

The ultimate goal of data integration is to gather all valuable information in one place, ensuring its integrity , quality, accessibility throughout the company, and readiness for BI, statistical data analysis, or machine learning. Most modern platforms expose public or private APIs as a way to access their data directly.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

NOVEMBER 23, 2021

But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. Real-time access.

Process 69

Process Data Lake Metadata Data Warehouse 69

AltexSoft

OCTOBER 8, 2021

At the same time, you get rid of the “data silos” problem: When no team or department has a unified view of all data due to fragments being locked in separate databases with limited access. Usually, data integration software is divided into on-premise, cloud-based, and open-source types. Cloud-based data integration tools.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

JANUARY 31, 2023

Map Reduce programs in cloud computing are parallel, making them ideal for executing large-scale data processing across multiple machines in a cluster. Database Testing: As the name implies, this testing often entails validating data acquired from numerous databases. Here, data is accessible even if the machine fails.

Big Data 52

Big Data Hadoop AWS Relational Database 52

U-Next

AUGUST 3, 2022

Along with certain Cloud integration solutions like Azure Blob Factory and Talend, there are the traditional ETL or ELT solutions like Oracle Enterprise Integration, Microsoft DTS, and Sap DataStage. Non-Technical Competencies. The required information may be gathered using a variety of practical techniques. Data Scientist Skills.

Retail 52

Retail Data Science Computer Science Entertainment 52

ProjectPro

JULY 27, 2021

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms. Differentiate between relational and non-relational database management systems.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

JANUARY 2, 2024

Platform: Web, Desktop, Cloud, and Scientific computing. While numerous database systems exist, the core essence of SQL querying remains consistent across them, making it a timeless skill in the tech world. Levels: Beginner to Advanced Skills: Database Querying, Management, and Design. Platform: Web, Cloud, and System tools.

Programming Language 52

Programming Language Programming Java NoSQL 52