Knowledge Hut

DECEMBER 21, 2023

NoSQL This database management system has been designed in a way that it can store and handle huge amounts of semi-structured or unstructured data. NoSQL databases can handle node failures. Different databases have different patterns of data storage. It is also horizontally scalable.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Knowledge Hut

APRIL 25, 2024

Create data storage and acceptance solutions for websites, especially those that take payments. Knowledge of Databases When working on a project, you must realize that data storage is essential since they contain a lot of information. Therefore, having a solid grasp of the database is essential.

Programming Language 98

Programming Language Java Algorithm MySQL 98

Edureka

MARCH 5, 2024

Full stack developers most frequently utilize tech stacks that combine front-end, back-end, and database technologies. Among the well-liked tech stacks are: Mean Stack: MongoDB : A NoSQL database that is adaptable and scalable for managing massive volumes of data because it stores data in a format resembling JSON.

MySQL 40

MySQL MongoDB NoSQL PostgreSQL 40

Knowledge Hut

MAY 31, 2023

It is also one of the most important database projects for students. Top Database Project Ideas Using MongoDB MongoDB is a popular NoSQL database management system that is widely used for web-based applications. Plus, MongoDB also enables efficient indexing, which facilitates quick query execution at scale.

Database 52

Database Coding MongoDB Project 52

ProjectPro

NOVEMBER 5, 2014

Hadoop is the way to go for organizations that do not want to add load to their primary storage system and want to write distributed jobs that perform well. MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets.

MongoDB 40

MongoDB Hadoop NoSQL Big Data 40

AltexSoft

MAY 12, 2023

Structured data is formatted in tables, rows, and columns, following a well-defined, fixed schema with specific data types, relationships, and rules. A fixed schema means the structure and organization of the data are predetermined and consistent. You can’t just keep it in SQL databases, unlike structured data.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

JUNE 23, 2023

Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala. You should be thorough with technicalities related to relational and non-relational databases, Data security, ETL (extract, transform, and load) systems, Data storage, automation and scripting, big data tools, and machine learning.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. And most of this data has to be handled in real-time or near real-time.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

SEPTEMBER 6, 2023

Over the past decade, the IT world transformed with a data revolution. Back when I studied Computer Science in the early 2000s, databases like MS Access and Oracle ruled. The rise of big data and NoSQL changed the game. Systems evolved from simple to complex, and we had to split how we find data from where we store it.

Database 52

Database Certification MongoDB MySQL 52

Cloud Academy

JANUARY 27, 2022

These fundamentals will give you a solid foundation in data and datasets. Knowing SQL means you are familiar with the different relational databases available, their functions, and the syntax they use. Have knowledge of regular expressions (RegEx) It is essential to be able to use regular expressions to manipulate data.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

U-Next

AUGUST 10, 2022

The essential knowledge base for Data Engineers is SQL. Without a solid understanding of SQL, you cannot administer an RDBMS (relational database management). Database Management: Understanding how to create and operate a data warehouse is a crucial skill.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 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

Knowledge Hut

APRIL 3, 2023

This includes handling data storage, user authentication, and server configuration. This includes the server, database, and application logic, as well as the APIs and other interfaces that connect the backend with the front end of the application. What is Backend Development? for building scalable and efficient web applications.

Programming Language 52

Programming Language Computer Science Portfolio PostgreSQL 52

AltexSoft

JULY 29, 2022

No matter the actual size, each cluster accommodates three functional layers — Hadoop distributed file systems for data storage, Hadoop MapReduce for processing, and Hadoop Yarn for resource management. As a result, today we have a huge ecosystem of interoperable instruments addressing various challenges of Big Data.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

JANUARY 19, 2022

Here are some role-specific skills you should consider to become an Azure data engineer- Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Who should take the certification exam?

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

MARCH 14, 2023

Databases store key information that powers a company’s product, such as user data and product data. The ones that keep only relational data in a tabular format are called SQL or relational database management systems (RDBMSs). Some popular databases are Postgres and MongoDB.

IT 59

IT Data Warehouse Data Governance Data Lake 59

ProjectPro

JULY 30, 2021

There are many cloud computing job roles like Cloud Consultant, Cloud reliability engineer, cloud security engineer, cloud infrastructure engineer, cloud architect, data science engineer that one can make a career transition to. PaaS packages the platform for development and testing along with data, storage, and computing capability.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

Rockset

SEPTEMBER 13, 2022

DynamoDB is a NoSQL database provided by AWS. It's a fully managed database, and it has growing popularity in both high-scale applications and in serverless applications. It has direct connectors for a number of primary data stores, including DynamoDB, MongoDB, Kafka, and many relational databases.

SQL 52

SQL Database Relational Database AWS 52

ProjectPro

JANUARY 19, 2022

Supports big data technology well. Supports high availability for data storage. Supports uniform consistency of data throughout different locations. The more you use the product, the cheaper the subscription plans. Support large-scale implementation of machine learning algorithms. Similar pricing as AWS.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

JULY 27, 2021

Below are some big data interview questions for data engineers based on the fundamental concepts of big data, such as data modeling, data analysis , data migration, data processing architecture, data storage, big data analytics, etc.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis.

Hadoop 52

Hadoop Project Big Data Healthcare 52