ProjectPro

JUNE 6, 2025

The relational databases- Amazon Aurora , Amazon Redshift, and Amazon RDS use SQL (Structured Query Language) to work on data saved in tabular formats. Amazon DynamoDB is a NoSQL database that stores data as key-value pairs. NoSQL Document Database. Data Model Structured data with tables and columns.

Amazon Web Services 40

Amazon Web Services NoSQL Relational Database AWS 40

ProjectPro

JUNE 6, 2025

The process of creating logical data models is known as logical data modeling. Prepare for Your Next Big Data Job Interview with Kafka Interview Questions and Answers 2. How would you create a Data Model using SQL commands? You can also use the INSERT command to fill your tables with data.

Data Warehouse 53

Data Warehouse NoSQL PostgreSQL Relational Database 53

ProjectPro

JUNE 6, 2025

Apache Hive Architecture Apache Hive has a simple architecture with a Hive interface, and it uses HDFS for data storage. Data in Apache Hive can come from multiple servers and sources for effective and efficient processing in a distributed manner. Spark SQL, for instance, enables structured data processing with SQL.

Hadoop 45

Hadoop Java Big Data Tools SQL 45

ProjectPro

JUNE 6, 2025

With BigQuery, users can process and analyze petabytes of data in seconds and get insights from their data quickly and easily. Moreover, BigQuery offers a variety of features to help users quickly analyze and visualize their data. It provides powerful query capabilities for running SQL queries to access and analyze data.

Bytes 40

Bytes Google Cloud Data Warehouse Cloud Storage 40

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 MongoDB Relational Database 52

ProjectPro

JUNE 6, 2025

Setting up the cloud to store data to ensure high availability is one of the most critical tasks for big data specialists. Due to this, knowledge of cloud computing platforms and tools is now essential for data engineers working with big data.

Data Engineer 40

Data Engineer Data Engineering PostgreSQL Engineering 40

ProjectPro

JUNE 6, 2025

Microsoft offers Azure Data Lake, a cloud-based data storage and analytics solution. It is capable of effectively handling enormous amounts of structured and unstructured data. Therefore, it is a popular choice for organizations that need to process and analyze big data files. Workload Classification.

Data Lake 40

Data Lake Amazon Web Services Data Warehouse SQL 40

ProjectPro

JUNE 6, 2025

They include relational databases like Amazon RDS for MySQL, PostgreSQL, and Oracle and NoSQL databases like Amazon DynamoDB. Database Variety: AWS provides multiple database options such as Aurora (relational), DynamoDB (NoSQL), and ElastiCache (in-memory), letting startups choose the best-fit tech for their needs.

AWS 40

AWS Database Amazon Web Services MySQL 40

Monte Carlo

OCTOBER 31, 2024

Proficiency in Programming Languages Knowledge of programming languages is a must for AI data engineers and traditional data engineers alike. In addition, AI data engineers should be familiar with programming languages such as Python , Java, Scala, and more for data pipeline, data lineage, and AI model development.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52

ProjectPro

JUNE 6, 2025

Questions span data warehousing , ETL processes, big data technologies , SQL, data processing, optimization, security, privacy, and data visualization. The on-site assessments cover SQL , analytics, machine learning , and algorithms. How would you optimize a SQL query for a large dataset in a data warehouse?

Data Engineer 40

Data Engineer Data Engineering Engineering NoSQL 40

ProjectPro

JUNE 6, 2025

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. Hop onto the repository here: [link] 7.

Big Data 49

Big Data Project Metadata Programming Language 49

ProjectPro

JUNE 6, 2025

They ensure the data flows smoothly and is prepared for analysis. Apache Hadoop Development and Implementation Big Data Developers often work extensively with Apache Hadoop , a widely used distributed data storage and processing framework. Understand how to write complex SQL queries and optimize them for performance.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

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 40

Big Data Hadoop Relational Database AWS 40

ProjectPro

JUNE 6, 2025

We will now describe the difference between these three different career titles, so you get a better understanding of them: Data Engineer A data engineer is a person who builds architecture for data storage. They can store large amounts of data in data processing systems and convert raw data into a usable format.

Engineering 75

Engineering Software Engineering Deep Learning Software Engineer 75

ProjectPro

JUNE 6, 2025

In 2024, the data engineering job market is flourishing, with roles like database administrators and architects projected to grow by 8% and salaries averaging $153,000 annually in the US (as per Glassdoor ). These trends underscore the growing demand and significance of data engineering in driving innovation across industries.

Data Engineer 59

Data Engineer Data Engineering Project Engineering 59

Data Engineering Podcast

JUNE 10, 2018

Summary With the increased ease of gaining access to servers in data centers across the world has come the need for supporting globally distributed data storage. To address these shortcomings the engineers at Cockroach Labs have built a globally distributed SQL database with full ACID semantics in Cockroach DB.

PostgreSQL 100

PostgreSQL NoSQL Relational Database SQL 100

ProjectPro

SEPTEMBER 16, 2021

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies.

NoSQL 52

NoSQL Database Hadoop Big Data 52

ProjectPro

JUNE 6, 2025

An ETL (Extract, Transform, Load) Data Engineer is responsible for designing, building, and maintaining the systems that extract data from various sources, transform it into a format suitable for data analysis, and load it into data warehouses, lakes, or other data storage systems.

Data Engineer 40

Data Engineer Data Engineering Engineering ETL Tools 40

Knowledge Hut

APRIL 25, 2024

Each of these technologies has its own strengths and weaknesses, but all of them can be used to gain insights from large data sets. As organizations continue to generate more and more data, big data technologies will become increasingly essential. Let's explore the technologies available for big data.

Big Data 98

Big Data Technology NoSQL Hadoop 98

ProjectPro

JUNE 6, 2025

Azure Cosmos DB Pricing Azure Cosmos DB Tutorial: Getting Started with NoSQL Database Real-World Applications of Azure Cosmos DB Boosting Performance in Cosmos DB: Top Tips and Techniques Azure Cosmos DB Project Ideas Enhance Your Data Management Skills with ProjectPro's Guided Azure Projects! What is Cosmos DB Used for?

Database 40

Database Management MongoDB NoSQL 40

ProjectPro

JUNE 6, 2025

FAQs on Data Engineering Skills Mastering Data Engineering Skills: An Introduction to What is Data Engineering Data engineering is the process of designing, developing, and managing the infrastructure needed to collect, store, process, and analyze large volumes of data. 2) Does data engineering require coding?

Data Engineer 49

Data Engineer Data Engineering Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

Transform unstructured data in the form in which the data can be analyzed Develop data retention policies Skills Required to Become a Big Data Engineer Big Data Engineer Degree - Educational Background/Qualifications Bachelor’s degree in Computer Science, Information Technology, Statistics, or a similar field is preferred at an entry level.

Big Data 40

Big Data Data Engineer Data Engineering Engineering 40

ProjectPro

JUNE 6, 2025

Distributed web-scale cache stores, like Memcached and Redis, that offer an in-memory cache of key-value type data. High-performance databases, including relational ones like MySQL and NoSQL ones like MongoDB and Cassandra. Using Oracle BYOL or SQL Server for 750 hours on a single-AZ Amazon RDS db.t2.micro micro, db.t3.micro,

PostgreSQL 40

PostgreSQL MySQL AWS Relational Database 40

ProjectPro

JUNE 6, 2025

This is important since big data can be structured or unstructured or any other format. Therefore, data engineers need data transformation tools to transform and process big data into the desired format. Database tools/frameworks like SQL, NoSQL , etc., Apache Hive 3 features in the latest HDP 3.0

Data Engineer 45

Data Engineer Data Engineering Engineering Kafka 45

ProjectPro

JUNE 6, 2025

Data Architect Salary How to Become a Data Architect - A 5-Step Guide Become a Data Architect - Key Takeaways FAQs on Data Architect Career Path What is a Data Architect Role? A solid understanding of SQL is also essential to manage, access, and manipulate data from relational databases.

Data Architect 40

Data Architect Data Mining Programming Language Java 40

ProjectPro

JUNE 6, 2025

Spark saves data in memory (RAM), making data retrieval quicker and faster when needed. Spark is a low-latency computation platform because it offers in-memory data storage and caching. Additional libraries on top of Spark Core enable a variety of SQL, streaming, and machine learning applications.

Hadoop 68

Hadoop Metadata Java Datasets 68

ProjectPro

JUNE 6, 2025

Hive is a data warehousing and SQL-like query language system built on top of Hadoop. It is designed to facilitate querying and managing large datasets in a distributed storage environment. Hive provides a high-level abstraction over Hadoop's MapReduce framework, enabling users to interact with data using familiar SQL syntax.

Big Data 40

Big Data Architecture Project Hadoop 40

ProjectPro

JUNE 6, 2025

These AWS resources offer the highest level of usability and are created specifically for the performance optimization of various applications using content delivery features, data storage, and other methods. AWS Redshift Amazon Redshift offers petabytes of structured or semi-structured data storage as an ideal data warehouse option.

AWS 40

AWS Data Engineer Data Engineering Engineering 40

ProjectPro

JUNE 6, 2025

All this data is stored in a database that requires SQL-based queries for retrieval and transformations, making it essential for every data professional to learn SQL for data science and machine learning. Table of Contents Why SQL for Data Science? What is SQL? Why SQL for Data Science?

Data Science 40

Data Science SQL NoSQL Programming Language 40

ProjectPro

JUNE 6, 2025

Data warehouses store highly transformed, structured data that is preprocessed and designed to serve a specific purpose. Data is generally not loaded into a data warehouse unless a use case has been defined for the data. Data from data warehouses is queried using SQL.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

DECEMBER 17, 2021

All this data is stored in a database that requires SQL-based queries for retrieval and transformations, making it essential for every data professional to learn SQL for data science and machine learning. Table of Contents Why SQL for Data Science? What is SQL? Why SQL for Data Science?

Data Science 52

Data Science SQL NoSQL Programming Language 52

Data Engineering Podcast

AUGUST 19, 2018

There are a few ways that graph structures and properties can be implemented, including the ability to store data in the vertices connecting nodes and the structures that can be contained within the nodes themselves. How does the query interface and data storage in DGraph differ from other options?

Database 100

Database PostgreSQL Transportation NoSQL 100

AltexSoft

JUNE 7, 2021

Master Nodes control and coordinate two key functions of Hadoop: data storage and parallel processing of data. Worker or Slave Nodes are the majority of nodes used to store data and run computations according to instructions from a master node. Data storage options. Data access options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JUNE 6, 2025

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 53

Cloud Computing Cloud Amazon Web Services AWS 53

ProjectPro

JUNE 6, 2025

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 40

Hadoop Project Big Data Scala 40

Cloudera

NOVEMBER 23, 2021

HBase is a column-oriented data storage architecture that is formed on top of HDFS to overcome its limitations. Although the HBase architecture is a NoSQL database, it eases the process of maintaining data by distributing it evenly across the cluster. Apache Phoenix is a RDBMS, an ANSI SQL interface. Apache HBase.

Database 91

Database Non-relational Database NoSQL Government 91

Knowledge Hut

JULY 24, 2023

The future of SQL (Structured Query Language) is a scalding subject among professionals in the data-driven world. As data generation continues to skyrocket, the demand for real-time decision-making, data processing, and analysis increases. How is SQL Being Utilized? billion in 2022 to $154.6

Database 52

Database SQL Process NoSQL 52