ProjectPro

JUNE 6, 2025

An ETL developer should be familiar with SQL/NoSQL databases and data mapping to understand data storage requirements and design warehouse layout. Cloud Computing Every business will eventually need to move its data-related activities to the cloud. And data engineers will likely gain the responsibility for the entire process.

Data Engineer

ProjectPro

JUNE 6, 2025

Source: LinkedIn The rise of cloud computing has further accelerated the need for cloud-native ETL tools , such as AWS Glue , Azure Data Factory , and Google Cloud Dataflow. As more organizations shift to the cloud, the demand for ETL engineers with expertise in these platforms is soaring.

Data Engineer

ProjectPro

JUNE 6, 2025

Stream processing engines often have in-memory storage for temporary data, while durable storage solutions like Apache Hadoop, Amazon S3, or Google Cloud Storage serve as repositories for long-term storage of processed data. Google Cloud DataFlow With 4.6

Data Ingestion

ProjectPro

JUNE 6, 2025

The other types of databases include key-value, columnar, time-series, NoSQL , etc. To handle NoSQL databases (that do not contain data in rows and columns), data engineers usually use Elasticsearch. Python allows users to manage NoSQL databases with its elasticsearch library.

Data Engineer

ProjectPro

JUNE 6, 2025

Apache Beam Source: Google Cloud Platform Apache Beam is an advanced unified programming open-source model launched in 2016. To execute pipelines, beam supports numerous distributed processing back-ends, including Apache Flink, Apache Spark , Apache Samza, Hazelcast Jet, Google Cloud Dataflow , etc.

Big Data

ProjectPro

JUNE 6, 2025

A data engineer is expected to be adept at using ETL (Extract, Transform and Load) tools and be able to work with both SQL and NoSQL databases. To do this, you need to learn how to put models in production with popular cloud platforms — Google Cloud, Amazon AWS, and Microsoft Azure.

Engineering

ProjectPro

JUNE 6, 2025

This project builds a comprehensive ETL and analytics pipeline, from ingestion to visualization, using Google Cloud Platform. Store the data in in Google Cloud Storage to ensure scalability and reliability. Load raw data into Google Cloud Storage, preprocess it using Mage VM, and store results in BigQuery.

Data Engineer

ProjectPro

JUNE 6, 2025

Google BigQuery Google BigQuery is a fully managed, serverless, and highly scalable data warehouse solution offered by Google Cloud. It is designed to help organizations store, process, and analyze vast amounts of data quickly and efficiently. Scaling can be complex and may require expertise.

Data Storage

ProjectPro

JUNE 6, 2025

and is accessed by data engineers with the help of NoSQL database management systems. The companies’ choice of cloud service providers depends on their data storage requirements. And the three popular choices for that are Microsoft Azure , Amazon Web Services (AWS), and Google Cloud Platform (GCP).

Data Engineer

ProjectPro

JUNE 6, 2025

Based on scalability, performance, and data structure, data is stored in suitable storage systems, such as relational databases, NoSQL databases, or data lakes. Automated infrastructure deployment and scalable data processing ensure efficient, reliable, and cost-effective financial data analytics on the Google Cloud Platform.

Data Science

ProjectPro

JUNE 6, 2025

Allows integration with other systems - Python is beneficial for integrating multiple scripts and other systems, including various databases (such as SQL and NoSQL databases), data formats (such as JSON, Parquet, etc.), Since it is a component of the Google Cloud Platform , it is simple to integrate with other programs you may be using.

Data Analysis Tools

ProjectPro

JUNE 6, 2025

Also, acquire a solid knowledge of databases such as the NoSQL or Oracle database. Organizations employ a variety of providers including AWS, Google Cloud , and Azure for their BI and Machine Learning applications. Table Storage in Microsoft Azure holds structured NoSQL data.

Data Engineer

ProjectPro

JUNE 6, 2025

Ability to write, analyze, and debug SQL queries Solid understanding of ETL (Extract, Transfer, Load) tools, NoSQL, Apache Spark System, and relational DBMS. Data Engineer - Salary According to a salary survey, the average base pay for data engineers is about $114,835. However, this can exceed up to $200,000 with expertise and specialization.

Data Science

ProjectPro

JUNE 6, 2025

This certification exam assesses a candidate's ability to design data processing systems, optimize complex machine learning models, and build and optimize data processing systems on the Google Cloud Platform. They excel in designing data pipelines, optimizing data storage and querying, and ensuring data governance and compliance.

Big Data

ProjectPro

JUNE 6, 2025

They get used in NoSQL databases like Redis, MongoDB , data warehousing. Use cases for EBS are Software development and testing, NoSQL databases, organization-wide application. Google Cloud Platform(GCP) Interview Questions and Answers 1. What is the difference between Google Compute App and Google Compute Engine?

Cloud Computing

ProjectPro

JUNE 6, 2025

For example, a dataset with billions of records may require specialized storage solutions such as distributed file systems or NoSQL databases to store and access the data efficiently. Another approach to scalability is using cloud-based machine learning platforms such as Amazon SageMaker or Google Cloud AI Platform.

Machine Learning

ProjectPro

JUNE 6, 2025

SQL, NoSQL) are essential. Additionally, skills in big data technologies such as Hadoop and Spark and cloud platforms like AWS, Azure, or Google Cloud are highly valued. Thorough knowledge of programming languages like Python, Java, and SQL and experience with database systems (e.g.,

Machine Learning

ProjectPro

JUNE 6, 2025

Deployment & Real-Time Monitoring: Deploy the solution on cloud platforms like AWS Lambda, Azure Functions, or Google Cloud Run for scalable processing. Use Graph-Based Search Algorithms (A)* and Dijkstra’s Algorithm for rapid path recalculations. Data Required for the Project Order History & Patterns (e.g.,

Data Science

Data Engineering Podcast

FEBRUARY 11, 2018

Is timescale compatible with systems such as Amazon RDS or Google Cloud SQL? Is timescale compatible with systems such as Amazon RDS or Google Cloud SQL? How is Timescale implemented and how has the internal architecture evolved since you first started working on it? What impact has the 10.0 What impact has the 10.0

PostgreSQL

Confluent

MAY 22, 2019

A scalable, distributed, peer-to-peer NoSQL database, Scylla is a perfect fit for consuming the variety, velocity, and volume of data (often time-series) coming directly from users, devices, and sensors spread across geographic locations. We use the Google Cloud API to automate the deployment of a ScyllaDB cluster. Ansible 2.3.

Kafka

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. Examples include Amazon DynamoDB and Google Cloud Datastore.

Database

Knowledge Hut

NOVEMBER 7, 2023

Google Cloud Google Cloud is a dependable, user-friendly, and secure cloud computing solution from one of today's most powerful technology companies. Despite having a smaller service portfolio than Azure, Google Cloud can nonetheless fulfill all of your IaaS and PaaS needs.

Cloud Computing

AltexSoft

MAY 12, 2023

Semi-structured data is typically stored in NoSQL databases, such as MongoDB, Cassandra, and Couchbase, following hierarchical or graph data models. Amazon S3, Google Cloud Storage, Microsoft Azure Blob Storage), NoSQL databases (e.g., Google Cloud Storage can also be used as a data lake system.

Unstructured Data

Confluent

MARCH 4, 2019

Thus, they created different Terraform scripts for each cloud provider that would be offered as an option, such as Amazon Web Services (AWS) , Google Cloud and Microsoft Azure. The first layer would abstract infrastructure details such as compute, network, firewalls, and storage—and they used Terraform to implement that.

Cloud

Knowledge Hut

APRIL 25, 2023

These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases.

Data Engineer

ProjectPro

JANUARY 24, 2023

Since its public release in 2011, BigQuery has been marketed as a unique analytics cloud data warehouse tool that requires no virtual machines or hardware resources. BigQuery is a highly scalable data warehouse platform with a built-in query engine offered by Google Cloud Platform. What is Google BigQuery Used for?

Bytes

Knowledge Hut

JUNE 23, 2023

Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala. Equip yourself with the experience and know-how of Hadoop, Spark, and Kafka, and get some hands-on experience in AWS data engineer skills, Azure, or Google Cloud Platform. Step 4 - Who Can Become a Data Engineer?

Data Engineer

Ascend.io

JUNE 22, 2023

Ascend’s platform is the first modern, cloud-based data pipeline automation tool capable of ingesting data from all major platforms and delivering it to MotherDuck (relational, NoSQL, event streams/queues, APIs and custom data sources). Next, build out connections to your sources and pipelines that deliver data to MotherDuck.

NoSQL

Rockset

MARCH 21, 2019

Function-as-a-Service frameworks, such as AWS Lambda, Azure Functions, and Google Cloud Functions, go quite far in realizing that vision for stateless applications, but the real challenge comes when applications need to deal with state.

SQL

ProjectPro

SEPTEMBER 6, 2021

So, are you ready to explore the differences between two cloud giants, AWS vs. google cloud? Amazon brought innovation in technology and enjoyed a massive head start compared to Google Cloud, Microsoft Azure , and other cloud computing services. GCP Storage Google Cloud storage provides high availability.

AWS

Edureka

AUGUST 29, 2024

Databases: Knowledgeable about SQL and NoSQL databases. Data Warehousing: Experience in using tools like Amazon Redshift, Google BigQuery, or Snowflake. Projects: Engage in projects with a component that involves data collection, processing, and analysis. Big Data Technologies: Aware of Hadoop, Spark, and other platforms for big data.

Data Engineer

Rockset

JANUARY 28, 2022

However, Seesaw’s DynamoDB database stored the data in its own NoSQL format that made it easy to build applications, just not analytical ones. And that was only possible if both internal and external users could drill down into the freshest data possible in order to get the answers they needed.

NoSQL

ProjectPro

JUNE 17, 2015

2) NoSQL Databases -Average Salary$118,587 If on one side of the big data virtuous cycle is Hadoop, then the other is occupied by NoSQL databases. According to Dice, the number of big data jobs for professionals with experience in a NoSQL databases like MongoDB, Cassandra and HBase has increased by 54% since last year.

Cloud Computing

Knowledge Hut

MARCH 26, 2024

Cloud Solutions Architect Role Overview: Design and implement cloud-based solutions leveraging platforms like AWS, Azure, or Google Cloud to meet business objectives. The Cloud Computing course syllabus covers most aspects of this field in detail.

Amazon Web Services

Cloud Academy

JANUARY 27, 2022

Some basic real-world examples are: Relational, SQL database: e.g. Microsoft SQL Server Document-oriented database: MongoDB (classified as NoSQL) The Basics of Data Management, Data Manipulation and Data Modeling This learning path focuses on common data formats and interfaces.

Certification

Cloudera

APRIL 2, 2019

HBase is a distributed, scalable NoSQL database that enterprises use to power applications that need random, real time read/write access to semi-structured data. Testing also conducted on Hewlett Packard Enterprise servers and Google Cloud Platform .

NoSQL

Knowledge Hut

DECEMBER 21, 2023

For a data engineer career, you must have knowledge of data storage and processing technologies like Hadoop, Spark, and NoSQL databases. Cloud Data Engineer A cloud data engineer designs, builds, and maintains data infrastructures to run on cloud platforms such as AWS or Google Cloud.

Data Engineer