Data Engineering Podcast

JANUARY 13, 2020

This requires a new class of data storage which can accomodate that demand without having to rearchitect your system at each level of growth. YugabyteDB is an open source database designed to support planet scale workloads with high data density and full ACID compliance.

SQL 100

SQL MongoDB PostgreSQL Database Design 100

ProjectPro

JUNE 6, 2025

He is an expert SQL user and is well in both database management and data modeling techniques. On the other hand, a Data Engineer would have similar knowledge of SQL, database management, and modeling but would also balance those out with additional skills drawn from a software engineering background.

Data Engineer 59

Data Engineer Data Engineering Engineering ETL Tools 59

ProjectPro

JUNE 6, 2025

Since data needs to be accessible easily, organizations use Amazon Redshift as it offers seamless integration with business intelligence tools and helps you train and deploy machine learning models using SQL commands. Amazon Redshift is helping over 10000 customers with its unique features and data analytics properties.

Data Pipeline 64

Data Pipeline AWS Project Building 64

ProjectPro

JUNE 6, 2025

This is where AWS data engineering tools come into the scenario. AWS data engineering tools make it easier for data engineers to build AWS data pipelines, manage data transfer, and ensure efficient data storage. In other words, these tools allow engineers to level-up data engineering with AWS.

AWS 52

AWS Data Engineer Data Engineering Engineering 52

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

Monte Carlo

AUGUST 15, 2023

Data testing Data teams that are on-premises don’t have the scale or rich metadata from central query logs or modern table formats to easily run machine learning driven anomaly detection (in other words data observability ). For example, customer_id should never be NULL or currency_conversion should never have a negative value.

Data Storage 88

Data Storage Cloud Metadata Media 88

ProjectPro

JUNE 6, 2025

Learn the A-Z of Big Data with Hadoop with the help of industry-level end-to-end solved Hadoop projects. Databricks vs. Azure Synapse: Architecture Azure Synapse architecture consists of three components: Data storage, processing, and visualization integrated into a single platform. Databricks supports Python, R, and SQL.

Programming Language 40

Programming Language Data Lake Scala Data Warehouse 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

Work in teams to create algorithms for data storage, data collection, data accessibility, data quality checks, and, preferably, data analytics. Connect with data scientists and create the infrastructure required to identify, design, and deploy internal process improvements.

Data Engineer 58

Data Engineer Data Engineering Engineering Amazon Web Services 58

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

Linked services are used majorly for two purposes in Data Factory: For a Data Store representation, i.e., any storage system like Azure Blob storage account, a file share, or an Oracle DB/ SQL Server instance. Can you Elaborate more on Data Factory Integration Runtime?

Data Lake 60

Data Lake Metadata SQL Datasets 60

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

ProjectPro

JUNE 6, 2025

Snowflake Basic Interview Questions Below are some basic questions for the Snowflake data engineer interview. SQL database serves as the foundation for Snowflake. As is typical of a SQL database, Snowflake offers its query tool and enables multi-statement transactions, role-based security, etc. Is Snowflake an ETL tool?

Amazon Web Services 40

Amazon Web Services Data Warehouse ETL Tools AWS 40

ProjectPro

JUNE 6, 2025

A serverless, affordable, highly scalable data warehouse with integrated machine learning capabilities, Google BigQuery, is a useful product of the Google Cloud Platform. This blog covers the topmost Google BigQuery interview questions and answers to help you become a successful GCP data engineer.

Google Cloud 40

Google Cloud Cloud Storage SQL MongoDB 40

Teradata

MAY 30, 2025

Introduction to Teradata VantageCloud Lake on AWS Teradata VantageCloud Lake, a comprehensive data platform, serves as the foundation for our data mesh architecture on AWS. The data mesh architecture Key components of the data mesh architecture 1.

AWS 52

AWS Architecture Building Amazon Web Services 52

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

Source : Storage.googleapis.com This GCP project involves collecting different and real-time traffic data. This data is then analyzed and mined using business intelligence tools. Technologies like SQL are used on GCP. Data Lake using Google Cloud Platform What is a Data Lake?

Google Cloud 58

Google Cloud Project Data Lake Healthcare 58

ProjectPro

JUNE 6, 2025

Over the past few years, there has been remarkable progress in two fields: data storage and warehousing. This is primarily due to the growth and development of cloud-based data storage solutions, which enable organizations across all industries to scale more efficiently, pay less upfront, and perform better.

Big Data 40

Big Data Project Bytes Google Cloud 40

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

The following prerequisites serve as a strong foundation for beginners, ensuring they have the fundamental knowledge required to start learning Snowflake effectively- Basic SQL Knowledge Gaining familiarity with SQL is crucial since Snowflake relies heavily on SQL for data querying and manipulation.

Data Warehouse 40

Data Warehouse SQL AWS Big Data 40

ProjectPro

JUNE 6, 2025

The candidate must be capable of analyzing and debugging SQL queries and skilled in scripting languages like Java, Python, C#, Perl, R, etc. SQL (Structured Query Language) Data warehouse engineers must have a thorough knowledge of SQL to build and maintain data warehouses.

Data Warehouse 40

Data Warehouse Engineering Business Intelligence Google Cloud 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

The Azure DP 203 certification equips you with the skills and knowledge needed to navigate the Azure data ecosystem with confidence and expertise. This certification validates your ability to design and implement Microsoft Azure data storage solutions. Table of Contents Why Enroll for DP 203: Data Engineering on Microsoft Azure?

Certification 40

Certification Data Storage Big Data Data Engineer 40

ProjectPro

JUNE 6, 2025

So, let’s dive into the list of the interview questions below - List of the Top Amazon Data Engineer Interview Questions Explore the following key questions to gauge your knowledge and proficiency in AWS Data Engineering. Become a Job-Ready Data Engineer with Complete Project-Based Data Engineering Course !

Data Engineer 40

Data Engineer Data Engineering Engineering 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

Christophe Blefari

JUNE 21, 2024

Both companies have added Data and AI to their slogan, Snowflake used to be The Data Cloud and now they're The AI Data Cloud. A UX where you buy a single tool combining engine and storage, where all you have to do is flow data in, write SQL, and it's done. —with Databricks you buy an engine.

Metadata 147

Metadata Data Warehouse BI Scala 147

Christophe Blefari

JUNE 16, 2023

I'm now under the Berlin rain with 20° When I write in these conditions I feel like a tortured author writing a depressing novel while actually today I'll speak about the AI Act, Python, SQL and data platforms. The ultimate SQL guide — After the last canva on data interviews, here's a canva to learn SQL.

Programming Language 130

Programming Language SQL PostgreSQL Data 130

ProjectPro

JUNE 6, 2025

Increased Efficiency: Cloud data warehouses frequently split the workload among multiple servers. As a result, these servers handle massive volumes of data rapidly and effectively. Handle Big Data: Storage in cloud-based data warehouses may increase independently of computational resources. What is Data Purging?

Data Warehouse 40

Data Warehouse Data Mining Recruitment Database 40

ProjectPro

JUNE 6, 2025

AWS Data Engineering is one of the core elements of AWS Cloud in delivering the ultimate solution to users. AWS Data Engineering helps big data professionals manage Data Pipelines, Data Transfer, and Data Storage. Table of Contents Who is an AWS Data Engineer? What Does an AWS Data Engineer Do?

AWS 45

AWS Data Engineer Data Engineering Amazon Web Services 45

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 Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 40

Big Data Hadoop Relational Database NoSQL 40

The Pragmatic Engineer

JUNE 13, 2023

Agoda co-locates in all data centers, leasing space for its racks and the largest data center consumes about 1 MW of power. It uses Spark for the data platform. For transactional databases, it’s mostly the Microsoft SQL Server, but also other databases like PostgreSQL, ScyllaDB and Couchbase.

Cloud 242

Cloud Database Utilities BI 242

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

Snowflake has a market share of 18.33% in the current industry because of its disruptive architecture for data storage, analysis, processing, and sharing. In contrast, Databricks is less expensive when it comes to data storage since it gives its clients different storage environments that can be configured for specific purposes.

Google Cloud 40

Google Cloud Cloud Storage Data Lake Data Storage 40

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Though basic and easy to use, traditional table storage formats struggle to keep up. Track data files within the table along with their column statistics. Contact phData Today!

Architecture 52

Architecture Systems Data Lake Google Cloud 52

ProjectPro

JUNE 6, 2025

The Microsoft Azure Data Factory Training is a beginner-friendly guide that explores the benefits and functionality of the Azure Data Factory. This training course showcases ADF’s scalability, flexibility, and seamless integration with Azure services like Blob Storage, SQL Database, and Data Lake Storage.

Data Lake 40

Data Lake Cloud Computing Data Workflow Data Pipeline 40

ProjectPro

JUNE 6, 2025

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 40

NoSQL Database Hadoop Big Data 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