ProjectPro

JUNE 6, 2025

Spark SQL, for instance, enables structured data processing with SQL. Highly flexible and scalable Real-time stream processing Spark Stream – Extension of Spark enables live-stream from massive data volumes from different web sources. Hive uses HQL, while Spark uses SQL as the language for querying the data.

Hadoop 45

Hadoop Java Big Data Tools SQL 45

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

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

Table of Contents What are Data Warehousing Tools? Why Choose a Data Warehousing Tool? Scalability to meet evolving data demands. Standard SQL support for querying. Flexible pricing options with encryption and data controls. Loading data can be time-consuming, especially for large volumes.

Data Storage 58

Data Storage PostgreSQL Data Warehouse AWS 58

Rockset

JULY 6, 2022

Traditional databases, with their wholly-inflexible structures, are brittle. So are schemaless NoSQL databases, which capably ingest firehoses of data but are poor at extracting complex insights from that data. Companies carefully engineered their ETL data pipelines to align with their schemas (not vice-versa).

NoSQL 52

NoSQL SQL Systems PostgreSQL 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

Kickstart your data engineer career with end-to-end solved big data projects for beginners. What does a Data Modeler do? The data modeler builds, implements, and analyzes data architecture and data modeling solutions using relational, dimensional, and NoSQL databases.

NoSQL 40

NoSQL ETL Tools Certification SQL 40

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

Rockset

NOVEMBER 19, 2020

In this blog post, we show how Rockset’s Smart Schema feature lets developers use real-time SQL queries to extract meaningful insights from raw semi-structured data ingested without a predefined schema. In SQL-based systems, the data is strongly and statically typed.

Structured Data 40

Structured Data SQL NoSQL Raw Data 40

ProjectPro

JUNE 6, 2025

This process involves data collection from multiple sources, such as social networking sites, corporate software, and log files. Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. Data Processing: This is the final step in deploying a big data model.

Big Data 40

Big Data Hadoop Relational Database NoSQL 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

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

A graph database is a specialized database designed to efficiently store and query interconnected data. Unlike traditional relational databases, which structure data in tables, rows, and columns, graph databases represent data as nodes (entities) with edges (relationships) between them. Is graph database SQL or NoSQL?

Database 40

Database Database-centric Relational Database MongoDB 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

What are DBT macros, and how do they enhance SQL functionality in DBT? DBT (Data Build Tool) macros are reusable pieces of SQL code written in Jinja – a templating language that enhances SQL's functionality by enabling dynamic and modular code creation. How can DBT be used to handle incremental data loads?

Raw Data 40

Raw Data SQL Datasets Data Pipeline 40

ProjectPro

JUNE 6, 2025

Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data warehouses store highly transformed, structured data that is preprocessed and designed to serve a specific purpose. Data from data warehouses is queried using SQL.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

JUNE 6, 2025

Additional libraries on top of Spark Core enable a variety of SQL, streaming, and machine learning applications. Spark can integrate with Apache Cassandra to process data stored in this NoSQL database. Spark can connect to relational databases using JDBC, allowing it to perform operations on SQL databases.

Hadoop 68

Hadoop Metadata Java Datasets 68

ProjectPro

JUNE 6, 2025

ETL Data Engineers work with different data formats, such as structured, semi-structured, and unstructured data, and ensure that pipelines are efficient, scalable, and optimized for performance. Clean, reformat, and aggregate data to ensure consistency and readiness for analysis.

Data Engineer 40

Data Engineer Data Engineering Engineering ETL Tools 40

ProjectPro

JUNE 6, 2025

A data warehouse is a relational database that has been technologically enhanced for accessing, storing, and querying massive amounts of data. Traditionally, engineers could store only structured data in data warehouses. Modern data warehouses can, however, combine both structured and unstructured data.

Data Science 40

Data Science Data Engineer Data Engineering Engineering 40

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

Rockset

JANUARY 5, 2022

So I don’t fault you for resisting my message, which is that the SQL database that came of age in the 80s still has a critical role to play today in moving data-driven companies from batch to real-time analytics. In many tech circles, SQL databases remain synonymous with old-school on-premises databases like Oracle or DB2.

Database 52

Database SQL NoSQL Raw Data 52

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. Trino Source: trino.io

Big Data 49

Big Data Project Metadata Programming Language 49

ProjectPro

JUNE 6, 2025

Hive is a data warehousing and SQL-like query language system built on top of Hadoop. Hive provides a high-level abstraction over Hadoop's MapReduce framework, enabling users to interact with data using familiar SQL syntax. Users interact with Hive using Hive Query Language (HQL), a SQL-like language.

Big Data 40

Big Data Architecture Project Hadoop 40

ProjectPro

JUNE 6, 2025

Top 15 Data Analysis Tools to Explore in 2025 | Trending Data Analytics Tools 1. Google Data Studio 10. Looker Data Analytics Tools Comparison Analyze Data Like a Pro with These Data Analysis Tools FAQs on Data Analysis Tools Data Analysis Tools- What are they? Power BI 4. Apache Spark 6.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

Rockset

DECEMBER 17, 2021

If you were one of the 15,000 people who attended Coalesce 2021 , you will likely remember SQL Draw, the Slack-based game combining SQL with cartesian geometry, art, creativity and teamwork. If you missed it, you can read more about SQL Draw on the Omnata website. Query Lambdas make it easy to create data APIs.

SQL 52

SQL NoSQL Database Design Metadata 52

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

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineer 40

Data Engineer Data Engineering Engineering 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

ProjectPro

JUNE 6, 2025

Data Engineers usually opt for database management systems for database management and their popular choices are MySQL, Oracle Database, Microsoft SQL Server, etc. When working with real-world data, it may only sometimes be the case that the information is stored in rows and columns.

Data Engineer 49

Data Engineer Data Engineering Engineering Hadoop 49

Knowledge Hut

DECEMBER 26, 2023

Certain roles like Data Scientists require a good knowledge of coding compared to other roles. Data Science also requires applying Machine Learning algorithms, which is why some knowledge of programming languages like Python, SQL, R, Java, or C/C++ is also required.

Data Science 97

Data Science BI Data Mining Business Intelligence 97

AltexSoft

JUNE 7, 2021

MapReduce performs batch processing only and doesn’t fit time-sensitive data or real-time analytics jobs. Data engineers who previously worked only with relational database management systems and SQL queries need training to take advantage of Hadoop. Data storage options. Cassandra excels at streaming data analysis.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JUNE 6, 2025

LLM-powered agents are at the forefront of this shift, capable of understanding natural language queries, automating SQL generation, and even performing predictive analysis like many professional data analysts do. They are ideal for users who may not have technical expertise in data analysis tasks or querying databases.

Data Analysis 40

Data Analysis Building Raw Data Datasets 40

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. NoSQL databases.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JUNE 6, 2025

Data engineers leverage AWS Glue's capability to offer all features, from data extraction through transformation into a standard Schema. 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

Rockset

MARCH 27, 2019

You have complex, semi-structured data—nested JSON or XML, for instance, containing mixed types, sparse fields, and null values. It's messy, you don't understand how it's structured, and new fields appear every so often. Organizations will typically build hard-to-maintain ETL pipelines to feed data into their SQL systems.

Raw Data 40

Raw Data SQL NoSQL Datasets 40

ProjectPro

JUNE 6, 2025

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., into HBase, Hive or HDFS.

ETL Tools 40

ETL Tools Hadoop Relational Database Unstructured Data 40

ProjectPro

FEBRUARY 16, 2023

At the heart of these data engineering skills lies SQL that helps data engineers manage and manipulate large amounts of data. Did you know SQL is the top skill listed in 73.4% of data engineer job postings on Indeed? Almost all major tech organizations use SQL. use SQL, compared to 61.7%

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52