Accessibility, Aggregated Data and Relational Database

Accessibility

Aggregated Data

Relational Database

Data Lake vs. Data Warehouse: Differences and Similarities

U-Next

SEPTEMBER 7, 2022

As a general rule, the bottom tier of a data warehouse is a relational database system. A database is also a relational database system. Rows and columns make up a relational database system, and a large amount of data is stored in it. . The DW and databases support multi-user access.

Data Lake

Data Lake Data Warehouse Unstructured Data Amazon Web Services

How to Become an Azure Data Engineer? 2023 Roadmap

Knowledge Hut

NOVEMBER 17, 2023

To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. You should be able to create intricate queries that use subqueries, join numerous tables, and aggregate data.

Data Engineering

Data Engineering Data Engineer Engineering Scala

Join 16,000+

Insiders

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Webinars

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Understanding User Needs and Satisfying Them

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Leading the Development of Profitable and Sustainable Products

How To Get Promoted In Product Management

MORE WEBINARS

Trending Sources

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

FEBRUARY 8, 2023

This serverless data integration service can automatically and quickly discover structured or unstructured enterprise data when stored in data lakes in Amazon S3, data warehouses in Amazon Redshift, and other databases that are a component of the Amazon Relational Database Service.

AWS

AWS Scala Metadata Data Lake

Webinars

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Understanding User Needs and Satisfying Them

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Leading the Development of Profitable and Sustainable Products

How To Get Promoted In Product Management

MORE WEBINARS

ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

AltexSoft

DECEMBER 23, 2022

In ELT, raw data is loaded into the destination, and then it receives transformations when it’s needed. Organizations now operate huge amounts of various data stored in multiple systems. ELT makes it easier to manage and access all this information by allowing both raw and cleaned data to be loaded and stored for further analysis.

Process

Process Building Raw Data Data Lake

Data Marts: What They Are and Why Businesses Need Them

AltexSoft

AUGUST 4, 2021

Some sweets are presented on your display cases for quick access while the rest is kept in the storeroom. Now let’s think of sweets as the data required for your company’s daily operations. Modern cloud warehouses make it possible to store data in its raw formats similarly to data lakes. Data mart designing.

Data Lake

Data Lake Data Warehouse ETL Tools Telecommunication

DynamoDB Filtering and Aggregation Queries Using SQL on Rockset

Rockset

SEPTEMBER 13, 2022

Further, data is king, and users want to be able to slice and dice aggregated data as needed to find insights. Users don't want to wait for data engineers to provision new indexes or build new ETL chains. They want unfettered access to the freshest data available.

SQL

SQL Database Relational Database AWS

20 Best Open Source Big Data Projects to Contribute on GitHub

ProjectPro

NOVEMBER 15, 2021

When any particular project is open-sourced, it makes the source code accessible to anyone. The adaptability and technical superiority of such open-source big data projects make them stand out for community use. DataFrames are used by Spark SQL to accommodate structured and semi-structured data.

Big Data

Big Data Project Metadata Programming Language

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

MARCH 14, 2023

That’s why some MDS tools are commercial distributions designed to be low-code or even no-code, making them accessible to data practitioners with minimal technical expertise. This means that companies don’t necessarily need a large data engineering team. Data democratization.

IT Data Warehouse Data Governance Data Lake

A Beginner’s Guide to Learning PySpark for Big Data Processing

ProjectPro

JANUARY 25, 2022

PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization The PySpark Architecture The PySpark architecture consists of various parts such as Spark Conf, RDDs, Spark Context, Dataframes , etc.

Big Data

Big Data Data Process Process Kafka

Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

OCTOBER 28, 2015

The major difference between Sqoop and Flume is that Sqoop is used for loading data from relational databases into HDFS while Flume is used to capture a stream of moving data. Table of Contents Hadoop ETL tools: Sqoop vs Flume-Comparison of the two Best Data Ingestion Tools What is Sqoop in Hadoop?

ETL Tools

ETL Tools Hadoop Relational Database Unstructured Data

100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering

Data Engineering Data Engineer Engineering Hadoop

14 Best Database Certifications in 2023 to Boost Your Career

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

Database Certification MongoDB MySQL

The Good and the Bad of the Elasticsearch Search and Analytics Engine

AltexSoft

SEPTEMBER 21, 2023

Accessible via a unified API, these new features enhance search relevance and are available on Elastic Cloud. The Elastic Stacks Elasticsearch is integral within analytics stacks, collaborating seamlessly with other tools developed by Elastic to manage the entire data workflow — from ingestion to visualization.

Engineering

Engineering NoSQL Programming Language Java

Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

DECEMBER 7, 2021

The second step for building etl pipelines is data transformation, which entails converting the raw data into the format required by the end-application. The transformed data is then placed into the destination data warehouse or data lake. It can also be made accessible as an API and distributed to stakeholders.

Data Pipeline

Data Pipeline Architecture Kafka AWS

Data Engineering Digest

Data Lake vs. Data Warehouse: Differences and Similarities

How to Become an Azure Data Engineer? 2023 Roadmap

Webinars

Trending Sources

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

Webinars

ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

Data Marts: What They Are and Why Businesses Need Them

DynamoDB Filtering and Aggregation Queries Using SQL on Rockset

20 Best Open Source Big Data Projects to Contribute on GitHub

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

A Beginner’s Guide to Learning PySpark for Big Data Processing

Sqoop vs. Flume Battle of the Hadoop ETL tools

100+ Data Engineer Interview Questions and Answers for 2023

14 Best Database Certifications in 2023 to Boost Your Career

The Good and the Bad of the Elasticsearch Search and Analytics Engine

Data Pipeline- Definition, Architecture, Examples, and Use Cases

Stay Connected