Knowledge Hut

MARCH 15, 2024

The job description for Azure data engineer that I have elucidated below focuses more on foundational tasks while providing opportunities for learning and growth within the field: Data ingestion: This role involves assisting in the process of collecting and importing data from various sources into Azure storage solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Certification 52

Striim

JULY 10, 2024

Data transformation includes normalizing data, encoding categorical variables, and aggregating data at the appropriate granularity. The surge in package theft due to more online shopping overwhelmed traditional security measures and data management systems, which showcased significant operational vulnerabilities.

Management 52

Management Transportation Machine Learning High Quality Data 52

DareData

JULY 5, 2023

The architecture of a data lake project may contain multiple components, including the Data Lake itself, one or multiple Data Warehouses or one or multiple Data Marts. The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

ProjectPro

DECEMBER 7, 2021

Big data pipelines must be able to recognize and process data in various formats, including structured, unstructured, and semi-structured, due to the variety of big data. Over the years, companies primarily depended on batch processing to gain insights. However, it is not straightforward to create data pipelines.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

NOVEMBER 15, 2021

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. Calcite has chosen to stay out of the data storage and processing business.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

SEPTEMBER 21, 2023

Besides Elasticsearch, which is the hub for indexing, searching, and complex data analytics, the stacks include the following tools Beats are lightweight data shippers that are part of the Elastic Stack. Beats facilitate data movement from source to destination, which can be either Elasticsearch or Logstash, depending on the use case.

Engineering 52

Engineering NoSQL Programming Language Java 52

phData: Data Engineering

JANUARY 3, 2022

This likely requires you to aggregate data from your ERP system, your supply chain system, potentially third-party vendors, and data around your internal business structure. Performance It’s not as simple as having data correct and available for a data engineer. Data must also be performant.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52