Knowledge Hut

JUNE 26, 2023

From analysts to Big Data Engineers, everyone in the field of data science has been discussing data engineering. When constructing a data engineering project, you should prioritize the following areas: Multiple sources of data (APIs, websites, CSVs, JSON, etc.)

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Knowledge Hut

JUNE 30, 2023

Key Benefits and Takeaways: Understand data intake strategies and data transformation procedures by learning data engineering principles with Python. Investigate alternative data storage solutions, such as databases and data lakes.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

MAY 14, 2024

Apache ORC (Optimized Row Columnar) : In 2013, ORC was developed for the Hadoop ecosystem to improve the efficiency of data storage and retrieval.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

AltexSoft

SEPTEMBER 23, 2021

Harmonization of data includes numerous operations, such as data cleaning, indexing, mapping, formatting, providing semantic consistency, and many more. As the output, the data collected from various sources becomes consistent and readable for the end-point systems like analytics applications. Azure Data Factory.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

ProjectPro

MARCH 15, 2016

Hadoop is beginning to live up to its promise of being the backbone technology for Big Data storage and analytics. Companies across the globe have started to migrate their data into Hadoop to join the stalwarts who already adopted Hadoop a while ago. The solution to this problem is straightforward.

Hadoop 40

Hadoop Retail Healthcare Banking 40

ProjectPro

JANUARY 31, 2023

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 52

Big Data Hadoop Relational Database AWS 52

Striim

NOVEMBER 8, 2023

A data mesh is technology-agnostic and underpins four main principles described in-depth in this blog post by Zhamak Dehghani. The four data mesh principles aim to solve major difficulties that have plagued data and analytics applications for a long time.

Architecture 52

Architecture Generalist Government Datasets 52

ProjectPro

SEPTEMBER 6, 2021

Popular instances where GCP is used widely are machine learning analytics, application modernization, security, and business collaboration. It provides cloud storage and computing services across 93 availability zones and 29 geographic regions.

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

AltexSoft

JULY 18, 2023

It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs. Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications.

Big Data 52

Big Data Data Process Process Hadoop 52

ProjectPro

JULY 15, 2021

You can also exchange images securely utilizing the application. It is recommended to use SQL database for data storage as it comes with built-in security tools and features. Popular ride-hailing services, such as Uber and Ola, have used such cloud-based analytics applications for data-driven decision-making.

Cloud Computing 40

Cloud Computing Cloud Project Banking 40

Knowledge Hut

JULY 26, 2023

Apache Cassandra is a well-known columnar database that can handle enormous quantities of data across dispersed clusters. It is widely utilized for its great scalability, fault tolerance, and quick write performance, making it ideal for large-scale data storage and real-time analytics applications.

Database 52

Database NoSQL Telecommunication MongoDB 52

phData: Data Engineering

JULY 18, 2023

CDWs are designed for running large and complex queries across vast amounts of data, making them ideal for centralizing an organization’s analytical data for the purpose of business intelligence and data analytics applications. This noticeably saves time on copying and drastically reduces data storage costs.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. What are the main components of a big data architecture?

Big Data 52

Big Data Coding Project Hadoop 52