Knowledge Hut

SEPTEMBER 26, 2023

Born out of the minds behind Apache Spark, an open-source distributed computing framework, Databricks is designed to simplify and accelerate data processing, data engineering, machine learning, and collaborative analytics tasks. This flexibility allows organizations to ingest data from virtually anywhere.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. The process requires extracting data from diverse sources, typically via APIs. Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake Machine Learning BI 64

WeCloudData

OCTOBER 19, 2021

Conclusion WeCloudData helped a client build a flexible data pipeline to address the needs from multiple business units requiring different sets, views and timelines of job market data.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

Conclusion WeCloudData helped a client build a flexible data pipeline to address the needs from multiple business units requiring different sets, views and timelines of job market data.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 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

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? With companies moving their data platforms to the cloud, the emergence of cloud-native solutions ( data warehouse vs data lake or even a data lakehouse ) have taken over the market, offering more accessible and affordable options for storing data relative to many on-premises solutions.

Building 52

Building BI Data Lake Data Governance 52

Confluent

OCTOBER 16, 2019

Along with using Postgres (or KSQL as shown above) for analytics, the data can be streamed using Kafka Connect into S3, from where it can serve multiple roles. In S3, it can be seen as the “cold storage”, or the data lake, against which as-yet-unknown applications and processes may be run. variation_status" : "LATE".

Kafka 19

Kafka Building Data Coding 19

Knowledge Hut

JUNE 26, 2023

Finnhub API with Kafka for Real-Time Financial Market Data Pipeline Project Overview: The goal of this project is to construct a streaming data pipeline by making use of the real-time financial market data API provided by Finnhub.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

JULY 6, 2023

It is a built-in Massively parallel processing (MPP) data lake house to handle all your infrastructure observability and security needs. However, there are costs associated with data ingestion. It is a free standalone application that makes working with Azure Storage data on Windows, macOS, and Linux effortlessly.

Amazon Web Services 52

Amazon Web Services Data Lake Java SQL 52

Knowledge Hut

APRIL 25, 2023

Fivetran Fivetran is a popular cloud-based data integration platform that simplifies the process of data engineering by automating data pipeline creation, management, and maintenance. Cloud Composer can integrate with other GCP services like BigQuery, Cloud Storage, and Cloud Dataflow.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Monte Carlo

NOVEMBER 22, 2024

At the front end, you’ve got your data ingestion layer —the workhorse that pulls in data from everywhere it lives. Gone are the days of just dumping everything into a single database; modern data architectures typically use a combination of data lakes and warehouses.

Data Engineering 52

Data Engineering Data Engineer Building Engineering 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Data Engineering Weekly

DECEMBER 18, 2024

These New Age Data IDEs will be characterized by: Seamless Integration: They will seamlessly integrate the entire data lifecycle, from data ingestion and transformation to analysis, visualization, and deployment, all within a unified environment. Tools like lakebyte.ai are the beginning of such a revolution.

Data Engineering 115

Data Engineering Data Engineer Engineering Data Lake 115

Data Engineering Weekly

JANUARY 24, 2025

The world of data management is undergoing a rapid transformation. The rise of cloud storage, coupled with the increasing demand for real-time analytics, has led to the emergence of the Data Lakehouse. This paradigm combines the flexibility of data lakes with the performance and reliability of data warehouses.

Architecture 77

Architecture Metadata Data Ingestion Data Lake 77

Edureka

APRIL 15, 2025

Officially titled “Implementing Data Engineering Solutions Using Microsoft Fabric” , this assessment evaluates a candidate’s ability to design and implement data engineering solutions using Microsoft Fabric. Data Factory : Automate workflows and manage data movement across multiple sources.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52