Data Engineering Weekly

MARCH 24, 2024

The author goes beyond comparing the tools to various offerings from streaming vendors in stream processing and Kafka protocol-supported systems. As we predicted in the key trends of 2023 about Apache Flink as a clear winner in the stream processing frameworks, we see Confluent offering Flink as a service.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

SEPTEMBER 26, 2023

This is particularly valuable in today's data landscape, where information comes in various shapes and sizes. Effective Data Storage: Azure Synapse offers robust data storage solutions that cater to the needs of modern data-driven organizations. Key Features of Databricks 1.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional who is in charge of designing, implementing, and maintaining data processing systems and solutions on the Microsoft Azure cloud platform. A Data Engineer is responsible for designing the entire architecture of the data flow while taking the needs of the business into account.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

MARCH 28, 2024

They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines. Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Experience with Azure services for big data processing and analytics.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? Below, we share what the “basic” data platform looks like and list some hot tools in each space (you’re likely using several of them): The modern data platform is composed of five critical foundation layers. Data Storage and Processing The first layer?

Building 52

Building BI Data Lake Data Governance 52

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

AltexSoft

MARCH 14, 2023

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59

IT Data Warehouse Data Governance Data Lake 59

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.) Source Code: Yelp Review Analysis 2.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Silectis

JANUARY 3, 2021

Data engineers design, build, and maintain data pipelines that transform data from a raw state to a useful one, ready for analysis or data science modeling. Data Integration Combining data from various, disparate sources into one unified view. HDFS stands for Hadoop Distributed File System.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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

ProjectPro

NOVEMBER 15, 2021

It was built from the ground up for interactive analytics and can scale to the size of Facebook while approaching the speed of commercial data warehouses. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage. CMAK is developed to help the Kafka community.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Big Data analytics processes and tools. Data ingestion.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 83

Engineering Raw Data Data Science Scala 83

ProjectPro

FEBRUARY 21, 2023

Knowledge of the definition and architecture of AWS Big Data services and their function in the data engineering lifecycle, including data collection and ingestion, data analytics, data storage, data warehousing, data processing, and data visualization.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

phData: Data Engineering

JANUARY 3, 2022

This involves: Building data pipelines and efficiently storing data for tools that need to query the data. Analyzing the data, ensuring it adheres to data governance rules and regulations. Understanding the pros and cons of data storage and query options.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

ProjectPro

AUGUST 21, 2015

Core components of a Hadoop application are- 1) Hadoop Common 2) HDFS 3) Hadoop MapReduce 4) YARN Data Access Components are - Pig and Hive Data Storage Component is - HBase Data Integration Components are - Apache Flume, Sqoop, Chukwa Data Management and Monitoring Components are - Ambari, Oozie and Zookeeper.

Hadoop 40

Hadoop Big Data Metadata Java 40