Data Engineering Weekly

DECEMBER 2, 2023

The paper discusses trade-offs among data freshness, resource cost, and query performance. Ref: [link] In the current state of the data infrastructure, we use a combination of multiple specialized data storage and processing engines to achieve this balance. Presto tried with RaptorX. It doesn’t fly.

IT 85

IT BI AWS Kafka 85

AltexSoft

JULY 18, 2023

This module can ingest live data streams from multiple sources, including Apache Kafka , Apache Flume , Amazon Kinesis , or Twitter, splitting them into discrete micro-batches. Netflix leverages Spark Streaming and Kafka for near real-time movie recommendations. Big data processing.

Big Data 52

Big Data Data Process Process Hadoop 52

Knowledge Hut

APRIL 25, 2024

Big data is a term that refers to the massive volume of data that organizations generate every day. In the past, this data was too large and complex for traditional data processing tools to handle. There are a variety of big data processing technologies available, including Apache Hadoop, Apache Spark, and MongoDB.

Big Data 98

Big Data Technology Hadoop NoSQL 98

ProjectPro

JANUARY 25, 2022

Features of PySpark Features that contribute to PySpark's immense popularity in the industry- Real-Time Computations PySpark emphasizes in-memory processing, which allows it to perform real-time computations on huge volumes of data. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency.

Big Data 52

Big Data Data Process Process Kafka 52

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. Source Code: Stock and Twitter Data Extraction Using Python, Kafka, and Spark 2.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Christophe Blefari

JANUARY 20, 2024

He wrote some years ago 3 articles defining data engineering field. Some concepts When doing data engineering you can touch a lot of different concepts. formats — This is a huge part of data engineering. Picking the right format for your data storage. Understand Change Data Capture — CDC.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Rockset

AUGUST 21, 2019

Rockset continuously ingests data streams from Kafka, without the need for a fixed schema, and serves fast SQL queries on that data. We created the Kafka Connect Plugin for Rockset to export data from Kafka and send it to a collection of documents in Rockset. This blog covers how we implemented the plugin.

Kafka 40

Kafka IT Data Storage Relational Database 40

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Monte Carlo

MAY 28, 2024

This involves connecting to multiple data sources, using extract, transform, load ( ETL ) processes to standardize the data, and using orchestration tools to manage the flow of data so that it’s continuously and reliably imported – and readily available for analysis and decision-making.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Data Engineering Weekly

DECEMBER 16, 2024

Vector Search and Unstructured Data Processing Advancements in Search Architecture In 2024, organizations redefined search technology by adopting hybrid architectures that combine traditional keyword-based methods with advanced vector-based approaches.

Data Engineering 63

Data Engineering Data Engineer Engineering Unstructured Data 63

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. Any Azure Data Engineer must have experience with Azure’s data storage options, including Azure Cosmos DB, Azure Data Lake Storage, and Azure Blob Storage.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

FEBRUARY 20, 2024

Let’s explore what to consider when thinking about data ingestion tools and explore the leading tools in the field. Consideration What to Look For Integration Capabilities Support for a diverse array of data sources and destinations, ensuring compatibility with your data ecosystem. Cost : It’s open-source software, so free.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Towards Data Science

OCTOBER 7, 2023

Automate engineering and data processes By automating repetitive or mundane aspects of coding and data engineering, generative AI is streamlining workflows and driving productivity for software and data engineers alike. Tools like Tensorflow and HuggingFace are good options to fine-tune your models.

Unstructured Data 98

Unstructured Data Finance SQL Database 98

Knowledge Hut

DECEMBER 26, 2023

They are also accountable for communicating data trends. Let us now look at the three major roles of data engineers. Generalists They are typically responsible for every step of the data processing, starting from managing and making analysis and are usually part of small data-focused teams or small companies.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Knowledge Hut

NOVEMBER 28, 2023

Data engineers design, manage, test, maintain, store, and work on the data infrastructure that allows easy access to structured and unstructured data. Data engineers need to work with large amounts of data and maintain the architectures used in various data science projects. Technical Data Engineer Skills 1.Python

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 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

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. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Cloud Academy

JANUARY 27, 2022

Apache Kafka Amazon MSK and Kafka Under the Hood Apache Kafka is an open-source streaming platform. Learn about the AWS-managed Kafka offering in this course to see how it can be more quickly deployed. Apache Hadoop Introduction to Google Cloud Dataproc Hadoop allows for distributed processing of large datasets.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

AltexSoft

OCTOBER 30, 2021

But with the start of the 21st century, when data started to become big and create vast opportunities for business discoveries, statisticians were rightfully renamed into data scientists. Data scientists today are business-oriented analysts who know how to shape data into answers, often building complex machine learning models.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Knowledge Hut

NOVEMBER 19, 2023

As a result, data engineers working with big data today require a basic grasp of cloud computing platforms and tools. Businesses can employ internal, public, or hybrid clouds depending on their data storage needs, including AWS, Azure, GCP, and other well-known cloud computing platforms.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

U-Next

AUGUST 17, 2022

Because of this, all businesses—from global leaders like Apple to sole proprietorships—need Data Engineers proficient in SQL. NoSQL – This alternative kind of data storage and processing is gaining popularity. Data Engineers must be proficient in Python to create complicated, scalable algorithms.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 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

Data Engineering Weekly

OCTOBER 13, 2024

Data-Arks serves as a vital component in integrating Large Language Models (LLMs) into the analytics workflow, streamlining processes like generating regular metric reports and conducting fraud investigations [link]. The author categorizes these queries into four types: append-only, upsert, min-delta (CDC), and full-delta (CDC).

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

Monte Carlo

FEBRUARY 25, 2025

Data engineering design patterns are repeatable solutions that help you structure, optimize, and scale data processing, storage, and movement. They make data workflows more resilient and easier to manage when things inevitably go sideways. Popular tools include Apache Kafka , Apache Flink , and AWS Kinesis.

Designing 52

Designing Data Engineering Data Engineer Engineering 52

Edureka

FEBRUARY 9, 2023

Here are some role-specific skills to consider if you want to become an Azure data engineer: Programming languages are used in the majority of data storage and processing systems. Data engineers must be well-versed in programming languages such as Python, Java, and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 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. CMAK is developed to help the Kafka community.

Big Data 52

Big Data Project Metadata Programming Language 52

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

ProjectPro

JANUARY 19, 2022

Here are some role-specific skills you should consider to become an Azure data engineer- Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Who should take the certification exam?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

ProjectPro

JUNE 4, 2015

Defining Architecture Components of the Big Data Ecosystem Core Hadoop Components 3) MapReduce- Distributed Data Processing Framework of Apache Hadoop MapReduce Use Case: >4)YARN Key Benefits of Hadoop 2.0 2) Hadoop Distributed File System (HDFS) - The default big data storage layer for Apache Hadoop is HDFS.

Hadoop 52

Hadoop Architecture IT Java 52

Knowledge Hut

NOVEMBER 17, 2023

Understanding data modeling concepts like entity-relationship diagrams, data normalization, and data integrity is a requirement for an Azure Data Engineer. You ought to be able to create a data model that is performance- and scalability-optimized. The certification cost is $165 USD.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

DECEMBER 21, 2023

The primary process comprises gathering data from multiple sources, storing it in a database to handle vast quantities of information, cleaning it for further use and presenting it in a comprehensible manner. Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language).

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Big Query Google’s cloud data warehouse. Flat File A type of database that stores data in a plain text format.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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. Key Benefits and Takeaways: Learn the core concepts of big data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

JULY 3, 2023

Use Cases of Real-time Ingestion Real-time ingestion provides organizations with infrastructure for implementing various data capture, data processing and data analyzing tools. Here are some key uses of real-time data ingestion: 1. Like IoT devices, sensors, social media platforms, financial data, etc.

Data Ingestion 52

Data Ingestion Google Cloud Pipeline-centric Media 52

Monte Carlo

OCTOBER 4, 2023

Automate engineering and data processes By automating repetitive or mundane aspects of coding and data engineering, generative AI is streamlining workflows and driving productivity for software and data engineers alike. Tools like Tensorflow and HuggingFace are good options to fine-tune your models.

Unstructured Data 72

Unstructured Data Finance SQL Database 72

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. Amazon S3 for AWS, Azure Blob Storage for Azure, or Google Cloud Storage for GCP) to store the actual data files in micro-partitions.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Knowledge Hut

NOVEMBER 2, 2023

Who is Azure Data Engineer? 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. CSV, SQL Server), transform it, and load it into a target storage (e.g.,

Data Engineering 52

Data Engineering Data Engineer Project Coding 52