Snowflake

MARCH 6, 2025

Large language models (LLMs) are transforming how we extract value from this data by running tasks from categorization to summarization and more. While AI has proved that real-time conversations in natural language are possible with LLMs, extracting insights from millions of unstructured data records using these LLMs can be a game changer.

Unstructured Data 97

Unstructured Data Medical Media Data Workflow 97

Data Engineering Weekly

MARCH 5, 2025

The modern data stack constantly evolves, with new technologies promising to solve age-old problems like scalability, cost, and data silos. It promised to address key pain points: Scaling: Handling ever-increasing data volumes. Speed: Accelerating data insights. Data Silos: Breaking down barriers between data sources.

Hadoop 57

Hadoop Metadata Data Ingestion Data Governance 57

Cloudera

NOVEMBER 15, 2024

In fact, according to the Identity Theft Resource Center (ITRC) Annual Data Breach Report , there were 2,365 cyber attacks in 2023 with more than 300 million victims, and a 72% increase in data breaches since 2021. However, there is a fundamental challenge standing in the way of being successful: data.

Metadata 84

Metadata Unstructured Data Data Lake Government 84

ProjectPro

JUNE 6, 2025

Amazon Web Services (AWS) provides a wide range of tools and services for handling enormous amounts of data. The two most popular AWS data engineering services for processing data at scale for analytics operations are Amazon EMR and AWS Glue. AWS Glue vs. EMR - Pricing The Amazon EMR pricing structure is basic and reasonable.

Big Data 52

Big Data AWS Amazon Web Services Project 52

ProjectPro

JUNE 6, 2025

Data engineering is the foundation for data science and analytics by integrating in-depth knowledge of data technology, reliable data governance and security, and a solid grasp of data processing. Data engineers need to meet various requirements to build data pipelines.

AWS 52

AWS Data Engineering Data Engineer Project 52

ProjectPro

JUNE 6, 2025

This guide is your roadmap to building a data lake from scratch. We'll break down the fundamentals, walk you through the architecture, and share actionable steps to set up a robust and scalable data lake. Traditional data storage systems like data warehouses were designed to handle structured and preprocessed data.

Data Lake 40

Data Lake Building Hadoop Raw Data 40

ProjectPro

JUNE 6, 2025

Data modeling is a crucial skill for every big data professional, but it can be challenging to master. So, if you are preparing for a data modelling interview, you have landed on the right page. We have compiled the top 50 data modelling interview questions and answers from beginner to advanced levels. billion by 2028.

Data Warehouse 53

Data Warehouse NoSQL PostgreSQL Relational Database 53

ProjectPro

JUNE 6, 2025

ETL is a critical component of success for most data engineering teams, and with teams harnessing it with the power of AWS, the stakes are higher than ever. Data Engineers and Data Scientists require efficient methods for managing large databases, which is why centralized data warehouses are in high demand.

AWS 40

AWS Data Management ETL Tools Management 40

ProjectPro

JUNE 6, 2025

With the global data volume projected to surge from 120 zettabytes in 2023 to 181 zettabytes by 2025, PySpark's popularity is soaring as it is an essential tool for efficient large scale data processing and analyzing vast datasets. Resilient Distributed Datasets (RDDs) are the fundamental data structure in Apache Spark.

Hadoop 68

Hadoop Metadata Java Datasets 68

ProjectPro

JUNE 6, 2025

Get ready for your Netflix Data Engineer interview in 2024 with this comprehensive guide. It's your go-to resource for practical tips and a curated list of frequently asked Netflix Data Engineer Interview Questions and Answers. That's where the role of Netflix Data Engineers comes in. petabytes of data. Interested?

Data Engineering 40

Data Engineering Data Engineer Engineering Unstructured Data 40

Teradata

MAY 30, 2025

Register now Home Insights Data platform Article How To Use Airbyte, dbt-teradata, Dagster, and Teradata Vantage™ for Seamless Data Integration Build and orchestrate a data pipeline in Teradata Vantage using Airbyte, Dagster, and dbt. In this case, we select Sample Data (Faker). dbt-core dagster==1.7.9

Data Integration 52

Data Integration Raw Data Metadata Data Pipeline 52

ProjectPro

JUNE 6, 2025

The adaptability and technical superiority of such open-source big data projects make them stand out for community use. As per the surveyors, Big data (35 percent), Cloud computing (39 percent), operating systems (33 percent), and the Internet of Things (31 percent) are all expected to be impacted by open source shortly.

Big Data 49

Big Data Project Metadata Programming Language 49

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 115

Data Lake Data Warehouse Cloud Unstructured Data 115

ProjectPro

JUNE 6, 2025

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake? Is Hadoop a data lake or data warehouse?

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

JUNE 6, 2025

Today, businesses use traditional data warehouses to centralize massive amounts of raw data from business operations. Since data needs to be accessible easily, organizations use Amazon Redshift as it offers seamless integration with business intelligence tools and helps you train and deploy machine learning models using SQL commands.

Data Pipeline 64

Data Pipeline AWS Project Building 64

ProjectPro

JUNE 6, 2025

Big data , Hadoop, Hive —these terms embody the ongoing tech shift in how we handle information. It's not just theory; it's about seeing how this framework actively shapes our data-driven world. These statistics underscore the global significance of Hive as a critical component in the arsenal of big data tools.

Big Data 40

Big Data Architecture Project Hadoop 40

ProjectPro

JUNE 6, 2025

Data is often referred to as the new oil, and just like oil requires refining to become useful fuel, data also needs a similar transformation to unlock its true value. This transformation is where data warehousing tools come into play, acting as the refining process for your data. Why Choose a Data Warehousing Tool?

Data Storage 58

Data Storage PostgreSQL Data Warehouse AWS 58

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Introduction to the Data Mesh Architecture and its Required Capabilities. Components of a Data Mesh.

Architecture 124

Architecture Metadata Kafka Government 124

Cloudyard

DECEMBER 2, 2024

Read Time: 2 Minute, 16 Second Introduction In today’s data-driven world, organizations rely on automated pipelines to handle unstructured and semi-structured data formats like PDFs. Pipeline Overview The pipeline consists of the following components: Stage : Stores PDF files and tracks their metadata using directory tables.

Python 52

Python Process Insurance Metadata 52

ProjectPro

JUNE 6, 2025

Traditional databases are great at handling structured data, like text or numerical values, but they struggle with high-dimensional vector data. It simplifies the process of managing vector data, removing one of the key barriers for AI-powered systems: the need for quick, scalable, and accurate search capabilities.

Database 40

Database Project Metadata Unstructured Data 40

Edureka

MAY 27, 2025

Microsoft Fabric is a next-generation data platform that combines business intelligence, data warehousing, real-time analytics, and data engineering into a single integrated SaaS framework. The architecture of Microsoft Fabric is based on several essential elements that work together to simplify data processes: 1.

Architecture 52

Architecture BI Business Intelligence Raw Data 52

Data Engineering Weekly

JANUARY 12, 2025

With Astro, you can build, run, and observe your data pipelines in one place, ensuring your mission critical data is delivered on time. link] Sponsored: Apache Airflow® Best Practices: Running Airflow at Scale The scalability of Airflow is why data teams at companies like Uber, Ford, and LinkedIn choose it to power their data ops.

Pipeline-centric 57

Pipeline-centric Data Engineering Data Engineer Engineering 57

ProjectPro

JUNE 6, 2025

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market.

Architecture 56

Architecture IT Data Warehouse Amazon Web Services 56

ProjectPro

JUNE 6, 2025

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! “Data analytics is the future, and the future is NOW!

Big Data 40

Big Data Hadoop Relational Database AWS 40

Data Engineering Podcast

JUNE 17, 2021

Summary Working with unstructured data has typically been a motivation for a data lake. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable. No more scripts, just SQL.

Unstructured Data 100

Unstructured Data Data Warehouse Metadata Media 100

ProjectPro

JUNE 6, 2025

This blog post provides an overview of the top 10 data engineering tools for building a robust data architecture to support smooth business operations. Table of Contents What are Data Engineering Tools? Dice Tech Jobs report 2020 indicates Data Engineering is one of the highest in-demand jobs worldwide.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

ProjectPro

JUNE 6, 2025

Are you looking to choose the best cloud data warehouse for your next big data project? This blog presents a detailed comparison of two of the very famous cloud warehouses - Redshift vs. BigQuery - to help you pick the right solution for your data warehousing needs. The global data warehousing market will likely reach $51.18

Data Warehouse 40

Data Warehouse Data Mining Google Cloud PostgreSQL 40

ProjectPro

JUNE 6, 2025

This approach helps bridge the gap between unstructured text generation and structured, factual data. RAG has changed how Large Language Models (LLMs) and natural language processing systems handle large-scale data to retrieve relevant information for question-answering systems.

Building 52

Building Unstructured Data Database Coding 52

ProjectPro

JUNE 6, 2025

Becoming a successful aws data engineer demands you to learn AWS for data engineering and leverage its various services for building efficient business applications. million organizations that want to be data-driven choose AWS as their cloud services partner. Table of Contents Why Learn AWS for Data Engineering?

AWS 40

AWS Data Engineering Data Engineer Engineering 40

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 112

IT Unstructured Data Data Architecture Government 112

Snowflake

JUNE 1, 2025

Fully managed within Snowflakes secure perimeter, these capabilities enable business users and data scientists to turn structured and unstructured data into actionable insights, without complex tooling or infrastructure. Model Context Protocol (MCP) provides an open standard for connecting AI systems with data sources.

Unstructured Data 97

Unstructured Data Google Cloud Government AWS 97

Data Engineering Podcast

FEBRUARY 3, 2019

Summary Archaeologists collect and create a variety of data as part of their research and exploration. Open Context is a platform for cleaning, curating, and sharing this data. I got frustrated at the lack of comparative data, and I got frustrated at all the work I put into creating data that nobody would likely use.

Digital Media 100

Digital Media PostgreSQL Media Google Cloud 100

ProjectPro

JUNE 6, 2025

Are you struggling to adapt data analysis techniques? Look no further than Pandas Functions to streamline your efforts and advance your skills in data manipulation. This blog is a guided tour through the must-know Pandas functions that will empower you to manipulate, transform, and extract insights from your data like never before.

Python 40

Python Datasets Data Analysis Data Science 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. Which Big Data tasks does Spark solve most effectively? How does it work? cost-effectiveness.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JUNE 6, 2025

MongoDB Inc offers an amazing database technology that is utilized mainly for storing data in key-value pairs. It proposes a simple NoSQL model for storing vast data types, including string, geospatial , binary, arrays, etc. This blog enlists 10 MongoDB projects that will help you learn about processing big data in a MongoDB database.

MongoDB 66

MongoDB Coding Project NoSQL 66

Engineering at Meta

MARCH 18, 2024

Users can query using regular expressions on log lines, arbitrary metadata fields attached to logs, and across log files of hosts and services. Logarithm’s data model Logarithm represents logs as a named log stream of (host-local) time-ordered sequences of immutable unstructured text, corresponding to a single log file. in PyTorch).

Engineering 104

Engineering Metadata Architecture Designing 104

Data Engineering Podcast

JULY 1, 2018

Summary Data is often messy or incomplete, requiring human intervention to make sense of it before being usable as input to machine learning projects. With private networking, shared block storage, node balancers, and a 40Gbit network, all controlled by a brand new API you’ve got everything you need to run a bullet-proof data platform.

Metadata 100

Metadata Machine Learning Data Preparation Data Collection 100