ProjectPro

JUNE 6, 2025

But none of them could truly address the core limitations, especially when it came to managing schema changes, handling continuous data ingestion, or supporting concurrent writes without locking. Apache Iceberg Architecture 1. Data Layer What are the main use cases for Apache Iceberg? Workarounds became the norm.

Architecture 40

Architecture Data Lake Metadata Cloud Storage 40

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 102

Architecture Metadata Machine Learning Unstructured Data 102

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. Automatic data backups and replication.

Data Storage 58

Data Storage PostgreSQL Data Warehouse AWS 58

ProjectPro

JUNE 6, 2025

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment. then you are on the right page.

ETL Tools 40

ETL Tools Hadoop Relational Database Unstructured Data 40

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. Let’s understand more about data lakes in the following section. Table of Contents What is a Data Lake?

Data Lake 40

Data Lake Building Hadoop Raw Data 40

Monte Carlo

MAY 28, 2024

A data ingestion architecture is the technical blueprint that ensures that every pulse of your organization’s data ecosystem brings critical information to where it’s needed most. A typical data ingestion flow. Used for identifying and cataloging data sources.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

ProjectPro

JUNE 6, 2025

FAQs on Data Engineering Projects Top 30+ Data Engineering Project Ideas for Beginners with Source Code [2025] We recommend over 20 top data engineering project ideas with an easily understandable architectural workflow covering most industry-required data engineer skills.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

Data Engineering Weekly

MARCH 5, 2025

While the Iceberg itself simplifies some aspects of data management, the surrounding ecosystem introduces new challenges: Small File Problem (Revisited): Like Hadoop, Iceberg can suffer from small file problems. Data ingestion tools often create numerous small files, which can degrade performance during query execution.

Hadoop 57

Hadoop Metadata Data Ingestion Data Governance 57

ProjectPro

JUNE 6, 2025

Here are some of the essential skills for an ETL developer- Data Modeling An ETL developer must be able to read, analyze, and transform data to determine the output formats in a target database. These formats are data models and serve as the foundation for an ETL developer's definition of the tools necessary for data transformation.

Data Engineering 59

Data Engineering Data Engineer Engineering ETL Tools 59

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Data Lake Hadoop 59

Snowflake

JANUARY 26, 2023

requires multiple categories of data, from time series and transactional data to structured and unstructured data. initiatives, such as improving efficiency and reducing downtime by including broader data sets (both internal and external), offers businesses even greater value and precision in the results.

Data Ingestion 52

Data Ingestion Manufacturing Unstructured Data Data 52

ProjectPro

JUNE 6, 2025

These pipelines are the go-to solution for data engineers, and it's no secret why. This blog will help you demystify batch data pipelines, explore the essential tools and architecture, share some best practices, and walk you through building your first batch data pipeline. Table of Contents What Is A Batch Data Pipeline?

Data Pipeline 40

Data Pipeline Building Data Ingestion Retail 40

ProjectPro

JUNE 6, 2025

Learn how to build a Retrieval-Augmented Generation (RAG) pipeline, including its architecture, implementation steps, and tips for optimal performance. It discusses the RAG architecture, outlining key stages like data ingestion , data retrieval, chunking , embedding generation , and querying. from 2024 to 2030.

Building 40

Building Project Metadata Data Ingestion 40

Striim

APRIL 18, 2025

Siloed storage : Critical business data is often locked away in disconnected databases, preventing a unified view. Delayed data ingestion : Batch processing delays insights, making real-time decision-making impossible.

High Quality Data 52

High Quality Data Business Intelligence Unstructured Data Government 52

ProjectPro

JUNE 6, 2025

Explore Data Engineer Projects to Learn the Plumbing of Data Science Role and Responsibilities of a Data Engineer Prepare, handle, and supervise efficient data pipeline architectures. Build and deploy ETL/ELT data pipelines that can begin with data ingestion and complete various data-related tasks.

Data Engineering 58

Data Engineering Data Engineer Engineering Amazon Web Services 58

ProjectPro

JUNE 6, 2025

Let us dive deeper into this data integration solution by AWS and understand how and why big data professionals leverage it in their data engineering projects. The ETL code for your data is automatically generated by AWS Glue when you specify your ETL process in the drag-and-drop job editor. How Does AWS Glue Work?

AWS 66

AWS Scala Metadata Data Lake 66

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? These tools are responsible for making the day-to-day tasks of a data engineer easier in various ways.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

ProjectPro

JUNE 6, 2025

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 40

Big Data Hadoop Relational Database NoSQL 40

ProjectPro

JUNE 6, 2025

Skills Portfolio: A diversified skill set with proficiency in multiple Big Data tools, programming languages, and data manipulation techniques can lead to higher salaries. Developers who can work with structured and unstructured data and use machine learning and data visualization tools are highly sought after.

Big Data 40

Big Data Hadoop Scala NoSQL 40

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Ingestion layer 2.

Architecture 52

Architecture Data Lake Metadata NoSQL 52

ProjectPro

JUNE 6, 2025

ETL developers are also responsible for addressing data inconsistencies and performance tuning to optimize the transfer process, which plays a key role in ensuring accurate and timely access to information. On the other hand, a data engineer has a broader focus that extends beyond the ETL process.

Data Engineering 40

Data Engineering Data Engineer Engineering ETL Tools 40

Cloudera

APRIL 20, 2021

In today’s demand for more business and customer intelligence, companies collect more varieties of data — clickstream logs, geospatial data, social media messages, telemetry, and other mostly unstructured data. What is modern streaming architecture?

Kafka 95

Kafka Hospitality Retail Data Ingestion 95

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Ingestion layer 2.

Architecture 52

Architecture Data Lake Metadata NoSQL 52

Cloudera

FEBRUARY 8, 2021

Future connected vehicles will rely upon a complete data lifecycle approach to implement enterprise-level advanced analytics and machine learning enabling these advanced use cases that will ultimately lead to fully autonomous drive.

Manufacturing 108

Manufacturing Machine Learning Electronics Data Ingestion 108

ProjectPro

JUNE 6, 2025

Zero ETL Components Zero ETL relies on several key components to streamline data integration and make it readily available for analysis without the traditional ETL process. This flexibility allows organizations to integrate data from multiple sources without upfront standardization.

Data Analytics 40

Data Analytics MySQL PostgreSQL Data Lake 40

Cloudera

AUGUST 13, 2021

Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis.

Data Pipeline 111

Data Pipeline Data Lake ETL Tools Unstructured Data 111

Cloudera

FEBRUARY 15, 2024

Seeing the future in a modern data architecture The key to successfully navigating these challenges lies in the adoption of a modern data architecture. The promise of a modern data architecture might seem like a distant reality, but we at Cloudera believe data can make what is impossible today, possible tomorrow.

Insurance 88

Insurance Banking Data Architecture Data Ingestion 88

ProjectPro

JUNE 6, 2025

It covers Snowflake architecture , SQL essentials, data loading, data security, and basic administration. Snowflake SnowPro Advanced: Architect Certification Image Source: learn.snowflake.com/ This certification validates proficiency in implementing comprehensive architectural solutions using Snowflake.

Certification 40

Certification Data Pipeline Hadoop Data Architect 40

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Benjamin Kennedy, Cloud Solutions Architect at Striim, emphasizes the outcome-driven nature of data pipelines.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

ProjectPro

JUNE 6, 2025

This blog is a one-stop solution to overcome these challenges that covers everything from a data pipeline architecture to the ultimate process of building a data pipeline from scratch with practical examples - So, let’s get started! Table of Contents What is a Data Science Pipeline?

Data Science 40

Data Science Building Data Lake AWS 40

Data Engineering Weekly

SEPTEMBER 18, 2024

Decoupling of Storage and Compute : Data lakes allow observability tools to run alongside core data pipelines without competing for resources by separating storage from compute resources. This opens up new possibilities for monitoring and diagnosing data issues across various sources.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Data 98

ProjectPro

JUNE 6, 2025

Let us compare traditional data warehousing and Hadoop-based BI solutions to better understand how using BI on Hadoop proves more effective than traditional data warehousing- Point Of Comparison Traditional Data Warehousing BI On Hadoop Solutions Data Storage Structured data in relational databases.

BI 40

BI Hadoop Big Data Business Intelligence 40

AltexSoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Data warehouse vs. data lake in a nutshell.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Snowflake

NOVEMBER 29, 2023

However, new technological approaches have unleashed the ability to scale data processing and computing in a secure, seamless and reliable manner, and move compute closer to the data. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 117

Metadata Healthcare Medical Data Storage 117

Zalando Engineering

JUNE 26, 2017

The immense explosion of unstructured data drives modern search applications to go beyond just fuzzy string matching, to invest in deep understanding of user queries through interpretation of user intention in order to respond with a relevant result set.

Architecture 40

Architecture Unstructured Data Machine Learning Data Ingestion 40

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka Data Lake 52