Striim

SEPTEMBER 11, 2024

Data Collection/Ingestion The next component in the data pipeline is the ingestion layer, which is responsible for collecting and bringing data into the pipeline. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

APRIL 23, 2024

Big Data In contrast, big data encompasses the vast amounts of both structured and unstructured data that organizations generate on a daily basis. It encompasses data from diverse sources such as social media, sensors, logs, and multimedia content.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses.

Data Management 52

Data Management Management Data Lake Data Governance 52

DareData

JANUARY 30, 2023

Our goal is to help data scientists better manage their models deployments or work more effectively with their data engineering counterparts, ensuring their models are deployed and maintained in a robust and reliable way. AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS).

Data Engineer 52

Data Engineer Data Engineering NoSQL Engineering 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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 105

Engineering Raw Data Data Science Machine Learning 105

RandomTrees

SEPTEMBER 27, 2024

This eliminates the need to make multiple copies of data assets. Unified data platform: One Lake provides a unified platform for all data types, including structured, semi-structured, and unstructured data.

Database-centric 52

Database-centric Pipeline-centric IT BI 52

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? To make things a little easier, I’ve outlined the six must-have layers you need to include in your data platform and the order in which many of the best teams choose to implement them. The five must-have layers of a modern data platform Second to “how do I build my data platform?”,

Building 52

Building BI Data Lake Data Governance 52

Precisely

MAY 13, 2024

A true enterprise-grade integration solution calls for source and target connectors that can accommodate: VSAM files COBOL copybooks open standards like JSON modern platforms like Amazon Web Services ( AWS ), Confluent , Databricks , or Snowflake Questions to ask each vendor: Which enterprise data sources and targets do you support?

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Sync Computing

NOVEMBER 7, 2024

Despite these limitations, data warehouses, introduced in the late 1980s based on ideas developed even earlier, remain in widespread use today for certain business intelligence and data analysis applications. While data warehouses are still in use, they are limited in use-cases as they only support structured data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

Edureka

FEBRUARY 9, 2023

As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical. Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. It is also crucial to have experience with data ingestion and transformation.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? Amazon S3 – An object storage service for structured and unstructured data, S3 gives you the compute resources to build a data lake from scratch. Singer – An open source tool for moving data from a source to a destination.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

AltexSoft

AUGUST 29, 2023

Unstructured data sources. This category includes a diverse range of data types that do not have a predefined structure. Examples of unstructured data can range from sensor data in the industrial Internet of Things (IoT) applications, videos and audio streams, images, and social media content like tweets or Facebook posts.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

APRIL 23, 2024

Example of Data Variety An instance of data variety within the four Vs of big data is exemplified by customer data in the retail industry. Customer data come in numerous formats. It can be structured data from customer profiles, transaction records, or purchase history.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Knowledge Hut

MARCH 28, 2024

Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance. Develop data models, data governance policies, and data integration strategies. GDPR, HIPAA), and industry standards.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

AltexSoft

MARCH 30, 2023

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Besides that, it’s fully compatible with various data ingestion and ETL tools. Let’s see what exactly Databricks has to offer.

Scala 64

Scala Data Lake Machine Learning BI 64

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

Monte Carlo

APRIL 24, 2023

We continuously hear data professionals describe the advantage of the Snowflake platform as “it just works.” Snowpipe and other features makes Snowflake’s inclusion in this top data lake vendors list a no-brainer. Not to mention seamless integration with the Oracle ecosystem.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

DareData

JULY 5, 2023

We've seen this happen in dozens of our customers: data lakes serve as catalysts that empower analytical capabilities. If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. And what is the reason for that?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

phData: Data Engineering

JANUARY 3, 2022

This means it’s business-critical that companies can derive value from their data to better inform business decisions, protect their enterprise and their customers, and grow their business. This comprehensive guide will cover all of the basics of data engineering including common roles, functions, and responsibilities.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Governance 52

Edureka

FEBRUARY 7, 2023

They should also be comfortable working with a variety of data sources and types and be able to design and implement data pipelines that can handle structured, semi-structured, and unstructured data.

Data Engineer 52

Data Engineer Data Engineering Engineering Programming Language 52

ProjectPro

FEBRUARY 21, 2023

Microsoft introduced the Data Engineering on Microsoft Azure DP 203 certification exam in June 2021 to replace the earlier two exams. This professional certificate demonstrates one's abilities to integrate, analyze, and transform various structured and unstructured data for creating effective data analytics solutions.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

AltexSoft

JULY 29, 2022

To facilitate data ingestion, there are Apache Flume aggregating log data from multiple servers and Apache Sqoop designed to transport information between Hadoop and relational (SQL) databases. In September 2021 Snowflake announced the public preview of the unstructured data management functionality.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Data Engineering Weekly

DECEMBER 18, 2024

DEW published The State of Data Engineering in 2024: Key Insights and Trends , highlighting the key advancements in the data space in 2024. We witnessed the explosive growth of Generative AI, the maturing of data governance practices, and a renewed focus on efficiency and real-time processing. But what does 2025 hold?

Data Engineer 113

Data Engineer Data Engineering Engineering Data Lake 113

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 Engineer 52

Data Engineer Data Engineering Engineering Data Ingestion 52

RandomTrees

MAY 6, 2025

Efficient data pipelines are necessary for AI systems to perform well since AI models need clean and organized as well as fresh datasets in order to learn and predict accurately. Au tomation in modern data engineering has a new dimension. It ensures a seamless flow of data within the pipelines with minimum human contact.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Cleanse 52