Data Engineering Podcast

JUNE 19, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Metadata 130

Metadata Unstructured Data MongoDB MySQL 130

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Big Data Large volumes of structured or unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Knowledge Hut

JUNE 20, 2023

Let's find out the differences between a data scientist and a machine learning engineer below to make an informative decision. Data Engineer vs Machine Learning Engineer While there are similarities between a data engineer and a machine learning engineer, both play a key role in the technological world.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Monte Carlo

JANUARY 5, 2024

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. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

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. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Data Engineering Podcast

JUNE 12, 2022

In this episode she shares her thoughts and insights on how to be intentional about establishing your own data team. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Unstruk is the DataOps platform for your unstructured data.

Metadata 100

Metadata Unstructured Data Business Intelligence MongoDB 100

Data Engineering Podcast

JULY 31, 2022

Summary Data lineage is the roadmap for your data platform, providing visibility into all of the dependencies for any report, machine learning model, or data warehouse table that you are working with. Data lineage and metadata systems are a hot topic right now. What are the core problems that Manta aims to solve?

IT 100

IT Metadata MongoDB MySQL 100

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Snowflake

APRIL 5, 2023

Two different data modeling approaches—dimensional data modeling and Data Vault—each have their own pros and cons. Modernizing a data warehouse with Snowflake Data Cloud is a smart investment that can provide significant benefits to businesses of all sizes, today more than ever as data models become ever more complex.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

JUNE 9, 2021

This blog on Data Science vs. Data Engineering presents a detailed comparison between the two domains. vs. What does a Data Engineer do? Are you a Data Scientist or a Data Engineer? Is data engineering more important than data science?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

APRIL 24, 2023

By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases. See our post: Data Lakes vs. Data Warehouses.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Towards Data Science

MAY 3, 2023

Data Engineering Learn about slow change dimensions (SCD) and how to implement SCD Type 2 in VDK Photo by Joshua Sortino on Unsplash Data is the backbone of any organization, and in today’s fast-paced world, it is crucial to keep track of its versions. They store and manage current and historical data in a data warehouse.

Data Lake 80

Data Lake Data SQL Data Warehouse 80

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. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

AltexSoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. Bad data management be like, Source: Makeameme Data architects are sometimes confused with other roles inside the data science team. Feel free to enjoy it.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Monte Carlo

AUGUST 31, 2023

Understanding the “rise of data downtime” With a greater focus on monetizing data coupled with the ever present desire to increase data accuracy, we need to better understand some of the factors that can lead to data downtime. We’ll take a closer look at variables that can impact your data next.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

DECEMBER 29, 2023

There are many data science fields in which experts may contribute to the success of a business, and you can hone the abilities you need by specializing in data science subfields. Data Engineering and Warehousing The data is the lifeblood of every successful Data Science endeavor.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Monte Carlo

JUNE 28, 2022

By design, data was less structured with limited metadata and no ACID properties. As a result, data observability has become particularly important for data lake environments as they often hold large amounts of unstructured data, making data quality issues challenging to detect, resolve, and prevent.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Knowledge Hut

DECEMBER 26, 2023

Data Science is a combination of several disciplines including Mathematics and Statistics, Data Analysis, Machine Learning, and Computer Science. Data Science is a huge umbrella with a plethora of roles available in the field such as a Data Scientist, Data Engineer, BI Developer, Data and Analytics Manager, etc.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Databand.ai

JULY 19, 2023

Learn more in our detailed guide to data lineage visualization (coming soon) Integration with Multiple Data Sources Data lineage tools are designed to integrate with a wide range of data sources, including databases, data warehouses, and cloud-based data platforms.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

ProjectPro

FEBRUARY 16, 2023

Input Data Structured data from various sources, such as databases, spreadsheets, and ERP systems. Structured, semi-structured, and unstructured data from multiple sources, such as social media, IoT devices, and sensors. Tools OLAP, data visualization, reporting, and dashboards.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

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

SEPTEMBER 9, 2021

Explore SQL Database Projects to Add them to Your Data Engineer Resume. Hive , for instance, does not support sub-queries and unstructured data. Data update and deletion operations are also not possible with Hive. Spark SQL supports real-time online transaction processing along with row-level updates.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is Data Science? What are the roles and responsibilities of a Data Engineer? And many more. And many more.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

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. Customers that require a hybrid of these to support many different tools and languages have built a data lakehouse.

Data Lake 90

Data Lake Data Warehouse Cloud Unstructured Data 90

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. Contents: What is the role of an Azure Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Warehouse? .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

ProjectPro

AUGUST 11, 2021

“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?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

DareData

JANUARY 30, 2023

Learn the most important data engineering concepts that data scientists should be aware of. As the field of data science and machine learning continues to evolve, it is increasingly evident that data engineering cannot be separated from it. DigDag: An open-source orchestrator for data engineering workflows.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Data Engineering Podcast

JUNE 26, 2022

In this episode Isaac Brodsky explains how the Unfolded platform is architected, their experience joining the team at Foursquare, and how you can start using it for analyzing your spatial data today. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.

Datasets 130

Datasets Unstructured Data Metadata MongoDB 130

Edureka

FEBRUARY 9, 2023

The role of Azure Data Engineer is in high demand in the field of data management and analytics. As an Azure Data Engineer, you will be in charge of designing, building, deploying, and maintaining data-driven solutions that meet your organization’s business needs. Who is an Azure Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JANUARY 19, 2022

Planning to land a successful job as an Azure Data Engineer? Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Meltano

OCTOBER 5, 2022

Interested in becoming a data engineer? The need for data experts in the U.S. job market is expected to grow by 22% in this decade, and according to LinkedIn’s 2020 report , a data engineer is listed as the 8th fastest growing job today. But what is data engineering exactly and what does a data engineer do?

Data Engineering 52

Data Engineering Data Engineer Engineering Raw Data 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52