Monte Carlo

FEBRUARY 8, 2024

You do that by leveraging the flexibility and scalability of your cloud environment. Here’s how to get the most bang for your buck: Use Cloud spot instances : Identify non-critical, interruptible tasks in your pipeline, such as batch processing or data analytics.

Data Pipeline 52

Data Pipeline AWS Datasets Data 52

Data Engineering Podcast

JULY 3, 2022

In order to quickly identify if and how two data systems are out of sync Gleb Mezhanskiy and Simon Eskildsen partnered to create the open source data-diff utility. report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. In fact, while only 3.5%

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Data Engineering Podcast

JANUARY 30, 2022

Today’s episode is Sponsored by Prophecy.io – the low-code data engineering platform for the cloud. Prophecy provides an easy-to-use visual interface to design & deploy data pipelines on Apache Spark & Apache Airflow. The only thing worse than having bad data is not knowing that you have it.

Data Engineering 100

Data Engineering Data Engineer Engineering Data Pipeline 100

Knowledge Hut

SEPTEMBER 25, 2023

Microsoft Azure is a cloud computing platform that gives businesses fantastic services. This demonstrates how in-demand Microsoft Certified Data Engineers are becoming. They are moving their servers and on-premises data to Azure Cloud. What does all of this mean for Data Engineering professionals?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Data Engineering Weekly

DECEMBER 25, 2023

The Rising Impact of AI and Large Language Models 2023 witnessed a substantial impact of AI and large language models in data engineering. These technologies are increasingly automating processes like ETL, improving data quality management, and evolving the landscape of data tools.

Data Engineering 52

Data Engineering Data Engineer Engineering Unstructured Data 52

Data Engineering Weekly

DECEMBER 29, 2022

Data catalogs are the most expensive data integration systems you never intended to build. Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. How happy are you with your data catalogs?

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Knowledge Hut

MARCH 28, 2024

Azure Data Engineer Career Demands & Benefits Azure has become one of the most powerful platforms in the industry, where Microsoft offers a variety of data services and analytics tools. As a result, organizations are looking to capitalize on cloud-based data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Data Engineering Podcast

OCTOBER 19, 2020

Are you bogged down by having to manually manage data access controls, repeatedly move and copy data, and create audit reports to prove compliance? How much time could you save if those tasks were automated across your cloud platforms? Interview Introduction How did you get involved in the area of data management?

Machine Learning 100

Machine Learning Data Engineering Data Engineer Data 100

Data Engineering Podcast

JULY 17, 2022

Shipyard]([link] Shipyard is an orchestration platform that helps data teams build out solid data operations from the get-go by connecting data tools and streamlining data workflows.

Data Management 130

Data Management Management Metadata MongoDB 130

Cloudera

SEPTEMBER 21, 2021

Many customers looking at modernizing their pipeline orchestration have turned to Apache Airflow, a flexible and scalable workflow manager for data engineers. A provider could be used to make HTTP requests, connect to a RDBMS, check file systems (such as S3 object storage), invoke cloud provider services, and much more.

Python 97

Python Cloud Data Workflow Accessible 97

Workfall

JULY 18, 2023

Additionally, they offer a way to keep your transformed data up to date without redoing the entire transformation process. By using DBT materializations, you can streamline your data workflows and focus on gaining insights rather than spending excessive time on repetitive calculations.

Datasets 77

Datasets Entertainment Data Workflow Data 77

Knowledge Hut

NOVEMBER 17, 2023

Integrating and transforming data: Azure Data Engineers are experts at building and managing data pipelines, combining data from several sources, and converting it into formats suitable for analysis and reporting. Azure Data Factory stands at the forefront, orchestrating data workflows.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

DataKitchen

MAY 10, 2024

Development : Observability in development includes conducting regression tests and impact assessments when new code, tools, or configurations are introduced, helping maintain system integrity as new code of data sets are introduced into production.

Raw Data 40

Raw Data Data Ingestion Datasets Data 40

Knowledge Hut

DECEMBER 28, 2023

Human society in 2023 is a digital world, and its fuel - its currency - is data. Today, organizations seek skilled professionals who can harness data’s power to drive informed decisions. As technology evolves, cloud platforms have emerged as the cornerstone of modern data management.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ThoughtSpot

SEPTEMBER 6, 2023

The pathway from ETL to actionable analytics can often feel disconnected and cumbersome, leading to frustration for data teams and long wait times for business users. And even when we manage to streamline the data workflow, those insights aren’t always accessible to users unfamiliar with antiquated business intelligence tools.

Data Workflow 91

Data Workflow Raw Data Data Lake Business Intelligence 91

Data Engineering Podcast

JANUARY 1, 2022

One of the ways to reason about progress in any domain is to look at what was the primary bottleneck of further progress (data adoption for decision making) at different points in time. Over the past couple of months, we’ve seen the resurgence of “benchmark wars” between major data warehousing platforms.

Data Warehouse 100

Data Warehouse Data Lake SQL Hadoop 100

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.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Data Engineering Podcast

SEPTEMBER 4, 2022

report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. In fact, while only 3.5% That’s where our friends at Ascend.io

MongoDB 100

MongoDB Scala MySQL Data Ingestion 100

Ascend.io

DECEMBER 19, 2023

You’re extracting and loading data first, then transforming it in Snowflake’s cloud data warehouse. However, there is a critical aspect to consider: using Snowflake’s native features to build data pipelines is akin to constructing a bespoke data platform. And it doesn’t end there.

ETL Tools 52

ETL Tools IT Data Pipeline Data Warehouse 52

Data Engineering Podcast

MAY 3, 2021

Summary The Data industry is changing rapidly, and one of the most active areas of growth is automation of data workflows. Taking cues from the DevOps movement of the past decade data professionals are orienting around the concept of DataOps.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Podcast

APRIL 5, 2021

It builds your customer data warehouse and your identity graph on your data warehouse, with support for Snowflake, Google BigQuery, Amazon Redshift, and more. Their SDKs and plugins make event streaming easy, and their integrations with cloud applications like Salesforce and ZenDesk help you go beyond event streaming.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Knowledge Hut

SEPTEMBER 29, 2023

Why Should You Get an Azure Data Engineer Certification? Becoming an Azure data engineer allows you to seamlessly blend the roles of a data analyst and a data scientist. One of the pivotal responsibilities is managing data workflows and pipelines, a core aspect of a data engineer's role.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Data Engineering Weekly

OCTOBER 30, 2022

Editor’s Note: The current state of the Data Catalog The results are out for our poll on the current state of the Data Catalogs. The highlights are that 59% of folks think data catalogs are sometimes helpful. We saw in the Data Catalog poll how far it has to go to be helpful and active within a data workflow.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Cloudera

AUGUST 21, 2020

One is data at rest, for example in a data lake, warehouse, or cloud storage and from there they can do analytics on this data and that is predominantly around what has already happened or around how to prevent something from happening in the future.

Banking 61

Banking Kafka Cloud Storage Government 61

Workfall

JULY 4, 2023

Reading Time: 8 minutes In the world of data engineering, a mighty tool called DBT (Data Build Tool) comes to the rescue of modern data workflows. Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights.

Data Warehouse 69

Data Warehouse SQL PostgreSQL Database 69

Data Engineering Podcast

APRIL 14, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is brought to you by Datafold – a testing automation platform for data engineers that prevents data quality issues from entering every part of your data workflow, from migration to dbt deployment.

Non-relational Database 147

Non-relational Database Relational Database Database Designing 147

DataKitchen

DECEMBER 20, 2020

A DataOps Engineer who understands how to automate and streamline data workflows can increase a data team’s productivity by orders of magnitude. A person like that is worth their weight in gold. The role of the DataOps Engineer goes by several different titles and is sometimes covered by IT, dev, or analyst functions.

Engineering 59

Engineering Manufacturing Data Analytics Data Workflow 59

Monte Carlo

JULY 27, 2023

The skills, languages and tools of a data quality engineer Data quality engineers need to be highly skilled in multiple programming languages such as SQL (mentioned in 61% of postings), Python (56%), and Scala (13%). 78% of job postings referenced at least part of their environment was in a modern data warehouse, lake, or lakehouse.

Engineering 52

Engineering Healthcare Scala Data Warehouse 52

DareData

NOVEMBER 28, 2023

And all of these recordings can be saved either on the local machine, in a database locally or even in a server or cloud service, where one can then regulate and control access. This latter possibility allows for collaboration and knowledge sharing within Data Science teams.

Data Science 52

Data Science Medical Machine Learning Data 52

Hepta Analytics

FEBRUARY 14, 2022

Disadvantages of a data lake are: Can easily become a data swamp data has no versioning Same data with incompatible schemas is a problem without versioning Has no metadata associated It is difficult to join the data Data warehouse stores processed data, mostly structured data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Cloudera

FEBRUARY 11, 2019

Disruption slows as cloud and nonrelational technology take their place beside traditional approaches , the leaders extend their lead, and distributed data approaches solidify their place as a best practice for DMSA.” Cloudera believes disruption persists around multi-cloud. Why multi-cloud?

Data Management 43

Data Management Management Metadata Government 43

Data Engineering Podcast

MARCH 31, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Dagster offers a new approach to building and running data platforms and data pipelines. Your first 30 days are free!

Project 130

Project Data Lake High Quality Data Data Workflow 130

Workfall

JUNE 12, 2023

Source: Records in the final table after updating and inserting new rows: We can also create data workflows in the form of data pipelines using apache airflow to know more, you can check our blog at Easily Build ETL Pipeline Using Python And Airflow Conclusion In this blog, we demonstrated implementing a CDC workflow.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Data Engineering Podcast

FEBRUARY 18, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. Data lakes are notoriously complex. Data lakes are notoriously complex. Your first 30 days are free!

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Monte Carlo

SEPTEMBER 20, 2022

Here’s how Prefect , Series B startup and creator of the popular data orchestration tool, harnessed the power of data observability to preserve headcount, improve data quality and reduce time to detection and resolution for data incidents. This left Dylan’s team with a gap to fill.

Big Data 52

Big Data Data Warehouse Data Data Governance 52

Data Engineering Podcast

APRIL 21, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. Data lakes are notoriously complex. Data lakes are notoriously complex. Your first 30 days are free!

Data Lake 182

Data Lake High Quality Data Data Pipeline Machine Learning 182

Data Engineering Podcast

MARCH 17, 2024

Summary A significant portion of data workflows involve storing and processing information in database engines. In this episode Gleb Mezhanskiy, founder and CEO of Datafold, discusses the different error conditions and solutions that you need to know about to ensure the accuracy of your data. Data lakes are notoriously complex.

Database 147

Database Data Lake High Quality Data Data Workflow 147