Christophe Blefari

FEBRUARY 23, 2024

JVM vs. SQL data engineer — There's a big discussion in the community about what real data engineering is. Is it DataFrames or SQL? Is it lake or warehouse? It's a sterile debate: both are useful and can serve different organisations with different service level for data users and stakeholders.

Data Lake 130

Data Lake PostgreSQL MongoDB Scala 130

Data Engineering Podcast

OCTOBER 28, 2021

He also explains why he started Decodable to address that limitation and the work that he and his team have done to let data engineers build streaming pipelines entirely in SQL. Start trusting your data with Monte Carlo today! The data you’re looking for is already in your data warehouse and BI tools.

Data Pipeline 100

Data Pipeline SQL Data Warehouse Data Lake 100

Data Engineering Podcast

NOVEMBER 11, 2018

Summary A data lake can be a highly valuable resource, as long as it is well built and well managed. In this episode Yoni Iny, CTO of Upsolver, discusses the various components that are necessary for a successful data lake project, how the Upsolver platform is architected, and how modern data lakes can benefit your organization.

Data Lake 100

Data Lake Building Kafka Cloud 100

Hevo

MAY 17, 2024

Snowflake Data Warehouse delivers essential infrastructure for handling a Data Lake, and Data Warehouse needs. It can store semi-structured and structured data in one place due to its multi-clusters architecture that allows users to independently query data using SQL.

Data Warehouse 52

Data Warehouse Data Lake Structured Data SQL 52

KDnuggets

JANUARY 18, 2023

7 Best Platforms to Practice SQL • Explainable AI: 10 Python Libraries for Demystifying Your Model's Decisions • ChatGPT: Everything You Need to Know • Data Lakes and SQL: A Match Made in Data Heaven • Google Data Analytics Certification Review for 2023

SQL 85

SQL Python Data Lake Certification 85

Data Engineering Podcast

SEPTEMBER 7, 2020

In this episode he explains how it is designed to allow for querying and combining data where it resides, the use cases that such an architecture unlocks, and the innovative ways that it is being employed at companies across the world. What are the tradeoffs of using Presto on top of a data lake vs a vertically integrated warehouse solution?

Architecture 100

Architecture Data Architecture SQL Engineering 100

Christophe Blefari

FEBRUARY 2, 2024

Fivetran uses DuckDB as the tech to do file merge in the data lake offering Datacamp uses DuckDB to be able in notebooks to query dataframes in SQL and consider it for teaching SQL — I might have something in the making about this on my side. Lastly they pre-compute statistics on datasets with DuckDB.

Datasets 130

Datasets Data Lake SQL Algorithm 130

Cloudera

NOVEMBER 10, 2020

Two of the more painful things in your everyday life as an analyst or SQL worker are not getting easy access to data when you need it, or not having easy to use, useful tools available to you that don’t get in your way! This simple statement captures the essence of almost 10 years of SQL development with modern data warehousing.

SQL 110

SQL Unstructured Data Data Lake Hadoop 110

Hevo

APRIL 12, 2024

ETL processes often involve aggregating data from various sources into a data warehouse or data lake. Bucketing can be used during the transformation phase to aggregate data into predefined buckets or intervals. It plays a […]

Aggregated Data 40

Aggregated Data SQL Data Lake Data Warehouse 40

Seattle Data Guy

FEBRUARY 10, 2024

Photo by Tiger Lily Data warehouses and data lakes play a crucial role for many businesses. It gives businesses access to the data from all of their various systems. As well as often integrating data so that end-users can answer business critical questions.

Data Lake 162

Data Lake Data Warehouse Data Accessible 162

Data Engineering Podcast

MAY 22, 2022

Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. Stop struggling to speed up your data lake.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Cloud 130

Towards Data Science

MAY 3, 2023

One such tool is the Versatile Data Kit (VDK), which offers a comprehensive solution for controlling your data versioning needs. VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python. Use VDK to build a data lake and merge multiple sources.

Data Lake 87

Data Lake Data SQL Data Warehouse 87

Data Engineering Podcast

DECEMBER 4, 2022

Datafold built automated regression testing to help data and analytics engineers deal with data quality in their pull requests. Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production. Pricing for SQLake is simple.

Data Lake 100

Data Lake MongoDB MySQL Data Warehouse 100

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.

SQL 52

SQL Kafka MongoDB MySQL 52

Christophe Blefari

JANUARY 20, 2024

The Rise of the Data Engineer The Downfall of the Data Engineer Functional Data Engineering — a modern paradigm for batch data processing There is a global consensus stating that you need to master a programming language (Python or Java based) and SQL in order to be self-sufficient.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

ProjectPro

FEBRUARY 16, 2023

At the heart of these data engineering skills lies SQL that helps data engineers manage and manipulate large amounts of data. Did you know SQL is the top skill listed in 73.4% of data engineer job postings on Indeed? Almost all major tech organizations use SQL. use SQL, compared to 61.7%

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes. Iterations of the lakehouse.

Data Lake 92

Data Lake Data Warehouse BI SQL 92

Data Engineering Podcast

DECEMBER 11, 2022

Datafold built automated regression testing to help data and analytics engineers deal with data quality in their pull requests. Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production. Pricing for SQLake is simple.

Database 100

Database MySQL Data Lake MongoDB 100

Knowledge Hut

MARCH 28, 2024

Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB. Education & Skills Required Proficiency in SQL, Python, or other programming languages. Develop predictive models and data-driven solutions to address business challenges.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Data Engineering Podcast

AUGUST 20, 2021

Summary Data lakes have been gaining popularity alongside an increase in their sophistication and usability. Despite improvements in performance and data architecture they still require significant knowledge and experience to deploy and manage. The data you’re looking for is already in your data warehouse and BI tools.

Building 100

Building Data Lake Data Warehouse SQL 100

Data Engineering Podcast

OCTOBER 16, 2022

Summary The "data lakehouse" architecture balances the scalability and flexibility of data lakes with the ease of use and transaction support of data warehouses. Mention the podcast to get a free "In Data We Trust World Tour" t-shirt. How has that history influenced the capabilities (e.g.

Data Lake 100

Data Lake Food MongoDB Scala 100

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

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Data Engineering Weekly

MAY 12, 2024

[link] Gradient Flow: Learning from the Past - Comparing the Hype Cycles of Big Data and GenAI The blogs compare the hype cycle of Big Data with Gen AI. The blog narrates the initial hype of Big Data, followed by talent shortages and lead time to build production applications.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Rockset

JULY 6, 2022

Typically stored in SQL statements, the schema also defines all the tables in the database and their relationship to each other. Companies carefully engineered their ETL data pipelines to align with their schemas (not vice-versa). SQL queries were easier to write. They also ran a lot faster. There were heavy tradeoffs, though.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Monte Carlo

DECEMBER 4, 2023

So, don’t forget to review your ChatGPT outputs before leverage scripts or pushing any SQL code to production. Extraction ChatGPT ETL prompts can be used to help write scripts to extract data from different sources, including: Databases I have a SQL database with a table named employees.

PostgreSQL 52

PostgreSQL Data Lake ETL Tools MySQL 52

Data Engineering Podcast

JANUARY 28, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.

Data Lake 147

Data Lake Building High Quality Data AWS 147

Knowledge Hut

SEPTEMBER 25, 2023

Skill Requirements for Azure Data Engineer Job Description Here are some important skill requirements that you may find in a job description for Azure Data Engineers: 1. Azure Data Engineers work with these and other solutions. They guarantee that the data is efficiently cleaned, converted, and loaded.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

NOVEMBER 17, 2023

To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. Here is a step-by-step guide on how to become an Azure Data Engineer: 1. You should possess a strong understanding of data structures and algorithms.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Data Engineering Podcast

NOVEMBER 6, 2022

RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control.

MongoDB 130

MongoDB Scala MySQL Data Lake 130

Data Engineering Podcast

JANUARY 13, 2019

Links TimescaleDB Original Appearance on the Data Engineering Podcast 1.0 Links TimescaleDB Original Appearance on the Data Engineering Podcast 1.0

Database 100

Database PostgreSQL SQL MongoDB 100

Monte Carlo

DECEMBER 29, 2022

Data Observability: How to Build Your Own Data Anomaly Detectors Using SQL The same author, Monte Carlo data scientist Ryan Kearns, dives into how to build machine learning driven data anomaly detectors using SQL. In fact, our original prototype only covered about 80% of possible combinations!

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Data Engineering Podcast

FEBRUARY 4, 2024

Summary Stream processing systems have long been built with a code-first design, adding SQL as a layer on top of the existing framework. In this episode Yingjun Wu explains how it is architected to power analytical workflows on continuous data flows, and the challenges of making it responsive and scalable. Starburst : ![Starburst

SQL 173

SQL Data Lake High Quality Data Data Pipeline 173

François Nguyen

MARCH 22, 2021

With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services. The data domain Discovery portal with all the metadata on the data life cycle 4.Federated The number of subjects to automatize is not short.

Architecture 130

Architecture Technology Google Cloud Metadata 130

Knowledge Hut

NOVEMBER 2, 2023

Azure Data Ingestion Pipeline Create an Azure Data Factory data ingestion pipeline to extract data from a source (e.g., CSV, SQL Server), transform it, and load it into a target storage (e.g., Azure SQL Database, Azure Data Lake Storage). A strong understanding of data sourcing with SQL.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Snowflake

DECEMBER 4, 2023

With this public preview, those external catalog options are either “GLUE”, where Snowflake can retrieve table metadata snapshots from AWS Glue Data Catalog, or “OBJECT_STORE”, where Snowflake retrieves metadata snapshots directly from the specified cloud storage location. With these three options, which one should you use?

Building 96

Building Metadata Cloud Storage AWS 96