Netflix Tech

NOVEMBER 14, 2023

Now, let’s explore the state of our pipelines after incorporating Psyberg. Pipelines After Psyberg Let’s explore how different modes of Psyberg could help with a multistep data pipeline. This is compatible with both Python and Scala Spark. This data pipeline monitors the various stages in the customer lifecycle.

Metadata 97

Metadata Data Pipeline Scala Data Workflow 97

ThoughtSpot

JANUARY 23, 2024

If you’re new to Snowpark, this is Snowflake ’s set of libraries and runtimes that securely deploy and process non-SQL code including Python, Java, and Scala. Build interactive, AI-powered data apps: Product leaders can use ThoughtSpot Everywhere and Snowpark to drive richer, search-driven embedded analytics experiences for all users.

Scala 84

Scala Programming Language Java Python 84

Airbnb Tech

SEPTEMBER 24, 2019

Scaling a Mature Data Pipeline — Managing Overhead There is often a hidden performance cost tied to the complexity of data pipelines — the overhead. In this post, we will introduce its concept, and examine the techniques we use to avoid it in our data pipelines.

Data Pipeline 52

Data Pipeline Management Data Scala 52

Data Engineering Weekly

MARCH 31, 2024

[link] Databricks: PySpark in 2023 - A Year in Review Can we safely say PySpark killed Scala-based data pipelines? I’m looking forward to playing around with Testing API and Arrow-optimized UDF since UDF is the only reason I write Scala nowadays.

Data Engineering 62

Data Engineering Data Engineer Engineering Scala 62

Ascend.io

SEPTEMBER 5, 2023

Snowpark is a library equipped with an API that developers can use for querying and processing data within the Snowflake Data Cloud. In its early days, Snowflake operated as a pure SQL-based engine, requiring external data extraction for processing in other languages.

IT 59

IT Scala Java Programming Language 59

Knowledge Hut

MAY 3, 2024

7 Kafka stores data in Topic i.e., in a buffer memory. Spark uses RDD to store data in a distributed manner (i.e., cache, local space) 8 It supports multiple languages such as Java, Scala, R, and Python. RDDs can include any kind of Python, Java, or Scala object, including classes that the user has specified.

Kafka 98

Kafka Scala Java Amazon Web Services 98

Snowflake

OCTOBER 30, 2023

Enter the new Event Tables feature, which helps developers and data engineers easily instrument their code to capture and analyze logs and traces for all languages: Java, Scala, JavaScript, Python and Snowflake Scripting. But previously, developers didn’t have a centralized, straightforward way to capture application logs and traces.

Java 94

Java Scala Hadoop Data Ingestion 94

Knowledge Hut

DECEMBER 26, 2023

Some of the best books that will guide you in Scala are:- Scala Cookbook: Recipes for Object-Oriented and Functional Programming (Author: Alvin Alexander) Scala for the Impatient (Author: Cay S. Horstmann) Programming Scala: Scalability = Functional Programming + Objects (Author: Alex Payne and Dean Wampler) 2.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

Cloudera

JULY 13, 2021

After the launch of CDP Data Engineering (CDE) on AWS a few months ago, we are thrilled to announce that CDE, the only cloud-native service purpose built for enterprise data engineers, is now available on Microsoft Azure. . CDP data lifecycle integration and SDX security and governance. Key features of CDP Data Engineering.

Data Engineering 126

Data Engineering Data Engineer Engineering Pipeline-centric 126

Data Engineering Podcast

NOVEMBER 20, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. And don’t forget to thank them for their continued support of this show!

Data Lake 130

Data Lake Data Ingestion MongoDB Scala 130

Data Engineering Podcast

NOVEMBER 6, 2022

Their SDKs make event streaming from any app or website easy, and their extensive library of integrations enable you to automatically send data to hundreds of downstream tools. Sign up free at dataengineeringpodcast.com/rudder Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

MongoDB 130

MongoDB Scala MySQL Data Lake 130

Knowledge Hut

NOVEMBER 17, 2023

They work with various stakeholders to provide real-time data analytics, maintain data quality and integrity, and deliver insightful data to the business. The main duties of an Azure Data Engineer are planning, developing, deploying, and managing the data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

NOVEMBER 28, 2023

Let us take a look at the top technical skills that are required by a data engineer first: A. Technical Data Engineer Skills 1.Python Python is ubiquitous, which you can use in the backends, streamline data processing, learn how to build effective data architectures, and maintain large data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Data Engineering Podcast

AUGUST 21, 2022

Data stacks are becoming more and more complex. This brings infinite possibilities for data pipelines to break and a host of other issues, severely deteriorating the quality of the data and causing teams to lose trust. Data stacks are becoming more and more complex.

Lambda Architecture 100

Lambda Architecture MongoDB Scala MySQL 100

ProjectPro

JANUARY 24, 2023

AWS Glue is a fully managed extract, transform, and load (ETL) service that simplifies the preparation and loading of data for analytics. AWS Glue provides the functionality required by enterprises to build ETL pipelines. The user only needs to define a data pipeline and the processes they want to perform when data flows through it.

AWS 52

AWS Cloud Amazon Web Services ETL Tools 52

Data Engineering Podcast

MARCH 1, 2021

Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days. Once you sign up and create an alert in Datafold for your company data, they will send you a cool water flask.

Machine Learning 100

Machine Learning Data Warehouse Scala Hadoop 100

ProjectPro

FEBRUARY 21, 2023

They must also understand how to build a data processing pipeline that can support the five Vs of big data- volume, velocity, variety, veracity, and value- as well as how to transform this data into maintainable code. Python, Java, and Scala knowledge are essential for Apache Spark developers.

Scala 52

Scala Programming Language Java Hadoop 52

Cloudera

OCTOBER 12, 2020

Eventador, based in Austin, TX, was founded by Erik Beebe and Kenny Gorman in 2016 to address a fundamental business problem – make it simpler to build streaming applications built on real-time data. This typically involved a lot of coding with Java, Scala or similar technologies.

Cloud 131

Cloud Process Scala Kafka 131

Data Engineering Podcast

JUNE 19, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Metadata 130

Metadata MongoDB Scala MySQL 130

Data Engineering Podcast

NOVEMBER 13, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. And don’t forget to thank them for their continued support of this show!

MongoDB 100

MongoDB Scala Google Cloud MySQL 100

Data Engineering Podcast

AUGUST 13, 2022

Data stacks are becoming more and more complex. This brings infinite possibilities for data pipelines to break and a host of other issues, severely deteriorating the quality of the data and causing teams to lose trust. Data stacks are becoming more and more complex.

Metadata 100

Metadata MongoDB Scala MySQL 100

Data Engineering Podcast

OCTOBER 30, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. And don’t forget to thank them for their continued support of this show!

Engineering 100

Engineering MongoDB Scala MySQL 100

Snowflake

JULY 10, 2023

Now, with unstructured data processing natively supported in Snowflake, we can process netCDF file types, thereby unifying our data pipeline. Processing files in a Python UDF and Stored Procedure has piqued the interest of our data scientists and paves the way for automation of new, complex data pipelines.”

Unstructured Data 40

Unstructured Data Python Process Scala 40

Knowledge Hut

APRIL 25, 2023

Data engineering tools can help automate many of these processes, allowing data engineers to focus on higher-level tasks like extracting insights and building data pipelines. If you want to learn more about data engineering tools, get guidance from Data Engineer courses online.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

SEPTEMBER 26, 2023

A person who designs and implements data management , monitoring, security, and privacy utilizing the entire suite of Azure data services to meet an organization's business needs is known as an Azure Data Engineer. The main exam for the Azure data engineer path is DP 203 learning path.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Data Engineering Podcast

AUGUST 28, 2022

Data stacks are becoming more and more complex. This brings infinite possibilities for data pipelines to break and a host of other issues, severely deteriorating the quality of the data and causing teams to lose trust. Data stacks are becoming more and more complex.

Building 100

Building MongoDB Scala MySQL 100

Snowflake

JUNE 27, 2023

Data engineers can run optimized logic, typically written in C/C++, in the same processing engine that runs SQL or Python DataFrame operations. Users are able to write data queries in SQL, Python, Java, or Scala that process data through containers running in Snowpark Container Services. Astronomer.

Scala 61

Scala Programming Language Data Science Python 61

Monte Carlo

MAY 31, 2022

When a data pipeline breaks, data engineers need to immediately understand where the rupture occurred and what has been impacted. Data downtime is costly. Field-level data lineage (not necessarily Spark lineage) with hundreds of connections between objects in upstream and downstream tables.

Data Lake 52

Data Lake Building Scala Metadata 52

Data Engineering Podcast

JULY 31, 2022

Data stacks are becoming more and more complex. This brings infinite possibilities for data pipelines to break and a host of other issues, severely deteriorating the quality of the data and causing teams to lose trust. Data stacks are becoming more and more complex.

Data Analysis 100

Data Analysis MongoDB Scala Algorithm 100

AltexSoft

MARCH 30, 2023

Here are four main applications of the platform across industries: data warehousing — SQL queries and business intelligence (BI) at scale; data engineering — building and maintaining data pipelines , running ETL and ELT workloads; data streaming and real-time analytics , and data science and machine learning projects.

Scala 64

Scala Data Lake BI Google Cloud 64

Data Engineering Podcast

JULY 3, 2022

Your newly mimicked datasets are safe to share with developers, QA, data scientists—heck, even distributed teams around the world. Shorten development cycles, eliminate the need for cumbersome data pipeline work, and mathematically guarantee the privacy of your data, with Tonic.ai.

Data Integration 100

Data Integration MongoDB Scala MySQL 100

ProjectPro

AUGUST 9, 2022

It is one of the most effective and reliable tools used by data engineers for orchestration, logging, and scheduling workflows or data pipelines. use Airflow to run their data pipelines efficiently. The pipeline can be started manually or using an external trigger (e.g., What is Apache Airflow Used For?

Scala 52

Scala Banking Hadoop Machine Learning 52

Data Engineering Podcast

JUNE 5, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. By the time errors have made their way into production, it’s often too late and damage is done.

Data Security 100

Data Security Metadata MongoDB Scala 100

Towards Data Science

DECEMBER 24, 2023

0 — Quick Review Quickly, let’s review what spark does… Spark is a big data processing engine. It takes python/java/scala/R/SQL and converts that code into a highly optimized set of transformations. At it’s lowest level, spark creates tasks, which are parallelizable transformations on data partitions. Let’s dive in!

Scala 79

Scala SQL Java Python 79

Data Engineering Podcast

AUGUST 13, 2022

Data stacks are becoming more and more complex. This brings infinite possibilities for data pipelines to break and a host of other issues, severely deteriorating the quality of the data and causing teams to lose trust. Data stacks are becoming more and more complex.

Machine Learning 100

Machine Learning Pipeline-centric Database-centric MongoDB 100

Data Engineering Podcast

AUGUST 6, 2022

Data stacks are becoming more and more complex. This brings infinite possibilities for data pipelines to break and a host of other issues, severely deteriorating the quality of the data and causing teams to lose trust. Data stacks are becoming more and more complex.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Knowledge Hut

JUNE 20, 2023

Languages Python, SQL, Java, Scala R, C++, Java Script, and Python Tools Kafka, Tableau, Snowflake, etc. Skills A data engineer should have good programming and analytical skills with big data knowledge. These technologies oversee making a data engineer's day-to-day duties easier in a variety of ways.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52