Data Engineering Podcast

OCTOBER 30, 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.

Engineering 100

Engineering MongoDB Scala MySQL 100

Data Engineering Podcast

OCTOBER 23, 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.

Database 100

Database MySQL Cloud MongoDB 100

Data Engineering Podcast

OCTOBER 16, 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.

Data Lake 100

Data Lake Food MongoDB Scala 100

Data Engineering Podcast

SEPTEMBER 25, 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.

Food 100

Food MongoDB Scala MySQL 100

Data Engineering Podcast

SEPTEMBER 18, 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.

Hospitality 100

Hospitality Food MongoDB Scala 100

Data Engineering Podcast

AUGUST 28, 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.

Building 100

Building MongoDB Scala MySQL 100

Data Engineering Podcast

JULY 24, 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.

MongoDB 100

MongoDB Scala MySQL Data Lake 100

Data Engineering Podcast

JULY 10, 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.

Data Engineering 100

Data Engineering Data Engineer Engineering MongoDB 100

Data Engineering Podcast

JULY 3, 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.

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Data Engineering Podcast

SEPTEMBER 11, 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.

Data Pipeline 130

Data Pipeline Building MongoDB Scala 130

Data Engineering Podcast

JUNE 5, 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.

Data Security 100

Data Security Metadata MongoDB Scala 100

Ascend.io

OCTOBER 4, 2023

Snowpark stands out as a game-changer for data engineers. It empowers them to tap into the familiar terrain of languages like Scala, Java, and Python, but with the unique advantage of not having to move data out of Snowflake. Snowflake is renowned for its vast capabilities, and Snowpark is no exception.

Scala 52

Scala Data Ingestion Python Java 52

Data Engineering Podcast

OCTOBER 9, 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.

Food 100

Food MongoDB Scala MySQL 100

Data Engineering Podcast

OCTOBER 2, 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.

IT 100

IT Food PostgreSQL MongoDB 100

Data Engineering Podcast

AUGUST 13, 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.

Machine Learning 100

Machine Learning Pipeline-centric Database-centric MongoDB 100

Data Engineering Podcast

AUGUST 6, 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.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Data Engineering Podcast

JUNE 26, 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.

Data Management 100

Data Management Management MongoDB Scala 100

Data Engineering Podcast

SEPTEMBER 4, 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.

MongoDB 100

MongoDB Scala MySQL Data Ingestion 100

Knowledge Hut

JULY 27, 2023

They are skilled in working with tools like MapReduce, Hive, and HBase to manage and process huge datasets, and they are proficient in programming languages like Java and Python. Using the Hadoop framework, Hadoop developers create scalable, fault-tolerant Big Data applications. What do they do? How to Improve Hadoop Developer Salary?

Hadoop 52

Hadoop Programming Language Banking Scala 52

Snowflake

AUGUST 16, 2023

Data comes in a continuous manner, and often a separate architecture is required to handle streaming data. What remains challenging is how streaming data is brought together with batch data. That’s why we built Snowpipe Streaming, now generally available to handle row-set data ingestion. Learn more here.

Scala 52

Scala Transportation Kafka Data Lake 52

Cloudera

APRIL 20, 2021

The developers must understand lower-level languages like Java and Scala and be familiar with the streaming APIs. A modern streaming architecture consists of critical components that provide data ingestion, security and governance, and real-time analytics. What is modern streaming architecture?

Hospitality 91

Hospitality Kafka Retail Data Ingestion 91

Knowledge Hut

APRIL 25, 2023

Here are some essential skills for data engineers when working with data engineering tools. Strong programming skills: Data engineers should have a good grasp of programming languages like Python, Java, or Scala, which are commonly used in data engineering.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

OCTOBER 3, 2023

Additionally, for a job in data engineering, candidates should have actual experience with distributed systems, data pipelines, and related database concepts. Conclusion A position that fits perfectly in the current industry scenario is Microsoft Certified Azure Data Engineer Associate.

Data Engineering 52

Data Engineering Data Engineer Engineering Cloud Computing 52

ProjectPro

FEBRUARY 21, 2023

Azure Data Engineer Associate DP-203 Certification Candidates for this exam must possess a thorough understanding of SQL, Python, and Scala, among other data processing languages. Must be familiar with data architecture, data warehousing, parallel processing concepts, etc. big data and ETL tools, etc.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

JUNE 28, 2022

In part two we will explore how we can run real-time streaming analytics using Apache Flink, and we will use Cloudera SQL Stream Builder GUI to easily create streaming jobs using only SQL language (no Java/Scala coding required). The use case. Fraud detection is a great example of a time-critical use case for us to explore.

Process 80

Process Kafka SQL Machine Learning 80

Knowledge Hut

APRIL 25, 2023

An end-to-end Data Science pipeline starts from business discussion to delivering the product to the customers. One of the key components of this pipeline is Data ingestion. It helps in integrating data from multiple sources such as IoT, SaaS, on-premises, etc., What is Data Ingestion?

Data Ingestion 52

Data Ingestion Lambda Architecture Raw Data Kafka 52

Data Engineering Podcast

NOVEMBER 20, 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.

Data Lake 130

Data Lake Data Ingestion MongoDB Scala 130

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. When working with Snowpark UDFs, some of the logic can become quite complex.

Java 90

Java Scala Hadoop Data Ingestion 90

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

JULY 31, 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.

Data Analysis 100

Data Analysis MongoDB Scala Algorithm 100

Snowflake

NOVEMBER 29, 2023

Data processing: Snowflake provides a unified interface to explore and analyze data with SQL and Python/Java/Scala-based modalities, thus connecting both data scientists and data analyst personas in one ecosystem.

Healthcare 81

Healthcare Metadata Medical Data Storage 81

Data Engineering Podcast

MAY 29, 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.

Architecture 100

Architecture Database Data Architecture PostgreSQL 100

Rockset

MARCH 27, 2023

One additional note: while many stream processing platforms support declarative languages like SQL, they also support Java, Scala, or Python, which are appropriate for advanced use cases like machine learning. It was developed by the Apache Software Foundation and is written in Java and Scala. Stateful Or Not?

Database 52

Database Process Scala SQL 52

Rock the JVM

JANUARY 21, 2023

The code samples are written in Kotlin, but the implementation should be easy to port in Java or Scala. Our event data is stored in CSV files that we want to ingest into Kafka, and since it is not real-time data ingestion, we don’t really care about latency here, but having a good throughput so that we can ingest them fast.

Kafka 68

Kafka Java Scala Coding 68

ProjectPro

JANUARY 25, 2022

PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. Multi-Language Support PySpark platform is compatible with various programming languages, including Scala, Java, Python, and R. When it comes to data ingestion pipelines, PySpark has a lot of advantages.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

DECEMBER 28, 2021

Whether you're working with semi-structured, structured, streaming, or machine learning data, Apache Spark is a fast, easy-to-use framework that allows you to solve various complex data issues. Many traditional stream processing systems use a continuous operator model to process data. Table of Contents What is Spark streaming?

Architecture 52

Architecture Kafka Java Scala 52

AltexSoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. Python and R are essential for data analysts; and.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59