Data Engineering Podcast

JULY 17, 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

NOVEMBER 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.

MongoDB 100

MongoDB Scala Google Cloud MySQL 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.

Metadata 100

Metadata MongoDB Scala MySQL 100

Netflix Tech

JANUARY 25, 2023

Unlike Java, we support multiple inheritance as well. We have several ML algorithms which scan Netflix media assets (images and videos) and create very interesting data for example identifying characters in frames or identifying match cuts. This allows our clients to create an “is-a-type-of” relationship between schemas.

Algorithm 113

Algorithm Media Metadata Data Ingestion 113

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

Cloudera

FEBRUARY 9, 2021

If you are a database administrator or developer, you can start writing queries right-away using Apache Phoenix without having to wrangle Java code. . To store and access data in the operational database, you can do one of the following: Use native Apache HBase client APIs to interact with data in HBase: Use the HBase APIs for Java.

Database 103

Database Java Data Ingestion SQL 103

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

Confluent

FEBRUARY 6, 2019

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. You can still import other models if you want (e.g.,

Machine Learning 107

Machine Learning Python Kafka Java 107

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

Knowledge Hut

NOVEMBER 2, 2023

Top 10 Azure Data Engineering Project Ideas for Beginners For beginners looking to gain practical experience in Azure Data Engineering, here are 10 Azure Data engineer real time projects ideas that cover various aspects of data processing, storage, analysis, and visualization using Azure services: 1.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

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

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 96

Hospitality Kafka Retail Data Ingestion 96

Striim

NOVEMBER 13, 2023

Introduction In the fast-evolving world of data integration, Striim’s collaboration with Snowflake stands as a beacon of innovation and efficiency. Striim’s integration with Snowpipe Streaming represents a significant advancement in real-time data ingestion into Snowflake.

Data Ingestion 59

Data Ingestion Utilities Data Integration Data 59

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

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

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

Netflix Tech

OCTOBER 19, 2020

Our tactical approach was to use Netflix-specific libraries for collecting traces from Java-based streaming services until open source tracer libraries matured. We chose Open-Zipkin because it had better integrations with our Spring Boot based Java runtime environment.

Building 93

Building Transportation Metadata Java 93

Snowflake

APRIL 19, 2023

Welcome to the third blog post in our series highlighting Snowflake’s data ingestion capabilities, covering the latest on Snowpipe Streaming (currently in public preview) and how streaming ingestion can accelerate data engineering on Snowflake. What is Snowpipe Streaming?

Data Ingestion 57

Data Ingestion Kafka Java Data Pipeline 57

Cloudera

MARCH 27, 2019

Cloudera Flow Management (CFM) is a no-code data ingestion and management solution powered by Apache NiFi. With a slick user interface, 300+ processors and the NiFi Registry, CFM delivers highly scalable data management and DevOps capabilities to the enterprise. NiFi can handle all types of data across any type of data source.

Management 72

Management Data Ingestion Machine Learning Java 72

LinkedIn Engineering

OCTOBER 19, 2023

To enable the ingestion and real-time processing of enormous volumes of data, LinkedIn built a custom stream processing ecosystem largely with tools developed in-house (and subsequently open-sourced). In 2010, they introduced Apache Kafka , a pivotal Big Data ingestion backbone for LinkedIn’s real-time infrastructure.

Process 119

Process Lambda Architecture Kafka Machine Learning 119

Knowledge Hut

MAY 2, 2024

As per Apache, “ Apache Spark is a unified analytics engine for large-scale data processing ” Spark is a cluster computing framework, somewhat similar to MapReduce but has a lot more capabilities, features, speed and provides APIs for developers in many languages like Scala, Python, Java and R.

Scala 52

Scala Hospitality Healthcare Retail 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Ascend.io

FEBRUARY 15, 2023

I didn’t know it yet, but big data would be a big deal Google was my first position out of college. In 2004, there was no such thing as a “frontend engineer,” so I was hired as a “Java developer,” working on the UI for web search (which, ironically, was written in C++). I’ll be writing about this topic and others in the coming months.

Cloud 52

Cloud Amazon Web Services Hadoop Telecommunication 52

Ascend.io

FEBRUARY 15, 2023

I didn’t know it yet, but big data would be a big deal Google was my first position out of college. In 2004, there was no such thing as a “frontend engineer,” so I was hired as a “Java developer,” working on the UI for web search (which, ironically, was written in C++). I’ll be writing about this topic and others in the coming months.

Cloud 52

Cloud Amazon Web Services Hadoop Telecommunication 52