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

AUGUST 28, 2022

Select Star’s data discovery platform solves that out of the box, with an automated catalog that includes lineage from where the data originated, all the way to which dashboards rely on it and who is viewing them every day. That’s where our friends at Ascend.io That’s where our friends at Ascend.io

Building 100

Building MongoDB Scala MySQL 100

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

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. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability.

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Data Engineering Podcast

JUNE 5, 2022

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. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.

Data Security 100

Data Security Metadata MongoDB Scala 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

Select Star’s data discovery platform solves that out of the box, with an automated catalog that includes lineage from where the data originated, all the way to which dashboards rely on it and who is viewing them every day. That’s where our friends at Ascend.io That’s where our friends at Ascend.io

Machine Learning 100

Machine Learning Pipeline-centric Database-centric MongoDB 100

Data Engineering Podcast

AUGUST 6, 2022

Summary The optimal format for storage and retrieval of data is dependent on how it is going to be used. For analytical systems there are decades of investment in data warehouses and various modeling techniques. For analytical systems there are decades of investment in data warehouses and various modeling techniques.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Data Engineering Podcast

SEPTEMBER 4, 2022

Select Star’s data discovery platform solves that out of the box, with an automated catalog that includes lineage from where the data originated, all the way to which dashboards rely on it and who is viewing them every day. That’s where our friends at Ascend.io That’s where our friends at Ascend.io

MongoDB 100

MongoDB Scala MySQL Data Ingestion 100

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

Knowledge Hut

APRIL 25, 2023

Data engineers add meaning to the data for companies, be it by designing infrastructure or developing algorithms. The practice requires them to use a mix of various programming languages, data warehouses, and tools. While they go about it - enter big data data engineer tools.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Edureka

FEBRUARY 9, 2023

As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical. Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. It is also crucial to have experience with data ingestion and transformation.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

FEBRUARY 8, 2023

It offers users a data integration tool that organizes data from many sources, formats it, and stores it in a single repository, such as data lakes, data warehouses, etc., Glue uses ETL jobs for extracting data from various AWS cloud services and integrating it into data warehouses and lakes.

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure's Azure Synapse, formerly known as Azure SQL Data Warehouse, is a complete analytics offering. Designed to tackle the challenges of modern data management and analytics, Azure Synapse brings together the worlds of big data and data warehousing into a unified and seamlessly integrated platform.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Edureka

FEBRUARY 7, 2023

They should also be proficient in programming languages such as Python , SQL , and Scala , and be familiar with big data technologies such as HDFS , Spark , and Hive. Learn programming languages: Azure Data Engineers should have a strong understanding of programming languages such as Python , SQL , and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Snowflake

MAY 22, 2023

Snowpark Scala user-defined function handlers – public preview Scala user-defined functions can now be created with in-line SQL or from a JAR on a stage. Plus, VerityData is the only insider data provider that delivers daily research insights from experts—elevating the insights so you don’t have to dig for them.

Healthcare 52

Healthcare Scala Medical Transportation 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. Students have the chance to put Azure data solutions into practice with the Microsoft Azure DP-203 certification training.

Data Engineering 52

Data Engineering Data Engineer Engineering Cloud Computing 52

Cloudera

JUNE 16, 2022

Faster data ingestion: streaming ingestion pipelines. Laila wants to use CSP but doesn’t have time to brush up on her Java or learn Scala, but she knows SQL really well. . Figure 1: The evolution of Cloudera Stream Processing offering based on customers’ evolving streaming use cases and requirements.

Kafka 86

Kafka Manufacturing Data Lake SQL 86

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value. ML workflow, ubr.to/3EJHjvm

Engineering 83

Engineering Raw Data Data Science Scala 83

Knowledge Hut

JUNE 26, 2023

Finnhub API with Kafka for Real-Time Financial Market Data Pipeline Project Overview: The goal of this project is to construct a streaming data pipeline by making use of the real-time financial market data API provided by Finnhub. Learn Data Engineering the Smart Way! Scripting and automation are skills you should learn.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

AltexSoft

JULY 29, 2022

To facilitate data ingestion, there are Apache Flume aggregating log data from multiple servers and Apache Sqoop designed to transport information between Hadoop and relational (SQL) databases. If you’re going to create applications for the Hadoop ecosystem, get familiar with Scala, which is the default language of Apache Spark.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. The prepared data is then stored in a data warehouse or a similar repository.

Big Data 52

Big Data Hadoop AWS Relational Database 52