Data Engineering Podcast

APRIL 19, 2021

Sometimes, however, one of those transformations is actually a full-fledged machine learning project in its own right. It builds your customer data warehouse and your identity graph on your data warehouse, with support for Snowflake, Google BigQuery, Amazon Redshift, and more. Via the UI or via an API. Flexibility. Dependencies.

Data Pipeline 100

Data Pipeline Machine Learning Data Warehouse Datasets 100

Towards Data Science

NOVEMBER 4, 2023

Cloud platform leaders made DWH (Snowflake, BigQuery, Redshift, Firebolt) infrastructure management really simple and in many scenarios they will outperform and dedicated in-house infrastructure management team in terms of cost-effectiveness and speed. So here are a few things to consider that can help us answer these questions.

Data Engineering 82

Data Engineering Data Engineer Engineering BI 82

Knowledge Hut

NOVEMBER 16, 2023

Machine Learning. Upload your code, and Elastic Beanstalk will handle the rest, including capacity provisioning, load balancing and auto scaling as well as application health monitoring. AWS Machine Learning: It is a service that makes it simple to create intelligent applications. Networking & Content Delivery.

AWS 52

AWS Amazon Web Services Cloud Computing Cloud Storage 52

Data Engineering Weekly

DECEMBER 4, 2022

[link] Joseph Monti: It’s Time We Treat Our Data Like an API The application development came a long way in standardizing the interoperability of services. COM/DCOM, CORBA, WSDL to REST Api & rpc frameworks gRPC. The author narrates the need for Data like the API. It's time we treat our data like API.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

JANUARY 9, 2024

Furthermore, via hands-on projects, applicants learn the ways to utilize public cloud computing platforms like Microsoft Azure and Amazon Web Services (AWS). Therefore, learning cloud computing can serve as a gateway for a high-paying career. It discusses the definition of cloud computing, its evolution, pros, cons, and challenges.

Cloud Computing 52

Cloud Computing Cloud Amazon Web Services Cloud Storage 52

ProjectPro

JANUARY 24, 2023

Integration with other AWS services like S3, Redshift, etc. Learn more about Big Data Tools and Technologies with Innovative and Exciting Big Data Projects Examples. ADF features a REST API,Net and Python SDKs, and a PowerShell CLI as developer tools. The DPU price is the same for most AWS Glue tasks and operations.

AWS 52

AWS Cloud Amazon Web Services ETL Tools 52

Knowledge Hut

SEPTEMBER 29, 2023

These mind maps are a fantastic resource for learning about AWS's vast array of services and how they are linked. To learn more about the AWS ecosystem you can refer in certifications for Cloud Engineers. Amazon Redshift: Data warehousing service that is quick and scalable. Amazon RDS: Relational database management service.

AWS 52

AWS Amazon Web Services Cloud Storage Relational Database 52

AltexSoft

AUGUST 29, 2023

If your organization fits into one of these categories and you’re considering implementing advanced data management and analytics solutions, keep reading to learn how data lakes work and how they can benefit your business. This makes them ideal for more advanced analytics activities, including real-time analytics and machine learning.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Data Science Blog: Data Engineering

DECEMBER 23, 2022

Viele Unternehmen sind gerade auf dem Weg zum Data-Driven Business, einer Unternehmensführung, die für ihre Entscheidungen auf transparente Datengrundlagen setzt und unter Einsatz von Business Intelligence, Data Science sowie der Automatisierung mit Deep Learning und RPA operative Prozesse so weit wie möglich automatisiert.

Data Engineering 52

Data Engineering Data Engineer Engineering Business Intelligence 52

ProjectPro

AUGUST 24, 2021

Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. They are also often expected to prepare their dataset by web scraping with the help of various APIs.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

NOVEMBER 7, 2022

If this is not a big deal, read on to learn more about Airflow concepts and architecture which, in turn, predefine its pros and cons. Airflow communicates with other platforms in the data ecosystem using hooks — high-level interfaces that spare you the trouble of searching for special libraries or writing code to hit external APIs.

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

ProjectPro

FEBRUARY 21, 2023

A professional certificate can also offer a well-structured learning path to improve your understanding of specific technologies or professional skills. The rest of the exam details are the same as the DP-900 exam. Can design, develop, and implement high-quality data processing systems and machine learning solutions.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

JULY 23, 2021

Orchestrate Redshift ETL using AWS Glue and Step Functions AWS Projects for Portfolio 17. How long does it take to learn AWS? How do I learn AWS from scratch? AWS Lambda and API Gateway are suitable for using the backend API. You shall also be aware of HTML, JavaScript, CSS, and RESTful API implementation.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

ProjectPro

JANUARY 31, 2022

Centralized Source of Data When training machine learning models, data scientists must consider a wide range of data. Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics. What is data collection? Data engineering explained in 14 minutes.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Rockset

AUGUST 23, 2019

The first step in this process was diving into DynamoDB’s documentation and doing some experimentation to ensure that we were using DynamoDB’s read APIs in a way that maximizes both the stability and performance of our system. Background on DynamoDB APIs AWS offers a Scan API and a Streams API for reading data from DynamoDB.

Bytes 52

Bytes NoSQL SQL AWS 52

Confluent

APRIL 11, 2019

But even if a use case requires a specific database such as Amazon Redshift, data will still land to S3 first and only then load to Redshift. Now that I’m only one REST API call away from starting the S3 connector, I’ll issue the call using the Confluent CLI: confluent load meetups-to-s3 -d./meetups-to-s3.json.

Kafka 110

Kafka AWS Metadata Architecture 110

Monte Carlo

AUGUST 19, 2023

I’ve also updated this post to include additional layers frequently found within a modern data platform such as data governance, access management, and machine learning. Amazon Kinesis – A streaming solution from AWS that may be ideal for those utilizing Redshift as their data warehouse. It depends.

Building 52

Building BI Data Lake Data Governance 52

Monte Carlo

MAY 9, 2023

The founders invested in a small-but-mighty data team of three (Michael himself, a data scientist, and a data engineer) to serve the rest of the organization, around 45 people at the time of our conversation. Learn how Monte Carlo and data observability can ensure your insights are timely and trusted.

IT 52

IT Data Datasets Building 52

ProjectPro

JANUARY 24, 2023

Sounds exciting to learn more about Google BigQuery, read on! Some excellent cloud data warehousing platforms are available in the market- AWS Redshift, Google BigQuery , Microsoft Azure , Snowflake , etc. 3) Machine Learning Machine learning (ML) models may be created and used in BigQuery ML models using Google Standard SQL queries.

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

ProjectPro

DECEMBER 7, 2021

Data Pipeline Tools AWS Data Pipeline Azure Data Pipeline Airflow Data Pipeline Learn to Create a Data Pipeline FAQs on Data Pipeline What is a Data Pipeline? It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

AUGUST 9, 2018

Differentiate between Amazon RDS, Redshift, and Dynamo DB. Features Amazon RDS Redshift Dynamo DB Computing Resources Instances with 64 vCPU and 244 GB RAM Nodes with vCPU and 244 GB RAM Not specified, SaaS-Software as a Service. It can also provide a history of AWS API calls for a particular account. 30 minutes every week.

AWS 40

AWS Amazon Web Services Cloud Computing Database 40

Monte Carlo

AUGUST 31, 2023

These conversations inspired us to write this book to convey some of the best practices we’ve learned and developed related to managing data quality at each stage of the data pipeline, from ingestion to analytics, and share how data teams in similar situations may be able to prevent their own data downtime. Meet: the data lakehouse.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

phData: Data Engineering

DECEMBER 16, 2021

In order to place one tool above the rest, you’ll have to look beyond just the features. Once Alation is being used to curate metadata, machine learning pattern recognition is used to determine usage patterns inside the catalog itself. What Things Should I Consider Before Choosing a Data Catalog Tool?

Metadata 52

Metadata Datasets ETL Tools Cloud 52

AltexSoft

NOVEMBER 23, 2021

This post is a perfect place to learn about this approach, its architecture components, differences, benefits, tools, and more. You can learn more about how such data pipelines are built in our video about data engineering. What is data virtualization? Data virtualization platforms can link to different data sources including.

Process 69

Process Data Lake Metadata Data Warehouse 69

Knowledge Hut

AUGUST 18, 2023

Individuals who have ample experience working with specific AWS services may pursue a specialty certification such as AWS Certified Security or AWS Certified Machine Learning. Having an AWS certification on your resume can help you stand out from the rest of the candidate pool & lead to increased job opportunities.

AWS 52

AWS Certification Amazon Web Services Cloud 52

phData: Data Engineering

JANUARY 3, 2022

This commonly introduces: Database or Data Warehouse API/EDI Integrations ETL software Business intelligence tooling By leveraging off-the-shelf tooling, your company separates disciplines by technology. The rest of this section will focus on Git specifically. A common tool that’s used for orchestration is Apache Airflow.

IT 52

IT AWS Software Engineer Software Engineering 52

Confluent

SEPTEMBER 20, 2019

BigQuery, Amazon Redshift, and MongoDB Atlas) and caches (e.g., Now from the application perspective, all the information required to start working with Apache Kafka is in the bootstrap servers endpoint, which is the cluster that your application will connect to, and the API key and secret used to identify your application.

Kafka 21

Kafka Management Cloud AWS 21