Knowledge Hut

APRIL 25, 2023

Here, we'll take a look at the top data engineer tools in 2023 that are essential for data professionals to succeed in their roles. These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

ProjectPro

JANUARY 31, 2022

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Knowledge Hut

APRIL 19, 2023

Let's take a closer look at each component: Source System: The source system is the data source. It can be any system that creates data, including databases, files, APIs, and cloud services. The source data must be retrieved from this system in a format that the transformation engine can use.

Data Warehouse 52

Data Warehouse Business Intelligence ETL Tools Data Pipeline 52

Knowledge Hut

JUNE 20, 2023

Apache Spark, Microsoft Azure, Amazon Web services, etc. Skills A data engineer should have good programming and analytical skills with big data knowledge. A machine learning engineer should know deep learning, scaling on the cloud, working with APIs, etc. It is a cloud-based machine learning platform.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Rockset

FEBRUARY 24, 2022

I’ll focus on the use of events to help understand, analyze and diagnose problems using various OLAP databases and AWS Kinesis data streams. AWS Kinesis Kinesis is Amazon’s solution for collecting and processing streaming data in real time. Rockset is the real-time analytics database in the cloud for modern data teams.

AWS 52

AWS Amazon Web Services Kafka SQL 52

ProjectPro

JANUARY 24, 2023

Integration with other AWS services: SageMaker integrates seamlessly with other services, such as Amazon Simple Storage Service(S3) and Amazon Elastic Compute Cloud (EC2), making it easy to incorporate machine learning into existing workflow and infrastructure. Amazon launched SageMaker in November 2017.

Building 52

Building Algorithm Machine Learning AWS 52

AltexSoft

MAY 14, 2021

With the ETL approach, data transformation happens before it gets to a target repository like a data warehouse, whereas ELT makes it possible to transform data after it’s loaded into a target system. Data storage and processing. Also, Spark supports machine learning (MLlib), SQL, graph processing (GraphX). Apache Kafka.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

SEPTEMBER 26, 2021

Many organizations are willing to pay 20-30% more to their Data Engineers than to Data Scientists. Google Trends shows the large-scale demand and popularity of Big Data Engineer compared with other similar roles, such as IoT Engineer, AI Programmer, and Cloud Computing Engineer. Who is a Big Data Engineer?

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

AUGUST 24, 2021

This is an end-to-end big data project for building a data engineering pipeline involving data extraction, data cleansing, data transformation, exploratory analysis , data visualization, data modeling, and data flow orchestration of event data on the cloud.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

MAY 31, 2021

There are open data platforms in several regions (like data.gov in the U.S.). These open data sets are a fantastic resource if you're working on a personal project for fun. Data Preparation and Cleaning The data preparation step, which may consume up to 80% of the time allocated to any big data or data engineering project, comes next.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

DECEMBER 10, 2021

What do you understand about cloud computing? Can you tell something about Azure Cloud Service? What are the various models available for cloud deployment? How many cloud service roles are provided by Azure? Why Must You Prepare For Azure Interview Questions? What makes Azure better than AWS?

BI 52

BI Cloud Computing SQL Database 52

ProjectPro

OCTOBER 20, 2021

This would include the automation of a standard machine learning workflow which would include the steps of Gathering the data Preparing the Data Training Evaluation Testing Deployment and Prediction This includes the automation of tasks such as Hyperparameter Optimization, Model Selection, and Feature Selection.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52