DataKitchen

JUNE 12, 2023

We wrote the first version because, after talking with hundreds of people at the 2016 Strata Hadoop World Conference, very few easily understood what we discussed at our booth and conference session. Those tools work together to take data from its source and deliver it to your customers. Why should I care?

ETL Tools 52

ETL Tools Data Science Data Lake Hadoop 52

Knowledge Hut

NOVEMBER 17, 2023

Additionally, they convert data into formats that can be used and store it effectively and securely in the Azure cloud. Data engineers must know data management fundamentals, programming languages like Python and Java, cloud computing and have practical knowledge on data technology.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required. To store various types of data, various methods are used.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Data Engineering Weekly

DECEMBER 29, 2022

era of Data Catalog Let’s call the pre-modern era; as the state of Data Warehouses before the explosion of big data and subsequent cloud data warehouse adoption. A couple of important characteristics of a Data Warehouse at this time The ETL tools and Data Warehouse appliances are limited in scope. The modern(?)

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Knowledge Hut

JANUARY 30, 2024

Its flexibility allows organizations to leverage data value, regardless of its format or source, and can reside in various storage environments, from on-premises solutions to cloud-based platforms or a hybrid approach, tailored to the organization's specific needs and strategies.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

AltexSoft

OCTOBER 8, 2021

Usually, data integration software is divided into on-premise, cloud-based, and open-source types. On-premise data integration tools. As the name suggests, these tools aim at integrating data from different on-premise source systems. Cloud-based data integration tools. Cloud-based tools make up another category.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

Knowledge Hut

SEPTEMBER 26, 2023

Data engineers work on the data to organize and make it usable with the aid of cloud services. The duties and responsibilities that a Microsoft Azure Data Engineer is required to carry out are all listed in this section: Data engineers provide and establish on-premises and cloud-based data platform technologies.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Edureka

FEBRUARY 7, 2023

Microsoft Azure is one of the most popular and rapidly expanding cloud service providers. Microsoft Azure is a cloud computing platform that includes hardware as well as software. 2) What is Azure’s primary ETL service? Export information to Azure Data Lake Store, Azure Blob Storage, or Hadoop.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

AltexSoft

MARCH 30, 2023

Source: Databricks Delta Lake is an open-source, file-based storage layer that adds reliability and functionality to existing data lakes built on Amazon S3, Google Cloud Storage, Azure Data Lake Storage, Alibaba Cloud, HDFS ( Hadoop distributed file system), and others. Delta Lake integrations.

Scala 64

Scala Data Lake BI Google Cloud 64

ProjectPro

FEBRUARY 21, 2023

Vendor-Specific Data Engineering Certifications The vendor-specific data engineer certifications help you enhance your knowledge and skills relevant to specific vendors, such as Azure, Google Cloud Platform, AWS, and other cloud service vendors. The certification gives you the technical know-how to work with cloud computing systems.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

AltexSoft

OCTOBER 30, 2021

Data engineers are programmers first and data specialists next, so they use their coding skills to develop, integrate, and manage tools supporting the data infrastructure: data warehouse, databases, ETL tools, and analytical systems. ETL and BI skills. Deploying machine learning models. Machine learning techniques.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

ProjectPro

SEPTEMBER 26, 2021

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. Big Data Engineer identifies the internal and external data sources to gather valid data sets and deals with multiple cloud computing environments.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

MAY 2, 2024

Features of Spark Speed : According to Apache, Spark can run applications on Hadoop cluster up to 100 times faster in memory and up to 10 times faster on disk. This would mean huge amounts of data and current cloud computing may not be sufficient to cater to so much data transfer, data processing and online demand of customer’s request.

Scala 52

Scala Hospitality Healthcare Retail 52

ProjectPro

NOVEMBER 30, 2021

ETL (Extract, Transform, and Load) Pipeline involves data extraction from multiple sources like transaction databases, APIs, or other business systems, transforming it, and loading it into a cloud-hosted database or a cloud data warehouse for deeper analytics and business intelligence.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

FEBRUARY 18, 2022

Anyone who works with data, whether a programmer, a business analyst, or a database developer, creates ETL pipelines , either directly or indirectly. ETL is a must-have for data-driven businesses. The transition to cloud-based software services and enhanced ETL pipelines can ease data processing for businesses.

Project 52

Project AWS Kafka Healthcare 52

ProjectPro

JULY 27, 2021

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms. How does Network File System (NFS) differ from Hadoop Distributed File System (HDFS)?

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

AUGUST 29, 2023

Unlike traditional DWs, cloud data warehouses like Snowflake, BigQuery, and Redshift come pre-equipped with advanced features; learn more about the differences in our dedicated article. Both storage and compute resources can reside on-premises, in the cloud, or in a hybrid configuration, offering many design possibilities.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

JUNE 23, 2016

Hadoop job interview is a tough road to cross with many pitfalls, that can make good opportunities fall off the edge. One, often over-looked part of Hadoop job interview is - thorough preparation. Needless to say, you are confident that you are going to nail this Hadoop job interview. directly into HDFS or Hive or HBase.

Hadoop 40

Hadoop MySQL Relational Database Java 40

ProjectPro

JANUARY 19, 2022

Microsoft Azure is a modern cloud platform that offers businesses a wide range of services. These companies are migrating their data and servers from on-premises to Azure Cloud. The fundamental skills apply to any data engineer, regardless of the cloud platform. Different methods are used to store different types of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

DECEMBER 7, 2021

Modern cloud-based data pipelines are agile and elastic to automatically scale compute and storage resources. Airflow also allows you to utilize any BI tool, connect to any data warehouse, and work with unlimited data sources. Talend Open Studio (TOS) is one of the most important data pipeline tools available.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52