Edureka

FEBRUARY 9, 2023

Proficiency in programming languages: Knowledge of programming languages such as Python and SQL is essential for Azure Data Engineers. Familiarity with cloud-based analytics and big data tools: Experience with cloud-based analytics and big data tools such as Apache Spark, Apache Hive, and Apache Storm is highly desirable.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

NOVEMBER 17, 2023

Database Knowledge Data warehousing ideas like the star and snowflake schema, as well as how to design and develop a data warehouse, should be well understood by you. This involves knowing how to manage data partitions, load data into a data warehouse, and speed up query execution.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JANUARY 20, 2016

With widespread enterprise adoption, learning Hadoop is gaining traction as it can lead to lucrative career opportunities. There are several hurdles and pitfalls students and professionals come across while learning Hadoop. How much Java is required to learn Hadoop? How much Java is required to learn Hadoop?

Hadoop 52

Hadoop SQL Java Big Data 52

ProjectPro

APRIL 27, 2016

Scott Gnau, CTO of Hadoop distribution vendor Hortonworks said - "It doesn't matter who you are — cluster operator, security administrator, data analyst — everyone wants Hadoop and related big data technologies to be straightforward. Curious to know about these Hadoop innovations?

Hadoop 40

Hadoop Big Data Technology Big Data Tools 40

Knowledge Hut

NOVEMBER 2, 2023

The goal is to create a data pipeline that collects and analyses surf data from the Surfline API before storing it in a Postgres data warehouse. Data Aggregation Working with a sample of big data allows you to investigate real-time data processing, big data project design, and data flow.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

JUNE 23, 2023

You should be well-versed in Python and R, which are beneficial in various data-related operations. Apache Hadoop-based analytics to compute distributed processing and storage against datasets. Machine learning will link your work with data scientists, assisting them with statistical analysis and modeling. What is Data Modeling?

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Big Data Tools

OCTOBER 10, 2022

Here are some great articles and posts that can help inspire us all to learn from the experience of other people, teams, and companies who work in data engineering. This practice can be extremely helpful, and in fact, famous, industry-changing open-source tools like Hadoop have been born out of it.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Big Data Tools

OCTOBER 10, 2022

Here are some great articles and posts that can help inspire us all to learn from the experience of other people, teams, and companies who work in data engineering. This practice can be extremely helpful, and in fact, famous, industry-changing open-source tools like Hadoop have been born out of it.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

ProjectPro

JANUARY 19, 2022

Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Good communication skills as a data engineer directly works with the different teams. To do that, a data engineer is likely to be expected to learn big data tools. The list does not end here.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

SEPTEMBER 26, 2021

You shall know database creation, data manipulation, and similar operations on the data sets. Data Warehousing: Data warehouses store massive pieces of information for querying and data analysis. Your organization will use internal and external sources to port the data.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

SEPTEMBER 26, 2023

We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. ETL activities are also the responsibility of data engineers.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

SEPTEMBER 26, 2021

This blog on Big Data Engineer salary gives you a clear picture of the salary range according to skills, countries, industries, job titles, etc. Big Data gets over 1.2 Several industries across the globe are using Big Data tools and technology in their processes and operations. So, let's get started!

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

AUGUST 24, 2021

Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis. Data Analytics: A data engineer works with different teams who will leverage that data for business solutions.

Data Engineering 52

Data Engineering Data Engineer Coding Project 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.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JANUARY 31, 2023

Typically, data processing is done using frameworks such as Hadoop, Spark, MapReduce, Flink, and Pig, to mention a few. How is Hadoop related to Big Data? Explain the difference between Hadoop and RDBMS. Data Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. Processes structured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

JUNE 24, 2021

Here are a few reasons why you should work on data analytics projects: Data analytics projects for grad students can help them learn big data analytics by doing instead of just gaining theoretical knowledge. Zeppelin allows individuals or teams to engage in data visualization on a collaborative basis.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

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. Data is regularly updated.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Databand.ai

DECEMBER 13, 2022

We’d be remiss not to share that Joseph was a recent guest on Databand’s MAD Data Podcast , where he discussed ways to keep data systems from becoming unwieldy and shared tips for data teams to manage their data warehouses and keep data pipelines running reliably. You can also watch the video recording.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

AltexSoft

JUNE 26, 2023

Luckily, the situation has been gradually changing for the better with the evolution of big data tools and storage architectures capable of handling large datasets, no matter their type (we’ll discuss different types of data repositories later on.) The difference between data warehouses, lakes, and marts.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

JUNE 20, 2023

Skills A data engineer should have good programming and analytical skills with big data knowledge. Examples Pull daily tweets from the data warehouse hive spreading in multiple clusters. The ML engineers act as a bridge between software engineering and data science.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

ProjectPro

APRIL 15, 2016

Preparing for a Hadoop job interview then this list of most commonly asked Apache Pig Interview questions and answers will help you ace your hadoop job interview in 2018. Research and thorough preparation can increase your probability of making it to the next step in any Hadoop job interview.

Hadoop 40

Hadoop Java Big Data SQL 40

U-Next

SEPTEMBER 23, 2022

Traditional data processing technologies have presented numerous obstacles in analyzing and researching such massive amounts of data. To address these issues, Big Data technologies such as Hadoop were established. These Big Data tools aided in the realization of Big Data applications. .

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

ProjectPro

JANUARY 19, 2022

ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Get familiar with popular ETL tools like Xplenty, Stitch, Alooma, etc. Different methods are used to store different types of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52