Big Data Tools

OCTOBER 5, 2021

PostgreSQL 14 – Sometimes I forget, but traditional relational databases play a big role in the lives of data engineers. And of course, PostgreSQL is one of the most popular databases. Improve YARN Registry DNS Server qps – In massive Hadoop clusters, there may be a lot of DNS queries.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 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

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. Depending on the type of database a data engineer is working with, they will use specific software. The list does not end here.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. What are its limitations and how do the Hadoop ecosystem address them? scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

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

Knowledge Hut

SEPTEMBER 26, 2023

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. Relational databases, nonrelational databases, data streams, and file stores are examples of data systems.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

DECEMBER 7, 2021

Image Credit: altexsoft.com Below are some essential components of the data pipeline architecture: Source: It is a location from where the pipeline extracts raw data. Data sources may include relational databases or data from SaaS (software-as-a-service) tools like Salesforce and HubSpot.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

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

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop AWS Relational Database 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

AUGUST 11, 2021

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? Any inconsistencies found in the data are removed, and all gaps that can be filled are filled to ensure that the data maintains integrity. Recommended Reading: Is Hadoop Going To Replace Data Warehouse?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

NOVEMBER 22, 2021

Python has a large library set, which is why the vast majority of data scientists and analytics specialists use it at a high level. If you are interested in landing a big data or Data Science job, mastering PySpark as a big data tool is necessary. Is PySpark a Big Data tool?

Hadoop 52

Hadoop Python Datasets Metadata 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. NFS is not very fault tolerant.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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

ProjectPro

JANUARY 19, 2022

Here are some role-specific skills you should consider to become an Azure data engineer- Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Learning SQL is essential to comprehend the database and its structures.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JANUARY 25, 2022

When it comes to data ingestion pipelines, PySpark has a lot of advantages. PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems. PySpark SQL and Dataframes A dataframe is a shared collection of organized or semi-structured data in PySpark.

Big Data 52

Big Data Data Process Process Kafka 52

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

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