Remove Big Data Tools Remove Hadoop Remove Scala Remove Unstructured Data
article thumbnail

Spark vs Hive - What's the Difference

ProjectPro

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Hive , for instance, does not support sub-queries and unstructured data.

Hadoop 52
article thumbnail

Azure Data Engineer Certification Path (DP-203): 2023 Roadmap

Knowledge Hut

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. The main exam for the Azure data engineer path is DP 203 learning path.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Data Engineering Learning Path: A Complete Roadmap

Knowledge Hut

Data warehousing to aggregate unstructured data collected from multiple sources. Data architecture to tackle datasets and the relationship between processes and applications. Apache Hadoop-based analytics to compute distributed processing and storage against datasets. What is Data Modeling? What is HDFS?

article thumbnail

?Data Engineer vs Machine Learning Engineer: What to Choose?

Knowledge Hut

Languages Python, SQL, Java, Scala R, C++, Java Script, and Python Tools Kafka, Tableau, Snowflake, etc. Skills A data engineer should have good programming and analytical skills with big data knowledge. The ML engineers act as a bridge between software engineering and data science.

article thumbnail

Data Architect: Role Description, Skills, Certifications and When to Hire

AltexSoft

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.);

article thumbnail

Top Hadoop Projects and Spark Projects for Beginners 2021

ProjectPro

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
article thumbnail

Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

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.