Remove Big Data Tools Remove Data Collection Remove Data Mining Remove Structured Data
article thumbnail

Top 16 Data Science Job Roles To Pursue in 2024

Knowledge Hut

The responsibilities of Data Analysts are to acquire massive amounts of data, visualize, transform, manage and process the data, and prepare data for business communications. They use tools like Microsoft Power BI or Oracle BI to develop dashboards, reports, and Key Performance Indicator (KPI) scorecards.

article thumbnail

Top 14 Big Data Analytics Tools in 2024

Knowledge Hut

You can check out the Big Data Certification Online to have an in-depth idea about big data tools and technologies to prepare for a job in the domain. To get your business in the direction you want, you need to choose the right tools for big data analysis based on your business goals, needs, and variety.

Insiders

Sign Up for our Newsletter

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

article thumbnail

A Beginner’s Guide to Learning PySpark for Big Data Processing

ProjectPro

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. Another reason to use PySpark is that it has the benefit of being able to scale to far more giant data sets compared to the Python Pandas library.

article thumbnail

20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. Big Data Tools: Without learning about popular big data tools, it is almost impossible to complete any task in data engineering. Google BigQuery receives the structured data from workers.

article thumbnail

20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

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.