ProjectPro

JANUARY 19, 2022

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. That needs to be done because raw data is painful to read and work with. Experience with using cloud services providing platforms like AWS/GCP/Azure.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Edureka

JUNE 1, 2023

Data Analytics tools and technologies offer opportunities and challenges for analyzing data efficiently so you can better understand customer preferences, gain a competitive advantage in the marketplace, and grow your business. What is Data Analytics?

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

ProjectPro

SEPTEMBER 26, 2021

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. You must be aware of Amazon Web Services (AWS) and the data warehousing concept to effectively store the data sets.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

FEBRUARY 8, 2023

In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses. In 2023, more than 5140 businesses worldwide have started using AWS Glue as a big data tool.

AWS 98

AWS Scala Metadata Data Lake 98

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