ProjectPro

JUNE 6, 2025

Build an Awesome Job Winning Data Engineering Projects Portfoli o Technical Skills Required to Become a Big Data Engineer Database Systems: Data is the primary asset handled, processed, and managed by a Big Data Engineer. You must have good knowledge of the SQL and NoSQL database systems.

Big Data 40

Big Data Data Engineer Data Engineering Engineering 40

ProjectPro

JUNE 6, 2025

When working with real-world data, it may only sometimes be the case that the information is stored in rows and columns. In such instances, raw data is available in the form of JSON documents, key-value pairs, etc., and is accessed by data engineers with the help of NoSQL database management systems.

Data Engineer 49

Data Engineer Data Engineering Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 40

Big Data Hadoop Relational Database NoSQL 40

ProjectPro

JUNE 6, 2025

This is what data engineering does. Data engineering entails creating and developing data collection, storage, and analysis systems. Data engineers create systems that gather, analyze, and transform raw data into useful information. such as Python/R, Hadoop, AWS, Azure, SQL/NoSQL , etc.

Data Engineer 40

Data Engineer Data Engineering Recruitment Engineering 40

ProjectPro

JUNE 6, 2025

Most of us have observed that data scientist is usually labeled the hottest job of the 21st century, but is it the only most desirable job? No, that is not the only job in the data world. by ingesting raw data into a cloud storage solution like AWS S3. Use the ESPNcricinfo Ball-by-Ball Dataset to process match data.

Data Engineer 59

Data Engineer Data Engineering Project Engineering 59

Knowledge Hut

DECEMBER 26, 2023

Data Engineers are engineers responsible for uncovering trends in data sets and building algorithms and data pipelines to make raw data beneficial for the organization. This job requires a handful of skills, starting from a strong foundation of SQL and programming languages like Python , Java , etc.

Data Engineer 98

Data Engineer Data Engineering Engineering Pipeline-centric 98

ProjectPro

JUNE 6, 2025

Cristiano Breuel , Senior AI Manager at Nubank, defines the role of a data scientist in one of his articles- Data Scientist: Roles and Responsibilities Here are some of the key responsibilities of a Data Scientist- Data Wrangling and Cleaning- Collect, clean, and prepare data from various sources for analysis.

Machine Learning 40

Machine Learning Computer Science Consulting Software Engineer 40

Cloud Academy

JANUARY 27, 2022

A data engineer is an engineer who creates solutions from raw data. A data engineer develops, constructs, tests, and maintains data architectures. Let’s review some of the big picture concepts as well finer details about being a data engineer. Earlier we mentioned ETL or extract, transform, load.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Edureka

AUGUST 29, 2024

In this respect, the purpose of the blog is to explain what is a data engineer , describe their duties to know the context that uses data, and explain why the role of a data engineer is central. What Does a Data Engineer Do? Design algorithms transforming raw data into actionable information for strategic decisions.

Data Engineer 40

Data Engineer Data Engineering Engineering Generalist 40

ProjectPro

JUNE 6, 2025

Allows integration with other systems - Python is beneficial for integrating multiple scripts and other systems, including various databases (such as SQL and NoSQL databases), data formats (such as JSON, Parquet, etc.), Excels stores data points in each cell in its most basic format. Instead, they can simply import a library.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

Knowledge Hut

JUNE 20, 2023

In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. Languages Python, SQL, Java, Scala R, C++, Java Script, and Python Tools Kafka, Tableau, Snowflake, etc. The ML engineers act as a bridge between software engineering and data science.

Machine Learning 52

Machine Learning Data Engineer Data Engineering Engineering 52

ProjectPro

OCTOBER 15, 2014

Pig hadoop and Hive hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. Hive Query language (HiveQL) suits the specific demands of analytics meanwhile PIG supports huge data operation. YES, when you extend it with Java User Defined Functions.

Hadoop 52

Hadoop Java Unstructured Data SQL 52

Knowledge Hut

NOVEMBER 28, 2023

Python is ubiquitous, which you can use in the backends, streamline data processing, learn how to build effective data architectures, and maintain large data systems. Java can be used to build APIs and move them to destinations in the appropriate logistics of data landscapes.

Data Engineer 52

Data Engineer Data Engineering Engineering Generalist 52

Ascend.io

SEPTEMBER 14, 2023

Read More: Data Automation Engineer: Skills, Workflow, and Business Impact Python for Data Engineering Versus SQL, Java, and Scala When diving into the domain of data engineering, understanding the strengths and weaknesses of your chosen programming language is essential. csv') data_excel = pd.read_excel('data2.xlsx')

Data Engineer 52

Data Engineer Data Engineering Python Engineering 52

ProjectPro

SEPTEMBER 26, 2021

Build an Awesome Job Winning Data Engineering Projects Portfoli o Technical Skills Required to Become a Big Data Engineer Database Systems: Data is the primary asset handled, processed, and managed by a Big Data Engineer. You must have good knowledge of the SQL and NoSQL database systems.

Big Data 52

Big Data Data Engineer Data Engineering Engineering 52

ProjectPro

JUNE 6, 2025

Data Analyst Career Path - Analytic Skills You Must Hone The first step in data analytics involves acquiring the essential skills and expertise for the specific job role. Data analysts mainly collect raw data from various data sets or databases and perform data mining and wrangling processes.

Consulting 40

Consulting Healthcare Programming Language BI 40

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop Relational Database NoSQL 52

AltexSoft

DECEMBER 23, 2022

For example, Online Analytical Processing (OLAP) systems only allow relational data structures so the data has to be reshaped into the SQL-readable format beforehand. In ELT, raw data is loaded into the destination, and then it receives transformations when it’s needed. ELT allows them to work with the data directly.

Process 52

Process Building Data Lake Raw Data 52

Knowledge Hut

JUNE 16, 2023

Analyzing data with statistical and computational methods to conclude any information is known as data analytics. Finding patterns, trends, and insights, entails cleaning and translating raw data into a format that can be easily analyzed. Using databases efficiently is an important data analyst technical skill.

Programming Language 52

Programming Language Cloud Computing Data Analytics Data Preparation 52

Edureka

JULY 4, 2024

For example, a retail company might use EMR to process high volumes of transaction data from hundreds or thousands of different sources (point-of-sale systems, online sales platforms, and inventory databases). Arranging the raw data could composite a 360-degree view of your sales customer integration across all channels.

AWS 52

AWS Amazon Web Services Hadoop Big Data 52

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. Good skills in computer programming languages like R, Python, Java, C++, etc.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

Knowledge Hut

OCTOBER 8, 2023

You need to know the data warehousing concepts to make your job easy. You must be proficient in NoSQL and SQL for data engineers to help with database management. Data pipeline design - It's where you extract raw data from different data sources and export it for analysis.

AWS 52

AWS Data Engineer Data Engineering Engineering 52

Rockset

NOVEMBER 1, 2018

Contrast with Java and C, which are statically typed. This impedance mismatch between dynamically typed languages and SQL's static typing has driven development away from SQL databases and towards NoSQL systems. It's easier to build apps on NoSQL systems, especially early on, before the data model stabilizes.

SQL 40

SQL NoSQL Programming Language Bytes 40

ProjectPro

APRIL 27, 2016

As MapReduce can run on low cost commodity hardware-it reduces the overall cost of a computing cluster but coding MapReduce jobs is not easy and requires the users to have knowledge of Java programming. Pig Hadoop dominates the big data infrastructure at Yahoo as 60% of the processing happens through Apache Pig Scripts.

Hadoop 40

Hadoop Big Data Technology Kafka 40

Edureka

JANUARY 18, 2024

Explore real-world examples, emphasizing the importance of statistical thinking in designing experiments and drawing reliable conclusions from data. Programming A minimum of one programming language, such as Python, SQL, Scala, Java, or R, is required for the data science field.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

NOVEMBER 14, 2015

Hadoop ecosystem has a very desirable ability to blend with popular programming and scripting platforms such as SQL, Java , Python, and the like which makes migration projects easier to execute. From Data Engineering Fundamentals to full hands-on example projects , check out data engineering projects by ProjectPro 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

U-Next

SEPTEMBER 9, 2022

We are acquiring data at an astonishing pace and need Data Science to add value to this information, make it applicable to real-world situations, and make it helpful. . They gather, purge, and arrange data that can eventually be leveraged to make business growth strategies. .

Data Science 40

Data Science Computer Science Machine Learning Data Cleanse 40

ProjectPro

JULY 12, 2021

They can store large amounts of data in data processing systems and convert raw data into a usable format. After the data engineer formats data in a way that makes it easy to extract, data analysts and data scientists can easily query this data and build machine learning algorithms.

Engineering 40

Engineering Software Engineer Software Engineering Deep Learning 40

ProjectPro

JUNE 6, 2025

Data that can be stored in traditional database systems in the form of rows and columns, for example, the online purchase transactions can be referred to as Structured Data. Data that can be stored only partially in traditional database systems, for example, data in XML records can be referred to as semi-structured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

AUGUST 21, 2015

Data that can be stored in traditional database systems in the form of rows and columns, for example, the online purchase transactions can be referred to as Structured Data. Data that can be stored only partially in traditional database systems, for example, data in XML records can be referred to as semi-structured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

AltexSoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. What is Hadoop? Hadoop ecosystem evolvement.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59