ProjectPro

JUNE 6, 2025

According to the 8,786 data professionals participating in Stack Overflow's survey, SQL is the most commonly-used language in data science. Despite the buzz surrounding NoSQL , Hadoop , and other big data technologies, SQL remains the most dominant language for data operations among all tech companies.

Data Engineer 45

Data Engineer Data Engineering SQL Engineering 45

ProjectPro

JUNE 6, 2025

A good place to start would be to try the Snowflake Real Time Data Warehouse Project for Beginners from the ProjectPro repository. Worried about finding good Hadoop projects with Source Code ? ProjectPro has solved end-to-end Hadoop projects to help you kickstart your Big Data career.

Data Engineer 49

Data Engineer Data Engineering Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

Worried about finding good Hadoop projects with Source Code ? ProjectPro has solved end-to-end Hadoop projects to help you kickstart your Big Data career. The bronze layer has raw data from Kafka, and the raw data is filtered to remove Personal Identifiable Information(PII) columns and loaded into the silver layer.

Data Lake 63

Data Lake Data Warehouse Metadata Unstructured Data 63

ProjectPro

JUNE 6, 2025

Lambda comes in handy when collecting the raw data is essential. Data engineers can develop a Lambda function to access an API endpoint, obtain the result, process the data, and save it to S3 or DynamoDB.

AWS 52

AWS Data Engineer Data Engineering Project 52

Teradata

MAY 30, 2025

Setting up the dbt project dbt (data build tool) allows you to transform your data by writing, documenting, and executing SQL workflows. The sample dbt project included converts raw data from an app database into a dimensional model, preparing customer and purchase data for analytics. dbt-core dagster==1.7.9

Data Integration 52

Data Integration Raw Data Metadata Data Pipeline 52

ProjectPro

JUNE 6, 2025

If you are willing to gain hands-on experience with Google BigQuery , you must explore the GCP Project to Learn using BigQuery for Exploring Data. Google Cloud Dataproc Dataproc is a fully-managed and scalable Spark and Hadoop Service that supports batch processing, querying, streaming, and machine learning.

Data Engineer 40

Data Engineer Data Engineering Engineering Google Cloud 40

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

We will now describe the difference between these three different career titles, so you get a better understanding of them: Data Engineer A data engineer is a person who builds architecture for data storage. They can store large amounts of data in data processing systems and convert raw data into a usable format.

Engineering 75

Engineering Software Engineer Software Engineering Deep Learning 75

Rockset

NOVEMBER 1, 2018

Over a decade after the inception of the Hadoop project, the amount of unstructured data available to modern applications continues to increase. This longevity is a testament to the community of analysts and data practitioners who are familiar with SQL as well as the mature ecosystem of tools around the language.

Raw Data 40

Raw Data SQL Unstructured Data NoSQL 40

ProjectPro

JUNE 6, 2025

If someone is looking to master the art and science of constructing batch pipelines, ProjectPro has got you covered with this comprehensive tutorial that will help you learn how to build your first batch data pipeline and transform raw data into actionable insights. Data Storage- Processed data needs a destination for storage.

Data Pipeline 40

Data Pipeline Building Retail Data Ingestion 40

ProjectPro

JUNE 6, 2025

Features of Apache Spark Allows Real-Time Stream Processing- Spark can handle and analyze data stored in Hadoop clusters and change data in real time using Spark Streaming. Faster and Mor Efficient processing- Spark apps can run up to 100 times faster in memory and ten times faster in Hadoop clusters.

Data Engineer 45

Data Engineer Data Engineering Engineering Kafka 45

ProjectPro

JUNE 6, 2025

Similarly, companies with vast reserves of datasets and planning to leverage them must figure out how they will retrieve that data from the reserves. A data engineer a technical job role that falls under the umbrella of jobs related to big data. You will work with unstructured data and NoSQL relational databases.

Data Engineer 58

Data Engineer Data Engineering Engineering Amazon Web Services 58

ProjectPro

JUNE 6, 2025

They often deal with big data (structured, unstructured, and semi-structured) to generate reports to identify patterns, gain valuable insights, and produce visualizations easily deciphered by stakeholders and non-technical business users. They transform enormous amounts of raw data into valuable insights.

Data Science 56

Data Science Data Mining Data Architect BI 56

ProjectPro

JUNE 6, 2025

As a Big Data Engineer, you shall also know and understand the Big Data architecture and Big Data tools. Hadoop , Kafka , and Spark are the most popular big data tools used in the industry today. You will get to learn about data storage and management with lessons on Big Data tools.

Big Data 40

Big Data Data Engineer Data Engineering Engineering 40

ProjectPro

JUNE 6, 2025

Preparing for a Hadoop job interview then this list of most commonly asked Apache Pig Interview questions and answers will help you ace your hadoop job interview in 2018. Research and thorough preparation can increase your probability of making it to the next step in any Hadoop job interview.

Hadoop 40

Hadoop Java SQL Big Data 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. Here's a data engineer resume sample showing certifications- 7.

Data Engineer 40

Data Engineer Data Engineering Recruitment Building 40

Ripple Engineering

JULY 9, 2024

We recently embarked on a significant data platform migration, transitioning from Hadoop to Databricks, a move motivated by our relentless pursuit of excellence and our contributions to the XRP Ledger's (XRPL) data analytics. This vital information then streams to the XRPL Data Extractor App.

Hadoop 96

Hadoop Data Lake Machine Learning Raw Data 96

ProjectPro

JANUARY 20, 2016

With widespread enterprise adoption, learning Hadoop is gaining traction as it can lead to lucrative career opportunities. There are several hurdles and pitfalls students and professionals come across while learning Hadoop. How much Java is required to learn Hadoop? How much Java is required to learn Hadoop?

Hadoop 52

Hadoop SQL Java BI 52

ProjectPro

JUNE 6, 2025

Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives. While data warehouses contain transformed data, data lakes contain unfiltered and unorganized raw data.

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

ProjectPro

JUNE 6, 2025

Source Code: Build a Similar Image Finder Top 3 Open Source Big Data Tools This section consists of three leading open-source big data tools- Apache Spark , Apache Hadoop, and Apache Kafka. In Hadoop clusters , Spark apps can operate up to 10 times faster on disk. Hadoop, created by Doug Cutting and Michael J.

Big Data Tools 40

Big Data Tools Big Data Hadoop Kafka 40

ProjectPro

JUNE 6, 2025

ELT involves three core stages- Extract- Importing data from the source server is the initial stage in this process. Load- The pipeline copies data from the source into the destination system, which could be a data warehouse or a data lake. Scalability ELT can be highly adaptable when using raw data.

Data Engineer 40

Data Engineer Data Engineering Engineering Data Lake 40

ProjectPro

JUNE 6, 2025

Emily is an experienced big data professional in a multinational corporation. As she deals with vast amounts of data from multiple sources, Emily seeks a solution to transform this raw data into valuable insights. dbt and Snowflake: Building the Future of Data Engineering Together."

Pipeline-centric 40

Pipeline-centric Database-centric Raw Data Data Warehouse 40

ProjectPro

JUNE 6, 2025

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? Upsolver has tools for automatically preparing the data for consumption in Athena, including compression, compaction partitioning and managing and creating tables in the AWS Glue Data Catalog.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

JUNE 6, 2025

Data engineers and data scientists work very closely together, but there are some differences in their roles and responsibilities. Data Engineer Data scientist The primary role is to design and implement highly maintainable database management systems. A data warehouse can contain unstructured data too.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

Python 3: An experience of working with Python will help build data pipelines with Airflow because we will be defining our workflows in Python code. The Data Cleaning Pipeline Let's assume we have clients sending hotel booking demand data from multiple data sources to a scalable storage solution.

Data Pipeline 45

Data Pipeline Building Data Lake Raw Data 45

ProjectPro

JUNE 6, 2025

Think of the data integration process as building a giant library where all your data's scattered notebooks are organized into chapters. You define clear paths for data to flow, from extraction (gathering structured/unstructured data from different systems) to transformation (cleaning the raw data, processing the data, etc.)

Data Integration 40

Data Integration Project Data Lake Hospitality 40

ProjectPro

JUNE 6, 2025

ETL Architecture on AWS: Examining the Scalable Architecture for Data Transformation ETL Architecture on AWS typically consists of three components - Source Data Store A Data Transformation Layer Target Data Store Source Data Store The source data store is where raw data is stored before being transformed and loaded into the target data store.

AWS 40

AWS Data Management ETL Tools Management 40

ProjectPro

OCTOBER 15, 2014

Pig and Hive are the two key components of the Hadoop ecosystem. What does pig hadoop or hive hadoop solve? Pig hadoop and Hive hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. Apache HIVE and Apache PIG components of the Hadoop ecosystem are briefed.

Hadoop 52

Hadoop Java Unstructured Data SQL 52

ProjectPro

JUNE 6, 2025

To extract data, you typically need to set up an API connection (an interface to get the data from its sources), transform it, clean it up, convert it to another format, map similar records to one another, validate the data, and then put it into a database (e.g. Let us understand how a simple ETL pipeline works.

Data Science 40

Data Science Data Engineer Data Engineering Engineering 40

Knowledge Hut

DECEMBER 26, 2023

Businesses benefit at large with these data collection and analysis as they allow organizations to make predictions and give insights about products so that they can make informed decisions, backed by inferences from existing data, which, in turn, helps in huge profit returns to such businesses. What is the role of a Data Engineer?

Data Engineer 98

Data Engineer Data Engineering Engineering Pipeline-centric 98

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. Data Migration 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

JUNE 6, 2025

Excels stores data points in each cell in its most basic format. Any numerical data, such as sales data, are input into a spreadsheet for better visibility and management. The raw data will be arranged in an accessible manner by a successful Excel spreadsheet, making it simpler to get actionable insights.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

ProjectPro

JUNE 6, 2025

Apache Hadoop , with its MapReduce framework , is commonly used for batch processing to break down tasks and process data across distributed nodes. Since batch processing is typically run in well-defined, scheduled intervals, it benefits from distributed computing models like those used in Hadoop and Apache Spark.

Process 40

Process Kafka Hadoop Banking 40

Knowledge Hut

DECEMBER 22, 2023

They can categorize and cluster raw data using algorithms, spot hidden patterns and connections in it, and continually learn and improve over time. Hadoop Gigabytes to petabytes of data may be stored and processed effectively using the open-source framework known as Apache Hadoop.

Hadoop 98

Hadoop Deep Learning Machine Learning Data Science 98

ProjectPro

JUNE 6, 2025

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

The Pragmatic Engineer

JUNE 13, 2023

The company’s largest data cluster is 20-30PB (petabytes: 1PB is 1,000 terabytes or 1M gigabytes). Ten years ago, this data cluster was 300GB as a Hadoop cluster; that’s around a 100,000-fold increase in data stored! The company runs 4 data centers: in the US and Europe, with two in Asia.

Cloud 242

Cloud Database Utilities BI 242

ProjectPro

JUNE 6, 2025

Name a few data warehouse solutions currently being used in the industry. The popular data warehouse solutions are listed below: Amazon RedShift Google BigQuery Snowflake Microsoft Azure Apache Hadoop Teradata Oracle Exadata What is the difference between OLTP and OLAP? The majority of the user's effort is inputting raw data.

Data Warehouse 40

Data Warehouse Data Mining Recruitment ETL Tools 40