ProjectPro

JUNE 6, 2025

Collaboration with the Data Science Team Big Data Developers work closely with a big data engineer and a team of data scientists to implement data analytics pipelines. They translate the data science team 's algorithms and models into practical, scalable solutions that handle large-scale data.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

Build your Data Engineer Portfolio with ProjectPro! FAQs on Data Engineering Projects Top 30+ Data Engineering Project Ideas for Beginners with Source Code [2025] We recommend over 20 top data engineering project ideas with an easily understandable architectural workflow covering most industry-required data engineer skills.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

ProjectPro

JUNE 6, 2025

Hadoop and Spark is the most talked about affair in the big data world in 2016. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Why use Hadoop? Hadoop is not popular for its processing speed in dealing with small data sets.

Hadoop 45

Hadoop IT Big Data Retail 45

AltexSoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JUNE 6, 2025

Athena by Amazon is a powerful query service tool that allows its users to submit SQL statements for making sense of structured and unstructured data. It is a serverless big data analysis tool. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization What is the need for AWS Athena?

AWS 67

AWS SQL Big Data Raw Data 67

ProjectPro

JUNE 6, 2025

To excel in this dynamic field, data scientists must possess specific skills that align with AWS technologies. Here are the top five AWS data scientist skills that are crucial for success in the realm of cloud-based data analytics. Highlight your expertise in data science, AWS services, and cloud computing.

AWS 40

AWS Amazon Web Services Cloud Computing Machine Learning 40

ProjectPro

JUNE 6, 2025

Becoming a Big Data Engineer - The Next Steps Big Data Engineer - The Market Demand An organization’s data science capabilities require data warehousing and mining, modeling, data infrastructure, and metadata management. Most of these are performed by Data Engineers.

Big Data 40

Big Data Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

In our earlier articles we have discussed a lot about what is big data and several use cases around how it is changing the way various industries operate. Big data analytics is an exploding practice today as companies devote most of their budget and time to harness and understand the power of big data around them.

Big Data 40

Big Data Retail Banking Pharmaceutical 40

ProjectPro

JUNE 6, 2025

Big data companies are closely watching the latest trends in big data analytics to gain competitive advantage with the use of data. Businesses are wading into the big data trends as they do not want to take the risk of being left behind. IDC also forecasts that Big Data Analytics market will outpour from $3.2

Big Data 40

Big Data Data Analysis NoSQL Deep Learning 40

ProjectPro

JUNE 6, 2025

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

ETL Tools 40

ETL Tools Hadoop Relational Database Unstructured Data 40

ProjectPro

JUNE 6, 2025

.” said the McKinsey Global Institute (MGI) in its executive overview of last month's report: "The Age of Analytics: Competing in a Data-Driven World." 2016 was an exciting year for big data with organizations developing real-world solutions with big data analytics making a major impact on their bottom line.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

JUNE 6, 2025

Uses statistical and computational methods to analyze and interpret data. Works with structured and unstructured data, including text and image data. Machine Learning: Data scientists should have a solid understanding of machine learning concepts and techniques, such as regression, classification, and clustering.

Business Analyst 40

Business Analyst Portfolio Data Mining Programming Language 40

ProjectPro

JUNE 6, 2025

It is difficult to stay up-to-date with the latest developments in IT industry especially in a fast growing area like big data where new big data companies, products and services pop up daily. With the explosion of Big Data, Big data analytics companies are rising above the rest to dominate the market.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

ProjectPro

JULY 13, 2015

Large commercial banks like JPMorgan have millions of customers but can now operate effectively-thanks to big data analytics leveraged on increasing number of unstructured and structured data sets using the open source framework - Hadoop. JP Morgan has massive amounts of data on what its customers spend and earn.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

JUNE 6, 2025

Top 10+ Tools For Data Engineers Worth Exploring in 2025 Let us look at the some of the best data engineering tools you should not miss exploring in 2022- 1. Apache Spark Apache Spark is an open-source data analytics engine with a customer base of over 52K organizations , including top companies like Apple, Microsoft, IBM, etc.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

ProjectPro

JUNE 6, 2025

Their role involves data extraction from multiple databases, APIs, and third-party platforms, transforming it to ensure data quality, integrity, and consistency, and then loading it into centralized data storage systems. Certifications and specialized skills are key drivers of salary growth.

Data Engineering 40

Data Engineering Data Engineer Engineering ETL Tools 40

ProjectPro

JUNE 6, 2025

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 2- Internal Data transformation at LakeHouse.

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

ProjectPro

JUNE 6, 2025

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies.

NoSQL 40

NoSQL Database Hadoop Big Data 40

ProjectPro

JUNE 6, 2025

Also, you will find some interesting data engineer interview questions that have been asked in different companies (like Facebook, Amazon, Walmart, etc.) that leverage big data analytics and tools. Preparing for data engineer interviews makes even the bravest of us anxious. Structured data usually consists of only text.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

The global data analytics market is expected to reach 68.09 Businesses are finding new methods to benefit from data. Data engineering entails building data pipelines for ingesting, modifying, supplying, and sharing data for analysis. Table of Contents ETL vs ELT for Data Engineers What is ETL?

Data Engineer 40

Data Engineer Data Engineering Engineering Data Lake 40

ProjectPro

JUNE 6, 2025

This program enables you to use Python programming and Linux/UNIX shell scripts for ETL data processes, explore Relational Databases using SQL queries, and manage NoSQL data models, databases, and unstructured data.

Data Engineering 45

Data Engineering Data Engineer Cloud Engineering 45

ProjectPro

JUNE 6, 2025

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. Get ready to expand your knowledge and take your big data career to the next level! “Data analytics is the future, and the future is NOW!

Big Data 40

Big Data Hadoop Relational Database AWS 40

ProjectPro

JUNE 6, 2025

Since vast amounts of data is present in a data lake, it is ideal for tracking analytical performance and data integration. Data in data lakes may be accessed using SQL, Python, R, Spark or other data querying tools. It allows users access to data before it is transformed and cleansed.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

JUNE 6, 2025

Additionally, columnar storage allows BigQuery to compress data more effectively, which helps to reduce storage costs. BigQuery enables users to store data in tables, allowing them to quickly and easily access their data. It supports structured and unstructured data, allowing users to work with various formats.

Bytes 40

Bytes Google Cloud Data Warehouse Cloud Storage 40

ProjectPro

JUNE 6, 2025

Predictive modeling is a statistical approach that analyzes data patterns to determine future events or outcomes. It's an essential aspect of predictive analytics, a type of data analytics that involves machine learning and data mining approaches to predict activity, behavior, and trends using current and past data.

Data Mining 45

Data Mining Banking Retail Healthcare 45

ProjectPro

JUNE 6, 2025

Businesses are estimated to have invested $215 billion in the last few years in building big data and business analytics solutions. This has led to a huge demand for big data analytics professionals across organizations worldwide. Data Integration and ETL Tools ETL is necessary for data modeling and vice versa.

NoSQL 40

NoSQL ETL Tools Certification SQL 40

ProjectPro

JUNE 6, 2025

Key Components of Batch Data Pipeline Architecture The batch data pipeline architecture consists of several key components and follows the below typical batch data pipeline workflow across systems - Data Source- This is where your data originates.

Data Pipeline 40

Data Pipeline Building Retail Data Ingestion 40

Knowledge Hut

JUNE 26, 2023

Best Data Science certifications online or offline are available to assist you in establishing a solid foundation for every end-to-end data engineering project. What are Data Engineering Projects? You should be able to identify potential weak spots in data pipelines and construct robust solutions to withstand them.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

ProjectPro

JUNE 6, 2025

Explore the world of data analytics with the top AWS databases! Check out this blog to discover your ideal database and uncover the power of scalable and efficient solutions for all your data analytical requirements. Their schema-less nature simplifies storage but requires careful data modeling for effective querying.

AWS 40

AWS Database Amazon Web Services MySQL 40

ProjectPro

JUNE 6, 2025

Its global read capabilities ensure data can be accessed with low latency from various geographic regions, providing a consistent and optimized user experience globally. Let ProjectPro be your guide to hands-on experience, enhancing your skills and portfolio. What is DocumentDB used for? Which is better: DynamoDB or DocumentDB?

AWS 40

AWS Database MongoDB Management 40

Cloudera

AUGUST 20, 2021

Legal and Regulatory Requirements: CDP delivers data products to address complex and continuously evolving legal and regulatory requirements by offering a programmatic way to dynamically manage data permissions at a granular level by type of data asset and for different roles / users interacting with and manipulating those data assets. .

Data Warehouse 98

Data Warehouse Data Cloud Architecture 98

ProjectPro

JUNE 6, 2025

Big data analytics - Big data and Cloud technologies go hand in hand and essentially make systems faster, scalable, failsafe, high-performance, and cheaper. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization 18.

Cloud Computing 53

Cloud Computing Cloud Amazon Web Services AWS 53

ProjectPro

MARCH 17, 2014

However, while you might be familiar with what is big data and hadoop, there is high probability that other people around you are not really sure on –What is big data, what hadoop is, what big data analytics is or why it is important. Table of Contents What is Big Data and what is the Big Deal?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

Monte Carlo

OCTOBER 10, 2024

Let’s dive into the responsibilities, skills, challenges, and potential career paths for an AI Data Quality Analyst today. Table of Contents What Does an AI Data Quality Analyst Do? Data Wrangling Tools : OpenRefine, Pandas. Cloud Platforms : AWS, Google Cloud, Microsoft Azure.

Unstructured Data 52

Unstructured Data Google Cloud ETL Tools Machine Learning 52

ProjectPro

JUNE 6, 2025

This rapid expansion is fueled by the increasing reliance on data-driven decision-making across industries, from tech giants to traditional retail, finance, and manufacturing sectors. Complexity of Data Problems One of the greatest challenges that data scientists face is dealing with messy, unstructured data.

Data Science 40

Data Science Machine Learning BI Certification 40

Knowledge Hut

DECEMBER 13, 2023

The big data industry is growing rapidly. Based on the exploding interest in the competitive edge provided by Big Data analytics, the market for big data is expanding dramatically. Big Data startups compete for market share with the blue-chip giants that dominate the business intelligence software market.

Big Data 52

Big Data Consulting Amazon Web Services Hadoop 52

ProjectPro

JUNE 6, 2025

Domain Algorithms Domain algorithms in AIOps intelligently comprehend rules and patterns extracted from data sources. Dive into topics such as data collection, aggregation, data analysis , and data visualization. Artificial intelligence (AI) AI is integral to AIOps, enabling automation and optimization of IT operations.

Machine Learning 40

Machine Learning Algorithm Big Data Utilities 40