ProjectPro

JUNE 6, 2025

1) Build an Uber Data Analytics Dashboard This data engineering project idea revolves around analyzing Uber ride data to visualize trends and generate actionable insights. Reddit, being a vast community-driven platform, provides a rich data source for extracting valuable insights.

Data Engineer 59

Data Engineer Data Engineering Project Engineering 59

ProjectPro

JUNE 6, 2025

Big data analytics market is expected to be worth $103 billion by 2023. We know that 95% of companies cite managing unstructured data as a business problem. of companies plan to invest in big data and AI. million managers and data analysts with deep knowledge and experience in big data. While 97.2%

Big Data 45

Big Data Big Data Skills Scala Hadoop 45

ProjectPro

JUNE 6, 2025

Security and Data Privacy Big Data Developers work closely with data protection officers to implement robust security measures, encryption, and access controls to safeguard data. Analysis of Vast Data Stores Big Data Developers use data mining and analysis tools to analyze vast and diverse data stores.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

APRIL 17, 2015

This articles explores four latest trends in big data analytics that are driving implementation of cutting edge technologies like Hadoop and NoSQL. The big data analytics market in 2015 will revolve around the Internet of Things (IoT), Social media sentiment analysis, increase in sensor driven wearables, etc.

Big Data 52

Big Data Data Analysis NoSQL Deep Learning 52

ProjectPro

APRIL 14, 2015

Big data dating is the secret of success behind long lasting romance in relationships of the 21 st century. This article elaborates how online dating data is used by companies to help customers find the secret to long lasting romance through data analysis techniques. billion by 2016. It kind of snowballs from there.

Big Data 52

Big Data Data Analysis MongoDB Hadoop 52

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

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 40

Big Data Hadoop Relational Database NoSQL 40

ProjectPro

JUNE 6, 2025

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

Knowledge Hut

MAY 23, 2024

Roles: A Data Scientist is often referred to as the data architect, whereas a Full Stack Developer is responsible for building the entire stack. The main difference between these two roles is that a Data Scientist has tremendous expertise in data analysis and knows how to analyze data.

Java 98

Java Computer Science Data Science Certification 98

ProjectPro

JUNE 6, 2025

An ETL (Extract, Transform, Load) Data Engineer is responsible for designing, building, and maintaining the systems that extract data from various sources, transform it into a format suitable for data analysis, and load it into data warehouses, lakes, or other data storage systems.

Data Engineer 40

Data Engineer Data Engineering Engineering ETL Tools 40

Knowledge Hut

MAY 23, 2024

Apache Spark: Apache Spark is a well-known data science tool, framework, and data science library, with a robust analytics engine that can provide stream processing and batch processing. It can analyze data in real-time and can perform cluster management. Apart from data analysis, it can also help in machine learning projects.

Data Science 52

Data Science MongoDB Programming Language Data Mining 52

Edureka

FEBRUARY 12, 2025

Databases Facilitates storage and retrieval of structured data. Examples: SQL databases MongoDB Firebase Cloud Platforms and Infrastructure Supports deployment and scaling of applications. Information Retrieval Description : Build systems to retrieve and summarize data from large documents.

IT 52

IT Database Google Cloud Coding 52

Knowledge Hut

DECEMBER 26, 2023

Of course, handling such huge amounts of data and using them to extract data-driven insights for any business is not an easy task; and this is where Data Science comes into the picture. To make accurate conclusions based on the analysis of the data, you need to understand what that data represents in the first place.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

AltexSoft

MAY 14, 2021

It’s worth noting though that data collection commonly happens in real-time or near real-time to ensure immediate processing. Any irrelevant or flawed data needs to be removed or taken into account. Several data quality tools can detect any flaws in datasets and conduct cleansing activities on them. Data analysis.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JUNE 6, 2025

Additionally, Spark provides a wide range of high-level tools, such as Spark Streaming , MLlib for machine learning, GraphX for processing graph data sets, and Spark SQL for real-time processing of structured and unstructured data. Additionally, you will learn how to integrate Spark with Kafka and MongoDB.

Big Data Tools 40

Big Data Tools Big Data Hadoop Kafka 40

Knowledge Hut

MARCH 7, 2024

The knowledge that results from studying the data is normally available to the man who works as an analyst with big data. Data analytics tools in big data includes a variety of tools that can be used to enhance the data analysis process. You can opt for the Knowledgehut Big data analytics course.

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52

Knowledge Hut

JULY 26, 2023

They enable organizations to use data as an asset, resulting in greater operational efficiency, improved decision-making, and an edge over competitors in today's data-driven corporate world. Database applications also help in data-driven decision-making by providing data analysis and reporting tools.

Database 52

Database NoSQL MongoDB Telecommunication 52

Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Knowledge Hut

NOVEMBER 7, 2023

Applications of Cloud Computing in Big Data Analysis Companies can acquire new insights and optimize business processes by harnessing the computing power of cloud computing. Every day, enormous amounts of data are collected from business endpoints, cloud apps, and the people who engage with them.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

ProjectPro

JUNE 6, 2025

By harnessing serverless architecture, it streamlines data analysis from varied sources like Aurora, S3-stored FOREX data, and Alpha Vantage API for intraday stocks. It uses Lambda functions, Kinesis streams, and DynamoDB to process and transform data sourced from Alpha Vantage.

AWS 40

AWS Database Amazon Web Services MySQL 40

Knowledge Hut

MARCH 27, 2024

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. Apache Spark.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

AltexSoft

JUNE 26, 2023

The ultimate goal of data integration is to gather all valuable information in one place, ensuring its integrity , quality, accessibility throughout the company, and readiness for BI, statistical data analysis, or machine learning. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

JUNE 20, 2023

They transform unstructured data into scalable models for data science. Data Engineer vs Machine Learning Engineer: Responsibilities Data Engineer Responsibilities: Analyze and organize unstructured data Create data systems and pipelines. Assemble data for predictive and prescriptive modeling.

Machine Learning 52

Machine Learning Data Engineer Data Engineering Engineering 52

ProjectPro

NOVEMBER 14, 2015

These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. These Apache Spark projects are mostly into link prediction, cloud hosting, data analysis, and speech analysis. Data Integration 3.Scalability Specialized Data Analytics 7.Streaming

Hadoop 52

Hadoop Project Big Data Healthcare 52

Edureka

JANUARY 18, 2024

For those looking to start learning in 2024, here is a data science roadmap to follow. What is Data Science? Data science is the study of data to extract knowledge and insights from structured and unstructured data using scientific methods, processes, and algorithms.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop Relational Database NoSQL 52

ProjectPro

DECEMBER 7, 2021

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 52

Data Pipeline Architecture Kafka Data Lake 52

Knowledge Hut

FEBRUARY 7, 2023

A data science platform is software that includes a variety of technologies for machine learning, data science, and other advanced analytics projects. Typically, data science projects involve using an abundance of ls (eg. Centralize data resources Data Science Platforms have a unified location for all work.

Data Science 52

Data Science Google Cloud Programming Language Machine Learning 52

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

Knowledge Hut

DECEMBER 27, 2023

Many business owners and professionals are interested in harnessing the power locked in Big Data using Hadoop often pursue Big Data and Hadoop Training. What is Big Data? Big data is often denoted as three V’s: Volume, Variety and Velocity. Unleash the power of data with our immersive Data Analysis Bootcamp.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

Edureka

FEBRUARY 12, 2025

Databases Facilitates storage and retrieval of structured data. Examples: SQL databases MongoDB Firebase Cloud Platforms and Infrastructure Supports deployment and scaling of applications. Information Retrieval Description : Build systems to retrieve and summarize data from large documents.

IT 52

IT Database Google Cloud Coding 52

Databand.ai

DECEMBER 13, 2022

Currently, as the Associate Director of Platform and DevOps Engineering at MIT, he is focused on marrying the worlds of software engineering, systems automation, and data analysis. Bill was also named by ComputerWorld as one of the ten most influential people in the history of the computer profession.

Data Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 52

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

In the big data industry, Hadoop has emerged as a popular framework for processing and analyzing large datasets, with its ability to handle massive amounts of structured and unstructured data. Tools/Tech stack used: The tools and technologies used for such weblog trend analysis using Apache Hadoop are NoSql, MapReduce, and Hive.

Hadoop 40

Hadoop Project Big Data Media 40

AltexSoft

JULY 29, 2022

It relieves the MapReduce engine of scheduling tasks and decouples data processing from resource management. The most common language for data analysis is SQL but barebone Hadoop doesn’t support it. MongoDB: an NoSQL database with additional features. How YARN master-slave architecture works.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

U-Next

AUGUST 3, 2022

A high-ranking expert is known as a “Data Scientist” who works with big data and has the mathematics, economic, technical, analytic, and technological abilities necessary to cleanse, analyse and evaluate organised and unstructured data to help organisations make more informed decisions.

Retail 52

Retail Data Science Computer Science Entertainment 52