ProjectPro

JUNE 6, 2025

Hadoop has become the go-to big data technology because of its power for processing large amounts of semi-structured and unstructured data. Hadoop is not popular for its processing speed in dealing with small data sets. It has a robust community support that is evolving over time with novel advancements.

Hadoop 45

Hadoop IT Big Data Retail 45

ProjectPro

JUNE 6, 2025

They include relational databases like Amazon RDS for MySQL, PostgreSQL, and Oracle and NoSQL databases like Amazon DynamoDB. Database Variety: AWS provides multiple database options such as Aurora (relational), DynamoDB (NoSQL), and ElastiCache (in-memory), letting startups choose the best-fit tech for their needs.

AWS 40

AWS Database Amazon Web Services MySQL 40

ProjectPro

JUNE 6, 2025

Hadoop can be used to carry out data processing using either the traditional (map/reduce) or Spark-based (providing an interactive platform to process queries in real-time) approach. Tools/Tech stack used: The tools and technologies used for such data pipeline management using Apache Spark are NoSQL, API, ETL, and Python.

Hadoop 40

Hadoop Project Big Data Scala 40

ProjectPro

JUNE 6, 2025

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

MAY 14, 2021

To understand Big Data, you need to get acquainted with its attributes known as the four V’s: Volume is what hides in the “big” part of Big Data. This relates to terabytes to petabytes of information coming from a range of sources such as IoT devices, social media, text files, business transactions, etc. NoSQL databases.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JUNE 6, 2025

This architecture typically consists of several layers, each serving a specific purpose in handling and processing data instantaneously- Source- Microsoft Azure Official Documentation Data Ingestion Layer At the forefront of the architecture, this layer is responsible for the initial acquisition and ingestion of data streams from diverse sources.

Data Ingestion 40

Data Ingestion Kafka Google Cloud AWS 40

Confluent

MARCH 4, 2019

Different data problems have arisen in the last two decades, and we ought to address them with the appropriate technology. We need something that can handle large amounts of data, something that can handle unstructured data coming from logs and social media, and data in their native form.

Cloud 89

Cloud Banking Kafka NoSQL 89

ProjectPro

JUNE 6, 2025

Dataset: Simulated Apple Health Data Skills Developed: Health data preprocessing and analysis Insight extraction using Amazon Redshift Visualizing activity trends with QuickSight 9) Build a Reddit Data Engineering Pipeline Extracting data from social media platforms has become essential for data analysis and decision-making.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

Knowledge Hut

APRIL 23, 2024

They also facilitate historical analysis, as they store long-term data records that can be used for trend analysis, forecasting, and decision-making. Big Data In contrast, big data encompasses the vast amounts of both structured and unstructured data that organizations generate on a daily basis.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Data Ingestion 52

ProjectPro

JUNE 6, 2025

They are used ideally for media transcoding, gaming servers, ad-server engines. These instances use their local storage to store data. They get used in NoSQL databases like Redis, MongoDB , data warehousing. Use cases for EBS are Software development and testing, NoSQL databases, organization-wide application.

Cloud Computing 53

Cloud Computing Cloud Amazon Web Services AWS 53

ProjectPro

JUNE 6, 2025

Storage Layer: This is a centralized repository where all the data loaded into the data lake is stored. HDFS is a cost-effective solution for the storage layer since it supports storage and querying of both structured and unstructured data. Insights from the system may be used to process the data in different ways.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

JUNE 6, 2025

Data Model DynamoDB is a NoSQL database, meaning it doesn't require a predefined schema and can handle unstructured data. DynamoDB is better for applications that require flexible and scalable NoSQL databases, such as gaming, IoT, and mobile applications. Select "Multiple Writers", then complete the setup.

Database 40

Database Technology Cloud PostgreSQL 40

Knowledge Hut

DECEMBER 26, 2023

Analyzing more data points will therefore give you a more detailed insight into your study. The spectrum of sources from which data is collected for the study in Data Science is broad. It comes from numerous sources ranging from surveys, social media platforms, e-commerce websites, browsing searches, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

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

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

Database 52

Database Management NoSQL Relational Database 52

Knowledge Hut

JULY 26, 2023

It also has strong querying capabilities, including a large number of operators and indexes that allow for quick data retrieval and analysis. Database Software- Other NoSQL: NoSQL databases cover a variety of database software that differs from typical relational databases.

Database 52

Database NoSQL Telecommunication MongoDB 52

ProjectPro

JUNE 6, 2025

When applied to data analysis, LLM-powered agents can process vast amounts of structured and unstructured data, extract patterns, generate meaningful insights, and forecast future trends with minimal human intervention. Databases: Querying data using SQL/ NoSQL databases.

Data Analysis 40

Data Analysis Building Raw Data Datasets 40

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

AUGUST 6, 2015

According to IDC, the amount of data will increase by 20 times - between 2010 and 2020, with 77% of the data relevant to organizations being unstructured. 81% of the organizations say that Big Data is a top 5 IT priority. 81% of the organizations say that Big Data is a top 5 IT priority.

Big Data 52

Big Data Insurance Hadoop Media 52

Knowledge Hut

NOVEMBER 7, 2023

Every day, enormous amounts of data are collected from business endpoints, cloud apps, and the people who engage with them. Cloud computing enables enterprises to access massive amounts of organized and unstructured data in order to extract commercial value. SQL, NoSQL, and Linux knowledge are required for database programming.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

U-Next

AUGUST 25, 2022

An open-spurce NoSQL database management program, MongoDB architecture, is used as an alternative to traditional RDMS. MongoDB is built to fulfil the needs of modern apps, with a technical base that allows you through: The document data model demonstrates the most effective approach to work with data. Introduction. Conclusion.

MongoDB 40

MongoDB Architecture NoSQL MySQL 40

Striim

SEPTEMBER 11, 2024

Data warehouses offer high performance and scalability, enabling organizations to manage large volumes of structured data efficiently. Data Lakes: Data lakes are designed to store structured, semi-structured, and unstructured data, providing a flexible and scalable solution.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

DECEMBER 26, 2023

Importance of Big Data Companies Big Data is intricate and can be challenging to access and manage because data often arrives quickly in ever-increasing amounts. Both structured and unstructured data may be present in this data. Splunk - Splunk is a software company that specializes in data analysis.

Big Data 52

Big Data Unstructured Data Amazon Web Services Manufacturing 52

ProjectPro

AUGUST 26, 2015

1997 -The term “BIG DATA” was used for the first time- A paper on Visualization published by David Ellsworth and Michael Cox of NASA’s Ames Research Centre mentioned about the challenges in working with large unstructured data sets with the existing computing systems. Truskowski.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

AltexSoft

NOVEMBER 23, 2021

Nowadays, all organizations need real-time data to make instant business decisions and bring value to their customers faster. But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. Identify your consumers.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

OCTOBER 28, 2015

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 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

MAY 23, 2015

Table of Contents How Walmart uses Big Data? Use market basket analysis to classify shopping trips Walmart Data Analyst Interview Questions Walmart Hadoop Interview Questions Walmart Data Scientist Interview Question American multinational retail giant Walmart collects 2.5 How Walmart is tracking its customers?

Big Data 52

Big Data Data Analysis Hadoop Retail 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

JUNE 6, 2025

Data Analysis Tools- How does Big Data Analytics Benefit Businesses? Big data is much more than just a buzzword. 95 percent of companies agree that managing unstructured data is challenging for their industry. Big data analysis tools are particularly useful in this scenario. and web services.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

Knowledge Hut

JULY 24, 2023

Future of SQL Databases: Streaming SQL The demand for data management and analysis drives the future of databases and SQL, as they are closely knotted. One of the most significant trends in the future of databases is the rise of NoSQL databases, which offer more flexibility and scalability than traditional relational databases.

Database 52

Database SQL Process NoSQL 52

ProjectPro

NOVEMBER 14, 2015

Hadoop can be used to carry out data processing using either the traditional (map/reduce) or Spark-based (providing an interactive platform to process queries in real-time) approach. Hadoop came as a rescue when the data volume coming from different sources increased exponentially.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Knowledge Hut

MAY 31, 2023

From basic data retrieval to robust CRUD operations, Node.js Top Database Project Ideas Using MongoDB MongoDB is a popular NoSQL database management system that is widely used for web-based applications. Traditional RDBMS solutions struggle when dealing with non-uniformly shaped, multi-format digital data.

Database 52

Database Coding MongoDB PostgreSQL 52

AltexSoft

NOVEMBER 10, 2021

Key data warehouse limitations: Inefficiency and high costs of traditional data warehouses in terms of continuously growing data volumes. Inability to handle unstructured data such as audio, video, text documents, and social media posts. websites, etc.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

JULY 27, 2021

TikTok – the China-based social media platform popular with teenagers – recommends accounts to follow with the help of user-centered modeling. The leading media streaming service says 80 percent of its watched content is based on algorithmic recommendations. How recommender systems work: data processing phases. Source: TikTok.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

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. Big data is often denoted as three V’s: Volume, Variety and Velocity.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

Knowledge Hut

JUNE 20, 2023

Examples Pull daily tweets from the data warehouse hive spreading in multiple clusters. Facial reorganization, social media optimization, etc. They transform unstructured data into scalable models for data science. A machine learning engineer should know deep learning, scaling on the cloud, working with APIs, etc.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

MARCH 19, 2024

RDS should be utilized with NoSQL databases like Amazon OpenSearch Service (for text and unstructured data) and DynamoDB (for low-latency/high-traffic use cases). It is the perfect fit for complex daily database requirements that are OLTP/transactional.

AWS 52

AWS Amazon Web Services Hospitality Cloud Computing 52