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

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

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

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

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

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

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 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

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 Project 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

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

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

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 Machine Learning NoSQL 40

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

APRIL 3, 2023

Below are some of the most important concepts/topics that one must learn: Databases Databases are collections of organized data stored on a computer system. There are several types of databases, including relational, NoSQL, object-oriented, hierarchical, network, and graph databases.

Programming Language 52

Programming Language Computer Science Portfolio Java 52

ProjectPro

MAY 19, 2015

5 Reasons to Learn Hadoop ​ Hadoop brings in better career opportunities in 2015 Learn Hadoop to pace up with the exponentially growing Big Data Market Increased Number of Hadoop Jobs Learn Hadoop to Make Big Money with Big Data Hadoop Jobs Learn Hadoop to pace up with the increased adoption of Hadoop by Big data companies Why learn Hadoop?

Hadoop 40

Hadoop Big Data NoSQL Database-centric 40

ProjectPro

JUNE 6, 2015

“Solocal is a company that Yellow Media had always admired in terms of their ability to grow their online audiences.”-said But now Solocal is looking to improve the maturity of Data Architecture in the company. This gives a lot of possibilities to analyse data.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

Knowledge Hut

MARCH 27, 2024

MongoDB This free, open-source platform, which came into the limelight in 2010, is a document-oriented (NoSQL) database that is used to store a large amount of information in a structured manner. The first is the type of data you have, which will determine the tool you need. Features: Users can choose the language they wish to run in.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

MARCH 23, 2016

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 40

Hadoop IT Big Data Portfolio 40

ProjectPro

JUNE 2, 2015

It is difficult to make sense out of billions of unstructured data points (in the form of news articles, forum comments, and social media data) without powerful technologies like Hadoop, Spark and NoSQL in place.

Big Data 40

Big Data Hadoop Banking Data Analytics 40

ProjectPro

JULY 27, 2021

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

ProjectPro

AUGUST 11, 2021

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 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

JULY 30, 2021

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. Amazon S3 stores large data sets, but EBS is the block storage unit for the EC2 instances, like hard drives for PCs.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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

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 Hadoop Insurance Media 52

Knowledge Hut

DECEMBER 26, 2023

Some of these ideas consist of: Big data technology and technologists deal with a number of similar problems, such as data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns. Relational and non-relational databases, such as RDBMS, NoSQL, and NewSQL databases.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75