ProjectPro

FEBRUARY 16, 2023

Input Data Structured data from various sources, such as databases, spreadsheets, and ERP systems. Structured, semi-structured, and unstructured data from multiple sources, such as social media, IoT devices, and sensors. Tools OLAP, data visualization, reporting, and dashboards.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 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 1- Automating the Lakehouse's data intake.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Data Engineering Podcast

JUNE 17, 2021

Summary Working with unstructured data has typically been a motivation for a data lake. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable.

Unstructured Data 100

Unstructured Data Data Warehouse Metadata Media 100

Knowledge Hut

JULY 26, 2023

This velocity aspect is particularly relevant in applications such as social media analytics, financial trading, and sensor data processing. Variety: Variety represents the diverse range of data types and formats encountered in Big Data. Handling this variety of data requires flexible data storage and processing methods.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Zalando Engineering

NOVEMBER 6, 2017

Fashion Content Platform - Finalists for SME Award In the age of vast amounts of fashion data, fashion blogs and social media influencers, predicting trends is a hard problem. Traditionally, fashion purchasing and trendspotting was done with manual research; offline at shows but also online with blogs and social media.

Data Science 40

Data Science Deep Learning Media Unstructured Data 40

Knowledge Hut

MAY 31, 2023

Companies utilize different approaches to deal with data in order to extract information from structured, semi-structured, or unstructured data sets. Business Intelligence is one such approach that helps professionals to extract valuable information from structured data.

Business Intelligence 52

Business Intelligence BI Business Analyst Consulting 52

ProjectPro

NOVEMBER 17, 2021

Sentiment analysis or opinion mining helps researchers and companies extract insights from user-generated social media and web content. Companies analyze customers’ sentiment through social media conversations and reviews so they can make better-informed decisions. For example, is a crisis on social media escalating?

Coding 52

Coding Project Entertainment Datasets 52

ProjectPro

OCTOBER 18, 2021

Recommendation engines are popular in media, entertainment, and shopping. This type of application is beneficial in searching, mobile application development, and social media apps. AI-driven Sentiment Analyzer Social media is swinging with millions of user-generated posts and content. also have the same feature.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

AUGUST 6, 2015

Companies like Electronic Arts, Riot Games are using big data for keeping a track of game play which helps predict performance of the play by analysing 4TB of operational logs and 500GB of structured data. Sports brands like ESPN have also got on to the big data bandwagon.

Big Data 52

Big Data Hadoop Insurance Media 52

ProjectPro

MARCH 17, 2021

Deep learning models usually perform Classification tasks directly from sound, text, or images (unstructured data). Data is the governor when it comes to deciding on choosing between deep learning and machine learning. Let’s consider the same example of classifying Apples and Oranges that we discussed for machine learning.

Deep Learning 52

Deep Learning Machine Learning Algorithm Datasets 52

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 We know that data warehouse is very big and a very complicated tool to maintain and to meet Big Data problems. In BI we just consider structured data.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 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

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

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

ProjectPro

SEPTEMBER 26, 2014

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services. Big data, multi-structured data, and advanced analytics.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

Precisely

SEPTEMBER 6, 2023

Similar laws in other jurisdictions are raising the stakes for enterprises, compelling them to govern their data more effectively than they have in the past. Traditional frameworks for data governance often work well for smaller volumes of data, and for highly structured data.

Data Governance 52

Data Governance Big Data Government Unstructured Data 52

ProjectPro

MAY 20, 2015

Several big data companies are looking to tame the zettabyte’s of BIG big data with analytics solutions that will help their customers turn it all in meaningful insights. Palantir Metropolis- This product focusses on information management, data integration and quantitative analytics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. This information is gathered from a variety of sources, including sensor readings, social media engagements, and client transactions. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

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.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

APRIL 25, 2024

Variety: Unstructured data, semi-structured data, and raw data are only a few examples of the variety of data kinds that exist.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 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

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

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 NoSQL Management Relational Database 52

Knowledge Hut

MARCH 27, 2024

Factors Considered for Selecting the Best Big Data Analytics Tools There are a few factors to consider when selecting the best big data analytics tool for your organization. The first is the type of data you have, which will determine the tool you need. The tools should be able to process data in real-time or near-real-time.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Cloudera

NOVEMBER 25, 2020

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

Data Warehouse 57

Data Warehouse Unstructured Data Medical Pharmaceutical 57

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

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., The complexity of the big data system increases with each data source.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

NOVEMBER 1, 2023

A corpus can range from a set of news articles to academic journals or even social media posts. NER for structuring unstructured data NER plays a pivotal role in converting unstructured text into structured data. This is a collection of texts used for linguistic analysis and training NER models.

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 52

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.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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

AltexSoft

NOVEMBER 10, 2021

Purpose-built, data warehouses allow for making complex queries on structured data via SQL (Structured Query Language) and getting results fast for business intelligence. Traditional data warehouse platform architecture. Another type of data storage — a data lake — tried to address these and other issues.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Cloudera

OCTOBER 30, 2018

Structured data from operational data stores now provides a small slice of the overall data needed to improve customer experience. IT departments previously invested in MDM and data warehousing technologies to consolidate information associated with customer profiles. Source: 451 Research.

Unstructured Data 42

Unstructured Data Data Lake Algorithm Machine Learning 42

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