Knowledge Hut

NOVEMBER 3, 2023

MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. With large amounts of unstructured data requiring storage and many popular data analysis tools working well with MongoDB, the prospects of picking it as your next database can be very enticing.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

JANUARY 19, 2024

With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. That's the promise of a career in data science.

Data Science 52

Data Science Machine Learning Datasets Algorithm 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

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 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. With the amounts of data involved, this can be crucial to utilizing a data lake effectively.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

ProjectPro

DECEMBER 7, 2021

It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

JUNE 19, 2023

Businesses use various data visualization techniques to present information from structured, semi-structured, or unstructured data collections. The amount of data is increasing every day, and organizations need better management to handle it.

Business Intelligence 52

Business Intelligence BI Programming Language Recruitment 52

ProjectPro

OCTOBER 18, 2021

Datasets like Google Local, Amazon product reviews, MovieLens, Goodreads, NES, Librarything are preferable for creating recommendation engines using machine learning models. They have a well-researched collection of data such as ratings, reviews, timestamps, price, category information, customer likes, and dislikes.

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 Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 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

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

ProjectPro

OCTOBER 15, 2014

Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data. We generally refer to Unstructured Data as “Big Data” and the framework that is used for processing Big Data is popularly known as Hadoop.

Hadoop 52

Hadoop Unstructured Data Java SQL 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. The products and services of Cloudera are changing the economics of big data analysis , BI, data processing and warehousing through Hadooponomics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

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

If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets. However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

SEPTEMBER 26, 2023

Organizations can harness the power of the cloud, easily scaling resources up or down to meet their evolving data processing demands. Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Edureka

AUGUST 2, 2023

Data processing analysts are experts in data who have a special combination of technical abilities and subject-matter expertise. They are essential to the data lifecycle because they take unstructured data and turn it into something that can be used. What does a Data Processing Analysts do ?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

ProjectPro

AUGUST 11, 2021

Data Lake vs Data Warehouse - The Differences Before we closely analyse some of the key differences between a data lake and a data warehouse, it is important to have an in depth understanding of what a data warehouse and data lake is. Data Lake vs Data Warehouse - The Introduction What is a Data warehouse?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

NOVEMBER 1, 2023

NER for structuring unstructured data NER plays a pivotal role in converting unstructured text into structured data. By doing so, NER transforms vast amounts of textual content into organized datasets, ready for further analysis. .”

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 52

ProjectPro

AUGUST 24, 2021

Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc. They are also often expected to prepare their dataset by web scraping with the help of various APIs. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

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 AWS Relational Database 52

ProjectPro

JANUARY 24, 2023

It will also cover a step-by-step Google BigQuery tutorial to help you get started with your data warehousing solutions. Google BigQuery Data Analysis Workflows Google BigQuery Architecture- A Detailed Overview Google BigQuery Datatypes BigQuery Tutorial for Beginners: How To Use BigQuery? What is Google BigQuery Used for?

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. What is Big Data analytics?

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. How HDFS master-slave structure works.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

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

AltexSoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. A powerful Big Data tool, Apache Hadoop alone is far from being almighty.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

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 Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

OCTOBER 20, 2021

Most Data Scientists know how to run python code on a Jupyter Notebook. We run the codes, do data analysis, come up with the final model result and stop there. There are multiple use-cases where companies have an in-house or hire an analytics vendor to perform analytics on a dataset and get the output.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

MARCH 15, 2016

That way every server, stores a fragment of the entire data set and all such fragments are replicated on more than one server to achieve fault tolerance. Hadoop MapReduce MapReduce is a distributed data processing framework. Apache Hadoop provides solution to the problem caused by large volume of complex data.

Hadoop 40

Hadoop Retail Healthcare Banking 40

AltexSoft

NOVEMBER 10, 2021

A data warehouse (DW) is a centralized repository for data accumulated from an array of corporate sources like CRMs, relational databases , flat files, etc. Typically used for data analysis and reporting, data warehouses rely on ETL mechanisms to extract , transform , and load data into a destination.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

NOVEMBER 11, 2014

What is Apache Spark - The User-Friendly Face of Hadoop Spark is a fast cluster computing system developed by the contributions of nearly 250 developers from 50 companies in UC Berkeley's AMP Lab to make data analytics more rapid and easier to write and run. It uses RAM for caching and data processing. DAGs have stages and steps.

Hadoop 40

Hadoop Scala Machine Learning Java 40

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

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Kicking off a big data analytics project is always the most challenging part.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

JUNE 4, 2015

In our earlier articles, we have defined “What is Apache Hadoop” To recap, Apache Hadoop is a distributed computing open source framework for storing and processing huge unstructured datasets distributed across different clusters. MapReduce breaks down a big data processing job into smaller tasks.

Hadoop 52

Hadoop Architecture IT Java 52

ProjectPro

MARCH 14, 2014

The next decade of industries will be using Big Data to solve the unsolved data problems in the physical world. Big Data analysis will be about building systems around the data that is generated. Every department of an organization including marketing, finance and HR are now getting direct access to their own data.

Hadoop 40

Hadoop Big Data Data Mining Retail 40