AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

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Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

JANUARY 31, 2023

The Big data market was worth USD 162.6 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. RDBMS stores structured data. So, let’s dive in!

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Big Data Hadoop AWS Relational Database 52

Knowledge Hut

DECEMBER 21, 2023

To establish a career in big data, you need to be knowledgeable about some concepts, Hadoop being one of them. Hadoop tools are frameworks that help to process massive amounts of data and perform computation. You can learn in detail about Hadoop tools and technologies through a Big Data and Hadoop training online course.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. How systems exchange data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

JUNE 7, 2021

Master Nodes control and coordinate two key functions of Hadoop: data storage and parallel processing of data. Worker or Slave Nodes are the majority of nodes used to store data and run computations according to instructions from a master node. Data storage options. Data access options.

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Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JANUARY 19, 2022

As a result, the role of data engineer has become increasingly important in the technology industry. Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Data infrastructure, data warehousing, data mining, data modeling, etc.,

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. And most of this data has to be handled in real-time or near real-time.

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Big Data Data Analytics IT NoSQL 78

Knowledge Hut

DECEMBER 26, 2023

You can also gain knowledge and certification on big data in detail through Big Data certification online courses. Top Big Data Books for Beginners 1. Big Data: Concepts, Technology and Architecture For data scientists, engineers, and database managers, Big Data is the best book to learn big data.

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Big Data Data Mining Business Intelligence Machine Learning 75

Rockset

DECEMBER 31, 2022

Storage of inconsistent schema items If your data objects are required to be stored in inconsistent schemas, DynamoDB can manage that. Because of Duolingo’s global usage and need for personalized data, DynamoDB is the only database that has been able to meet their needs, both in terms of data storage and DevOps.

Non-relational Database 52

Non-relational Database Healthcare Amazon Web Services NoSQL 52

AltexSoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. Data storage component in a modern data stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

AltexSoft

SEPTEMBER 23, 2021

We’ll also analyze some of the data hub products existing in the market to explore how this technology works and what it actually can do. What is Data Hub? A data hub is a central mediation point between various data sources and data consumers. A data hub serves as a gateway to dispense the required data.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 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 Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

JULY 29, 2022

The biggest star of the Big Data world, Hadoop was named after a yellow stuffed elephant that belonged to the 2-year son of computer scientist Doug Cutting. The toy became the official logo of the technology, used by the major Internet players — such as Twitter, LinkedIn, eBay, and Amazon. How data engineering works under the hood.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. These data have been accessible to us because of the advanced and latest technologies which are used in the collection of data.

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Data Engineering Data Engineer Engineering Pipeline-centric 98

Edureka

FEBRUARY 7, 2023

The main advantage of Azure Files over Azure Blobs is that it allows for folder-based data organisation and is SMB compliant, allowing for use as a file share. Storage for Azure VMs is provided by Azure Disks (Virtual Machines). 13) Examine the capabilities of Azure storage explorer. 15) What is Azure table storage, exactly?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

AltexSoft

NOVEMBER 10, 2021

Prior to the recent advances in data management technologies, there were two main types of data stores companies could make use of, namely data warehouses and data lakes. Data warehouse. Traditional data warehouse platform architecture. Data lake. Unstructured and streaming data support.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

U-Next

OCTOBER 27, 2022

Cloud computing is the term used to describe internet data storage and access. It doesn’t store any data on your computer’s hard drive and allows users to access data from faraway servers. Using Amazon RDS, you can manage relational databases.

AWS 40

AWS Amazon Web Services Cloud Computing Cloud 40

ProjectPro

NOVEMBER 15, 2021

DataFrames are used by Spark SQL to accommodate structured and semi-structured data. You can also access data through non-relational databases such as Apache Cassandra, Apache HBase, Apache Hive, and others like the Hadoop Distributed File System. However, Trino is not limited to HDFS access.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

MARCH 19, 2015

With the availability of several mobile and web applications, it is pretty common to have billions of users- who will generate a lot of unstructured data. There is a need for a database technology that can render 24/7 support to store, process and analyze this data.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

JANUARY 25, 2022

One of the most in-demand technical skills these days is analyzing large data sets, and Apache Spark and Python are two of the most widely used technologies to do this. Python is one of the most extensively used programming languages for Data Analysis, Machine Learning , and data science tasks.

Big Data 52

Big Data Data Process Process Kafka 52

AltexSoft

SEPTEMBER 10, 2021

These types define the underlying principles of integrating data. Data consolidation. Data consolidation is the classic data integration process leveraging ETL technology. The delivery style to consolidate data is common data storage we’re covering below. How data consolidation works.

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Data Integration Data Consolidation Data Warehouse BI 52

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

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Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. What makes big data analysis difficult to optimize?

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Big Data Coding Project Hadoop 52

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis.

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Hadoop Project Big Data Healthcare 52

Netflix Tech

DECEMBER 14, 2018

data access semantics that guarantee repeatable data read behavior for client applications. System Requirements Support for Structured Data The growth of NoSQL databases has broadly been accompanied with the trend of data “schemalessness” (e.g., key value stores generally allow storing any data under a key).

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Media Database Metadata Data Schemas 94

ProjectPro

NOVEMBER 22, 2021

Spark saves data in memory (RAM), making data retrieval quicker and faster when needed. Spark is a low-latency computation platform because it offers in-memory data storage and caching. PySpark SQL is a structured data library for Spark. Become a data engineer and put your skills to the test!

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Hadoop Python Datasets Metadata 52