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

Knowledge Hut

DECEMBER 22, 2023

Linear Algebra Linear Algebra is a mathematical subject that is very useful in data science and machine learning. A dataset is frequently represented as a matrix. Statistics Statistics are at the heart of complex machine learning algorithms in data science, identifying and converting data patterns into actionable evidence.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

Towards Data Science

OCTOBER 7, 2023

Given LLMs’ capacity to understand and extract insights from unstructured data, businesses are finding value in summarizing, analyzing, searching, and surfacing insights from large amounts of internal information. Let’s explore how a few key sectors are putting gen AI to use.

Unstructured Data 98

Unstructured Data Finance SQL Database 98

Striim

SEPTEMBER 11, 2024

Striim, for instance, facilitates the seamless integration of real-time streaming data from various sources, ensuring that it is continuously captured and delivered to big data storage targets. Data storage Data storage follows.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Sync Computing

JANUARY 27, 2025

For example, when processing a large dataset, you can add more EC2 worker nodes to speed up the task. Amazon S3 : Highly scalable, durable object storage designed for storing backups, data lakes, logs, and static content. Data is accessed over the network and is persistent, making it ideal for unstructured data storage.

AWS 52

AWS Data Lake Big Data Machine Learning 52

Knowledge Hut

JUNE 26, 2023

From analysts to Big Data Engineers, everyone in the field of data science has been discussing data engineering. When constructing a data engineering project, you should prioritize the following areas: Multiple sources of data (APIs, websites, CSVs, JSON, etc.)

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

ProjectPro

FEBRUARY 8, 2023

Smooth Integration with other AWS tools AWS Glue is relatively simple to integrate with data sources and targets like Amazon Kinesis, Amazon Redshift, Amazon S3, and Amazon MSK. It is also compatible with other popular data storage that may be deployed on Amazon EC2 instances.

AWS 98

AWS Scala Metadata Data Lake 98

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. What is Big Data analytics? Big Data analytics processes and tools.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Data lakehouse architecture is an increasingly popular choice for many businesses because it supports interoperability between data lake formats.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Data lakehouse architecture is an increasingly popular choice for many businesses because it supports interoperability between data lake formats.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Knowledge Hut

APRIL 23, 2024

View A broader view of data Narrower view of data Data Data is gleaned from diverse sources. Results Broader and exploratory results Targeted results Big Data vs Data Mining Here is a more detailed illustration of the difference between big data and data mining:- 1.

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

Knowledge Hut

APRIL 23, 2024

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Big data offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

DECEMBER 26, 2023

According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. These skills are essential to collect, clean, analyze, process and manage large amounts of data to find trends and patterns in the dataset.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

ProjectPro

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

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 Hadoop 98

Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Monte Carlo

MAY 28, 2024

Ensuring all relevant data inputs are accounted for is crucial for a comprehensive ingestion process. Data Extraction : Begin extraction using methods such as API calls or SQL queries. Batch processing gathers large datasets at scheduled intervals, ideal for operations like end-of-day reports.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Monte Carlo

OCTOBER 4, 2023

Given LLMs’ capacity to understand and extract insights from unstructured data, businesses are finding value in summarizing, analyzing, searching, and surfacing insights from large amounts of internal information. Let’s explore how a few key sectors are putting gen AI to use.

Unstructured Data 72

Unstructured Data Finance SQL Database 72

ProjectPro

JULY 3, 2015

The maximum value of big data can be extracted by integrating the in-memory processing capabilities of SAP HANA (High Performance Analytic Appliance) and the ability of Hadoop to store large unstructured datasets. “With Big Data, you’re getting into streaming data and Hadoop. .

Hadoop 40

Hadoop Big Data Data Solutions Unstructured Data 40

Data Engineering Weekly

MARCH 3, 2024

This approach enables deeper insights into complex datasets that LLMs have not been trained on, demonstrating substantial improvements in data understanding and thematic discovery. link] Nvidia: What Is Sovereign AI?

Data Engineering 67

Data Engineering Data Engineer Engineering Pipeline-centric 67

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 Relational Database AWS 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. Find sources of relevant data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

FEBRUARY 25, 2025

ELT (Extract, Load, Transform) ELT flips the orderstoring raw data first and applying transformations later. Cloud data warehouses like Snowflake , BigQuery , and Redshift have made ELT the go-to choice for massive, messy datasets since they offer scalable compute for on-the-fly transformations. Which One Should You Choose?

Designing 52

Designing Data Engineering Data Engineer Engineering 52

ProjectPro

MARCH 19, 2015

RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data. As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT

NoSQL 49

NoSQL Big Data SQL Database-centric 49

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Notice how Snowflake dutifully avoids (what may be a false) dichotomy by simply calling themselves a “data cloud.” With strong G2 scores (4.7

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

SEPTEMBER 9, 2021

The datasets are usually present in Hadoop Distributed File Systems and other databases integrated with the platform. Hive is built on top of Hadoop and provides the measures to read, write, and manage the data. Apache Hive Architecture Apache Hive has a simple architecture with a Hive interface, and it uses HDFS for data storage.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Rockset

JULY 29, 2022

For query processing, BigQuery charges $5 per TB of data processed by each query, with the first TB of data per month free. For storage, BigQuery offers up to 10GB of free data storage per month and $0.02 per additional GB of active storage, making it very economical for storing large amounts of historical data.

Data Analytics 52

Data Analytics Data Warehouse Datasets Cloud 52

Precisely

FEBRUARY 9, 2024

Organizations must focus on breaking down silos and integrating all relevant, critical data into on-premises or cloud storage for AI model training and inference. These more complete datasets will both reduce bias and increase accuracy.

Data Integration 69

Data Integration Government Data Metadata 69

ProjectPro

JANUARY 24, 2023

BigQuery is a highly scalable data warehouse platform with a built-in query engine offered by Google Cloud Platform. It provides a powerful and easy-to-use interface for large-scale data analysis, allowing users to store, query, analyze, and visualize massive datasets quickly and efficiently. What is Google BigQuery Used for?

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is a NoSQL database that’s been making rounds in the data science community. MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. Let us see where MongoDB for Data Science can help you. Why Use MongoDB for Data Science?

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Knowledge Hut

JUNE 23, 2023

Data warehousing to aggregate unstructured data collected from multiple sources. Data architecture to tackle datasets and the relationship between processes and applications. You should be well-versed in Python and R, which are beneficial in various data-related operations. What is COSHH? Explain indexing.

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 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

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. What is a Data Lake? Consistency of data throughout the data lake.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Knowledge Hut

NOVEMBER 28, 2023

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? Big resources still manage file data hierarchically using Hadoop's open-source ecosystem.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 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. Data Integration 3.Scalability

Hadoop 52

Hadoop Project Big Data Healthcare 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.

Data Process 52

Data Process Process Data Cleanse Data Mining 52