Monte Carlo

FEBRUARY 12, 2024

To differentiate and expand the usefulness of these models, organizations must augment them with first-party data – typically via a process called RAG (retrieval augmented generation). Today, this first-party data mostly lives in two types of data repositories. Quality : Is the data itself anomalous?

Database 72

Database Unstructured Data Data Pipeline Metadata 72

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

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies. Increased confidence in data results in trusted AI.

Cloud 104

Cloud Unstructured Data Metadata Datasets 104

Knowledge Hut

APRIL 23, 2024

Data Science is the field that focuses on gathering data from multiple sources using different tools and techniques. Whereas, Business Intelligence is the set of technologies and applications that are helpful in drawing meaningful information from raw data. Data Usage It stores the data in a sorted manner for future use.

Business Intelligence 52

Business Intelligence Data Science BI Unstructured Data 52

Snowflake

MARCH 18, 2024

This time it’s all about ensuring that the data and the platform where it’s processed are ready for the new AI models. But there’s still a long way to go in an environment where the volume, velocity and complexity of data and data types is constantly increasing. And it’s not just any type of data.

Unstructured Data 88

Unstructured Data Government Data Pipeline Cloud 88

Monte Carlo

MAY 28, 2024

A data ingestion architecture is the technical blueprint that ensures that every pulse of your organization’s data ecosystem brings critical information to where it’s needed most. Ensuring all relevant data inputs are accounted for is crucial for a comprehensive ingestion process. A typical data ingestion flow.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

AltexSoft

OCTOBER 25, 2021

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. What is Natural Language Processing? This allows machines to extract value even from unstructured data. Nuance, acquired for $19.7

Medical 52

Medical Healthcare Process Hospitality 52

Snowflake

NOVEMBER 2, 2023

Rather than defining schema upfront, a user can decide which data and schema they need for their use case. Snowflake has long supported semi-structured data types and file formats like JSON, XML, Parquet, and more recently storage and processing of unstructured data such as PDF documents, images, videos, and audio files.

Data Lake 92

Data Lake Data Warehouse Cloud Unstructured Data 92

Precisely

SEPTEMBER 6, 2023

To truly succeed in an increasingly data-driven world, organizations need data governance. Data governance is the formal orchestration of people, processes, and technology to enable an organization to leverage data as an enterprise asset. The need for scalable data governance frameworks is growing.

Data Governance 52

Data Governance Big Data Government Unstructured Data 52

Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

APRIL 23, 2024

Data storing and processing is nothing new; organizations have been doing it for a few decades to reap valuable insights. Compared to that, Big Data is a much more recently derived term. So, what exactly is the difference between Traditional Data and Big Data? Smaller and more cost-effective ways of managing data.

Big Data 52

Big Data Relational Database Data Datasets 52

Knowledge Hut

APRIL 23, 2024

Big data refers to large volumes of data or datasets that cannot be gleaned or parsed with traditional tools and methods. These overwhelming datasets encompass extensive and complex information from multiple sources like transactions, web interactions, and sensor data.

Big Data 52

Big Data Media Datasets Unstructured Data 52

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

JANUARY 30, 2024

What is data extraction? Data extraction is the vital process of retrieving raw data from diverse sources, such as databases, Excel spreadsheets, SaaS platforms, or web scraping efforts. In this repository, data from multiple sources is consolidated and standardized, providing a centralized hub for analytical purposes.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. Data lakes are often used for situations in which an organization wishes to store information for possible future use.

Data Lake 57

Data Lake Data Warehouse Hadoop Raw Data 57

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

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. js: To create interactive and customizable charts, D3.js

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Knowledge Hut

JANUARY 11, 2024

Data science is the field of study that deals with a huge volume of data using modern technologically driven tools and techniques to find some sort of pattern and derive meaningful information out of it that eventually helps in business and financial decisions. Data science practices help with risk analysis.

Finance 93

Finance Data Science Programming Language Machine Learning 93

U-Next

MARCH 1, 2023

Being a hybrid role, Data Engineer requires technical as well as business skills. They build scalable data processing pipelines and provide analytical insights to business users. A Data Engineer also designs, builds, integrates, and manages large-scale data processing systems. What is a data warehouse?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

Snowflake

MAY 1, 2023

A shared source of truth for data teams living in Snowflake. AI services for semantic processing of unstructured information. We are in the process of transforming our application into a Snowflake Native App for the next phase of our growth,” says Steinman. Automated financial and operational ERP insights.

Insurance 102

Insurance Unstructured Data Python Building 102

Knowledge Hut

JULY 24, 2023

Disruptive database technologies include, for instance: Blockchain Blockchain is a distributed ledger technology that enables data to be safely stored across several nodes in a decentralized (or sometimes in a centralized) manner. These nodes contain hashed/encrypted information to ensure security at each level.

Database 52

Database NoSQL Management Relational Database 52

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. Embedding: The retrieved data is encoded into embeddings that the LLM can interpret.

Data Engineering 46

Data Engineering Data Engineer Engineering Unstructured Data 46

Knowledge Hut

APRIL 25, 2024

One of the industries with the quickest growth rates is big data. It refers to gathering and processing sizable amounts of data to produce insights that may be used by an organization to improve its various facets. What Are the Different Features of Big Data Analytics? The main features of big data analytics are: 1.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making.

Unstructured Data 74

Unstructured Data Data Lake Data Architecture Data 74

Knowledge Hut

DECEMBER 26, 2023

You can execute this by learning data science with python and working on real projects. These skills are essential to collect, clean, analyze, process and manage large amounts of data to find trends and patterns in the dataset. The dataset can be either structured or unstructured or both.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

AltexSoft

AUGUST 29, 2023

Getting back to the topic, the key thing to understand about a data lake isn’t its construction but rather its capabilities. It is a versatile platform for exploring, refining, and analyzing petabytes of information that continually flow in from various data sources. Who needs a data lake? Structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

MAY 31, 2023

Artificial intelligence (AI) projects are software-based initiatives that utilize machine learning, deep learning, natural language processing, computer vision, and other AI technologies to develop intelligent programs capable of performing various tasks with minimal human intervention.

Project 96

Project Healthcare Deep Learning Transportation 96

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Data Engineering Weekly

JUNE 4, 2023

[link] Uber: Spark Analysers: Catching Anti-Patterns In Spark Apps One of the challenges in commoditizing data processing engines like Spark is that it requires an expert user to understand and operate this system. Many of the real-world data, all the way from medical images to astro monitoring, are unstructured data.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

Knowledge Hut

DECEMBER 13, 2023

The data is the property of various organizations, each of which uses it for various objectives. Change is a constant, whether it be in the form of new businesses, products, processes, or approaches. Big Data startups compete for market share with the blue-chip giants that dominate the business intelligence software market.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

Knowledge Hut

MARCH 7, 2024

Introduction to Big Data Analytics Tools Big data analytics tools refer to a set of techniques and technologies used to collect, process, and analyze large data sets to uncover patterns, trends, and insights. Very High-Performance Analytics is required for the big data analytics process.

Big Data 52

Big Data Data Analytics Data Mining MongoDB 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

ProjectPro

JANUARY 27, 2023

It is extremely important for businesses to process data correctly since the volume and complexity of raw data are rapidly growing. Over the past few years, data-driven enterprises have succeeded with the Extract Transform Load (ETL) process to promote seamless enterprise data exchange.

BI 52

BI ETL Tools Retail Healthcare 52

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52