Monte Carlo

OCTOBER 31, 2024

Key Differences Between AI Data Engineers and Traditional Data Engineers While traditional data engineers and AI data engineers have similar responsibilities, they ultimately differ in where they focus their efforts. Let’s dive into the tools necessary to become an AI data engineer.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52

Data Engineering Weekly

JULY 14, 2024

[link] Sponsored: 7/25 Amazon Bedrock Data Integration Tech Talk Streamline & scale data integration to and from Amazon Bedrock for generative AI applications. Senior Solutions Architect at AWS) Learn about: Efficient methods to feed unstructured data into Amazon Bedrock without intermediary services like S3.

Data Engineer 98

Data Engineer Data Engineering Engineering Unstructured Data 98

Monte Carlo

JULY 15, 2024

We recently spoke with Killian Farrell , Principal Data Scientist at insurance startup AssuranceIQ to learn how his team built an LLM-based product to structure unstructured data and score customer conversations for developing sales and customer support teams. Any moment could impact a customer’s next decision.”

Unstructured Data 52

Unstructured Data Insurance Data Lake Structured Data 52

Monte Carlo

OCTOBER 10, 2024

Let’s dive into the responsibilities, skills, challenges, and potential career paths for an AI Data Quality Analyst today. Table of Contents What Does an AI Data Quality Analyst Do? An AI Data Quality Analyst should be comfortable with: Data Management : Proficiency in handling large datasets.

Unstructured Data 52

Unstructured Data Google Cloud Machine Learning ETL Tools 52

ProjectPro

MARCH 17, 2021

“Machine Learning” and “Deep Learning” – are two of the most often confused and conflated terms that are used interchangeably in the AI world. However, there is one undeniable fact that both machine learning and deep learning are undergoing skyrocketing growth. respectively.

Deep Learning 52

Deep Learning Machine Learning Algorithm Data Science 52

Snowflake

NOVEMBER 11, 2024

Traditionally, SQL has been limited to structured data neatly organized in tables. Snowflake will be introducing new multimodal SQL functions (private preview soon) that enable data teams to run analytical workflows on unstructured data, such as images.

Unstructured Data 52

Unstructured Data SQL AWS Healthcare 52

AltexSoft

JULY 27, 2021

And what does machine learning have to do with it? In this article, we’re taking you down the road of machine learning-based personalization. You’ll learn about the types of recommender systems, their differences, strengths, weaknesses, and real-life examples. How recommender systems work: data processing phases.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. It is because these apps render machine learning models that try to understand the customer's taste. can help you model such machine learning projects.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

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.

Database 72

Database Unstructured Data Data Pipeline Metadata 72

Knowledge Hut

APRIL 23, 2024

Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data. Data warehousing offers several advantages. By structuring data in a predefined schema, data warehouses ensure data consistency and accuracy.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

AUGUST 16, 2024

The most common degrees that Data Scientists have are Statistics and Mathematics (32%), Business and Economics (21%), Computer Science (19%), and Engineering (16%). Let us look at some of the areas in Mathematics that are the prerequisites to becoming a Data Scientist.

Data Science 52

Data Science Hadoop Unstructured Data Programming Language 52

Cloudera

NOVEMBER 15, 2024

Unstructured data not ready for analysis: Even when defenders finally collect log data, it’s rarely in a format that’s ready for analysis. Cyber logs are often unstructured or semi-structured, making it difficult to derive insights from them.

Metadata 77

Metadata Unstructured Data Data Lake Government 77

Knowledge Hut

APRIL 23, 2024

Big data and data mining are neighboring fields of study that analyze data and obtain actionable insights from expansive information sources. Big data encompasses a lot of unstructured and structured data originating from diverse sources such as social media and online transactions.

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

Cloudera

MAY 14, 2024

This form of hybrid also goes a level deeper than one may find in a standard hybrid cloud, accounting for the entirety of the data lifecycle, whether that’s the point of ingestion, warehousing, or machine learning—even when that end-to-end data lifecycle is split between entirely different environments.

Cloud 98

Cloud Data Governance Unstructured Data Data Architecture 98

Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Cloud Storage 157

Cloud Storage Data Lake Cloud Unstructured Data 157

RandomTrees

SEPTEMBER 17, 2024

Data Discovery: Users can find and use data more effectively because to Unity Catalog’s tagging and documentation features. Unified Governance: It offers a comprehensive governance framework by supporting notebooks, dashboards, files, machine learning models, and both organized and unstructured data.

Data Governance 52

Data Governance Government Metadata Machine Learning 52

Striim

SEPTEMBER 11, 2024

Data Pipeline Use Cases Data pipelines are integral to virtually every industry today, serving a wide range of functions from straightforward data transfers to complex transformations required for advanced machine learning applications.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

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

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Management Data Lake Data Governance 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

Knowledge Hut

DECEMBER 26, 2023

Of course, handling such huge amounts of data and using them to extract data-driven insights for any business is not an easy task; and this is where Data Science comes into the picture. Mathematical concepts like Statistics and Probability, Calculus, and Linear Algebra are vital in pursuing a career in Data Science.

Data Science 97

Data Science BI Business Intelligence Machine Learning 97

Edureka

JUNE 7, 2024

Industry Applications of Predictive AI While both involve machine learning and data analysis, they differ in their core objectives and approaches. paintings, songs, code) Historical data relevant to the prediction task (e.g., Real-world Applications of Generative AI The Power of Predictive AI How Does Predictive AI Work?

Deep Learning 114

Deep Learning Media Manufacturing Algorithm 114

Knowledge Hut

APRIL 23, 2024

Data Usage It stores the data in a sorted manner for future use. It uses data from the past and present to make decisions related to future growth. Data Type Data science deals with both structured and unstructured data. Business Intelligence only deals with structured data.

Business Intelligence 52

Business Intelligence Data Science BI Unstructured Data 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

DareData

JANUARY 30, 2023

Learn the most important data engineering concepts that data scientists should be aware of. As the field of data science and machine learning continues to evolve, it is increasingly evident that data engineering cannot be separated from it. Join us!

Data Engineer 52

Data Engineer Data Engineering NoSQL Engineering 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Data Engineering Weekly

APRIL 7, 2024

I guess only the time will tell who wins in the data mesh vs data fabric war. link] Matt Turck: Full Steam Ahead: The 2024 MAD (Machine Learning, AI & Data) Landscape Coninue the week of insights into the world of data & AI landscape, the 2024 MAD landscape is out.

Data Engineer 70

Data Engineer Data Engineering Engineering Unstructured Data 70

AltexSoft

AUGUST 29, 2023

If your organization fits into one of these categories and you’re considering implementing advanced data management and analytics solutions, keep reading to learn how data lakes work and how they can benefit your business. While flexible, they may require more extensive management to ensure data quality and security.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

FEBRUARY 15, 2023

A data warehouse is an online analytical processing system that stores vast amounts of data collected within a company’s ecosystem and acts as a single source of truth to enable downstream data consumers to perform business intelligence tasks, machine learning modeling, and more.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Knowledge Hut

SEPTEMBER 26, 2023

It offers a wide range of services, including computing, storage, databases, machine learning, and analytics, making it a versatile choice for businesses looking to harness the power of the cloud. Organizations can harness the power of the cloud, easily scaling resources up or down to meet their evolving data processing demands.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Edureka

JANUARY 18, 2024

This guide provides a comprehensive understanding of the essential skills and knowledge required to become a successful data scientist, covering data manipulation, programming, mathematics, big data, deep learning, and machine learning technologies.

Data Science 40

Data Science Deep Learning Machine Learning NoSQL 40

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.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 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?

Big Data 52

Big Data Relational Database Data Datasets 52

Striim

OCTOBER 11, 2024

A data pipeline refers to a series of processes that transport data from one or more sources to a destination, such as a data warehouse, database, or application. Throughout the pipeline, data undergoes various transformations such as filtering, cleaning, aggregating, enriching, and even real-time analysis.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52