Knowledge Hut

APRIL 26, 2024

Datasets are the repository of information that is required to solve a particular type of problem. Also called data storage areas , they help users to understand the essential insights about the information they represent. Datasets play a crucial role and are at the heart of all Machine Learning models.

Machine Learning 98

Machine Learning Datasets Deep Learning Finance 98

databricks

JUNE 11, 2025

Automatic evaluation : Agent Bricks will then automatically create evaluation benchmarks specific to your task, which may involve synthetically generating new data or building custom LLM judges. Powered by MLflow 3, Agent Bricks automatically creates evaluation datasets and custom judges tailored to your task.

Entertainment 132

Entertainment Manufacturing Retail Consulting 132

Data Engineering Podcast

AUGUST 14, 2021

In this episode Davit Buniatyan, founder and CEO of Activeloop, explains why he is spending his time and energy on building a platform to simplify the work of getting your unstructured data ready for machine learning. Go to dataengineeringpodcast.com/satori today and get a $5K credit for your next Satori subscription.

Unstructured Data 100

Unstructured Data Machine Learning Data Lake SQL 100

ProjectPro

JUNE 6, 2025

RAG has changed how Large Language Models (LLMs) and natural language processing systems handle large-scale data to retrieve relevant information for question-answering systems. It enables semantic search over vast datasets by combining vector databases with language models. Optimal for general unstructured data.

Building 52

Building Unstructured Data Database Datasets 52

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 examine a few.

Data Engineering 52

Data Engineering Data Engineer Engineering Unstructured Data 52

ProjectPro

JUNE 6, 2025

As Databricks has revealed, a staggering 73% of a company's data goes unused for analytics and decision-making when stored in a data lake. Built on datasets that fail to capture the majority of a company's data, these models are doomed to return inaccurate results. The basic unit of storage in data lakes is called a blob.

Data Lake 63

Data Lake Data Warehouse Metadata Unstructured Data 63

Data Engineering Podcast

FEBRUARY 27, 2022

With Select Star’s data catalog, a single source of truth for your data is built in minutes, even across thousands of datasets. With Select Star’s data catalog, a single source of truth for your data is built in minutes, even across thousands of datasets.

Unstructured Data 100

Unstructured Data Cloud Management Metadata 100

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

ProjectPro

JUNE 6, 2025

Data is often referred to as the new oil, and just like oil requires refining to become useful fuel, data also needs a similar transformation to unlock its true value. This transformation is where data warehousing tools come into play, acting as the refining process for your data. Familiar SQL language for querying.

Data Storage 58

Data Storage PostgreSQL Data Warehouse AWS 58

Seattle Data Guy

DECEMBER 12, 2024

Document Intelligence Studio is a data extraction tool that can pull unstructured data from diverse documents, including invoices, contracts, bank statements, pay stubs, and health insurance cards. The cloud-based tool from Microsoft Azure comes with several prebuilt models designed to extract data from popular document types.

Insurance 130

Insurance Unstructured Data Banking Datasets 130

ProjectPro

JUNE 6, 2025

This considerable variation is unexpected, as we see from the past data trend and the model prediction shown in blue. You can train machine learning models can to identify such out-of-distribution anomalies from a much more complex dataset. More anomaly datasets can be accessed here: Outlier Detection DataSets (ODDS).

Machine Learning 60

Machine Learning Python Datasets Algorithm 60

ProjectPro

JUNE 6, 2025

Similarly, companies with vast reserves of datasets and planning to leverage them must figure out how they will retrieve that data from the reserves. A data engineer a technical job role that falls under the umbrella of jobs related to big data. You will work with unstructured data and NoSQL relational databases.

Data Engineering 58

Data Engineering Data Engineer Engineering Amazon Web Services 58

ProjectPro

JUNE 6, 2025

As per the March 2022 report by statista.com, the volume for global data creation is likely to grow to more than 180 zettabytes over the next five years, whereas it was 64.2 And, with largers datasets come better solutions. It is a serverless big data analysis tool. Best suited for large unstructured datasets.

AWS 67

AWS Big Data SQL Datasets 67

ProjectPro

JUNE 6, 2025

Scale Existing Python Code with Ray Python is popular among data scientists and developers because it is user-friendly and offers extensive built-in data processing libraries. For analyzing huge datasets, they want to employ familiar Python primitive types. Glue works absolutely fine with structured as well as unstructured data.

AWS 66

AWS Scala Metadata Data Lake 66

ProjectPro

JUNE 6, 2025

Sentiment Analysis and Voice of Customer Emerging Trends in AI Data Analytics Build AI and Data Analytics Skills with ProjectPro FAQS What is AI in Data Analytics? AI in data analytics refers to the use of AI tools and techniques to extract insights from large and complex datasets faster than traditional analytics methods.

Data Analytics 40

Data Analytics Unstructured Data Datasets BI 40

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

ProjectPro

JUNE 6, 2025

This influx of data and surging demand for fast-moving analytics has had more companies find ways to store and process data efficiently. This is where Data Engineers shine! The first step in any data engineering project is a successful data ingestion strategy. The data that Flume works is streaming data i.e

Data Ingestion 45

Data Ingestion Data Engineering Data Engineer Project 45

Snowflake

APRIL 20, 2023

In doing so, without compromising security or governance, we enable customers and partners to bring the power of LLMs to the data to help achieve two things: make enterprises smarter about their data and enhance user productivity in secure and scalable ways. Figure 1: Visual Question Answering Challenge data types and results.

Building 140

Building Unstructured Data Government Coding 140

Data Engineering Weekly

FEBRUARY 9, 2025

MoEs necessitate less compute for pre-training compared to dense models, facilitating the scaling of model and dataset size within similar computational budgets. link] QuantumBlack: Solving data quality for gen AI applications Unstructured data processing is a top priority for enterprises that want to harness the power of GenAI.

Data Engineering 58

Data Engineering Data Engineer Engineering Unstructured Data 58

Monte Carlo

DECEMBER 9, 2024

” Even when you’re working with unstructured data, like text for a language learning model, you still want to steer clear of bad inputs. If the data is messy or misleading, it can distort the AI’s understanding and lead to poor outputs. For simple tasks, smaller, focused datasets work great.

High Quality Data 52

High Quality Data Unstructured Data Data Datasets 52

RandomTrees

NOVEMBER 25, 2024

Generative AI employs ML and deep learning techniques in data analysis on larger datasets, resulting in produced content that has a creative touch but is also relevant. The considerable amount of unstructured data required Random Trees to create AI models that ensure privacy and data handling.

Telecommunication 52

Telecommunication IT Unstructured Data Data Mining 52

ProjectPro

JUNE 6, 2025

He suggests one should start by understanding the crucial distinction between structured and unstructured data—it's the cornerstone. For those venturing into data engineering, structured data is your launchpad. Consider this advice as your compass through the diverse roles in data science. PREVIOUS NEXT <

Data Science 52

Data Science Unstructured Data Portfolio Healthcare 52

ProjectPro

JUNE 6, 2025

Google BigQuery BigQuery is a fully-managed, serverless cloud data warehouse by Google. It facilitates business decisions using data with a scalable, multi-cloud analytics platform. It offers fast SQL queries and interactive dataset analysis. Additionally, it has excellent machine learning and business intelligence capabilities.

Data Engineering 40

Data Engineering Data Engineer Engineering Google Cloud 40

ProjectPro

JUNE 6, 2025

Netflix Analytics Engineer Interview Questions and Answers Here's a thoughtfully curated set of Netflix Analytics Engineer Interview Questions and Answers to enhance your preparation and boost your chances of excelling in your upcoming data engineer interview at Netflix: How will you transform unstructured data into structured data?

Data Engineering 40

Data Engineering Data Engineer Engineering NoSQL 40

ProjectPro

JUNE 6, 2025

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 Spark , on the other hand, is an analytics framework to process high-volume datasets.

Hadoop 45

Hadoop Java Big Data Tools SQL 45

ProjectPro

JUNE 6, 2025

It involves various steps like data collection, data quality check, data exploration, data merging, etc. This blog covers all the steps to master data preparation with machine learning datasets. ” Learning dance is not different than learning a new subject like machine learning or data science.

Data Preparation 45

Data Preparation Machine Learning Project IT 45

ProjectPro

JUNE 6, 2025

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 69

Machine Learning Project Datasets Algorithm 69

Striim

APRIL 18, 2025

Many organizations struggle with: Inconsistent data formats : Different systems store data in varied structures, requiring extensive preprocessing before analysis. Siloed storage : Critical business data is often locked away in disconnected databases, preventing a unified view.

High Quality Data 52

High Quality Data Business Intelligence Unstructured Data Data Pipeline 52

ProjectPro

JUNE 6, 2025

Integrating and implementing business intelligence on Hadoop has revolutionized how businesses manage big data , making Hadoop-based BI solutions more efficient and cost-effective than traditional data warehousing. Business intelligence OLAP is a powerful technology used in BI to perform complex analyses of large datasets.

Hadoop 40

Hadoop BI Big Data Business Intelligence 40

ProjectPro

JUNE 6, 2025

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 40

Big Data Hadoop Relational Database AWS 40

Data Engineering Weekly

MARCH 5, 2025

In the mid-2000s, Hadoop emerged as a groundbreaking solution for processing massive datasets. It promised to address key pain points: Scaling: Handling ever-increasing data volumes. Speed: Accelerating data insights. Like Hadoop, it aims to tackle scalability, cost, speed, and data silos.

Hadoop 58

Hadoop Metadata Data Ingestion Data Governance 58

ProjectPro

JUNE 6, 2025

Performance High performance for simple queries on small datasets. Low latency, high throughput for large datasets with simple queries. Data Consistency Strong consistency with ACID transactions. Amazon DynamoDB is a fully managed NoSQL database service by Amazon Web Services with document and key-value data model support.

Amazon Web Services 40

Amazon Web Services NoSQL Relational Database AWS 40

ProjectPro

JUNE 6, 2025

Features of Apache Spark Allows Real-Time Stream Processing- Spark can handle and analyze data stored in Hadoop clusters and change data in real time using Spark Streaming. Spark uses Resilient Distributed Dataset (RDD), which allows it to keep data in memory transparently and read/write it to disc only when necessary.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

ProjectPro

JUNE 6, 2025

Project Idea: Start data engineering pipeline by sourcing publicly available or simulated Uber trip datasets, for example, the TLC Trip record dataset.Use Python and PySpark for data ingestion, cleaning, and transformation. This project will help analyze user data for actionable insights.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

ProjectPro

JUNE 6, 2025

Apache Hadoop Development and Implementation Big Data Developers often work extensively with Apache Hadoop , a widely used distributed data storage and processing framework. They develop and implement Hadoop-based solutions to manage and analyze massive datasets efficiently.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

The first step, in this case study, is to clean the dataset to handle missing values, duplicates, and outliers. In the same step, the data is transformed, and the data is prepared for modeling with the help of feature engineering methods. The study is based on the dataset of passengers aboard the Titanic when it sank in 1912.

Machine Learning 75

Machine Learning Algorithm Amazon Web Services Healthcare 75

ProjectPro

JUNE 6, 2025

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40