AWS Machine Learning Blog

FEBRUARY 21, 2025

The agent knowledge base stores Amazon Bedrock service documentation, while the cache knowledge base contains curated and verified question-answer pairs. For this example, you will ingest Amazon Bedrock documentation in the form of the User Guide PDF into the Amazon Bedrock knowledge base. This will be the primary dataset.

AWS

databricks

JUNE 12, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

SQL

AWS Machine Learning Blog

FEBRUARY 18, 2025

To handle the log data efficiently, raw logs were centralized into an Amazon Simple Storage Service (Amazon S3) bucket. An Amazon EventBridge schedule checked this bucket hourly for new files and triggered log transformation extract, transform, and load (ETL) pipelines built using AWS Glue and Apache Spark.

AWS

Hacker News

JULY 1, 2025

I'm JD, a Software Engineer with experience touching many parts of the stack (frontend, backend, databases, data & ETL pipelines, you name it). Contribute to internal and external documentation to improve customer experiences. Oh, also, I'm great at writing documentation.

Python

Hacker News

AUGUST 1, 2025

We spend half a day a week reading documentation and doing nothing else, and another full day coaching the team on cutting edge tech (how to design, build, train, deploy ai models). It is a toolbox for web engineers and application developers who need a painless way to render, edit and process documents. We invest a lot in our team.

Python

Pickl AI

MARCH 19, 2025

MongoDB MongoDB is a NoSQL database that stores data in flexible, JSON-like documents. It is ideal for handling unstructured or semi-structured data, making it perfect for modern applications that require scalability and fast access. It simplifies data processing by providing an SQL-like interface for querying Big Data.

Data Engineering

AWS Machine Learning Blog

MARCH 5, 2025

For example, consider how the following source document chunk from the Amazon 2023 letter to shareholders can be converted to question-answering ground truth. To convert the source document excerpt into ground truth, we provide a base LLM prompt template. Further, Amazons operating income and Free Cash Flow (FCF) dramatically improved.

AWS

Hacker News

AUGUST 1, 2025

My expertise includes data visualization, business intelligence and analytics. I have extensive experience with the TIBCO Jaspersoft BI suite - Jaspersoft Studio, JasperReports Server and Jaspersoft ETL (Talend Open Studio and Server). Majorly worked in the Education sector for external & internal applications.

Python

Smart Data Collective

JULY 20, 2021

Big data technology is incredibly important in modern business. One of the most important applications of big data is with building relationships with customers. These software tools rely on sophisticated big data algorithms and allow companies to boost their sales, business productivity and customer retention.

Big Data

Data Science Blog

SEPTEMBER 19, 2023

In the contemporary age of Big Data, Data Warehouse Systems and Data Science Analytics Infrastructures have become an essential component for organizations to store, analyze, and make data-driven decisions. So why using IaC for Cloud Data Infrastructures?

Data Warehouse

Dataconomy

SEPTEMBER 4, 2023

Text analytics: Text analytics, also known as text mining, deals with unstructured text data, such as customer reviews, social media comments, or documents. It uses natural language processing (NLP) techniques to extract valuable insights from textual data. Poor data integration can lead to inaccurate insights.

Analytics

Hacker News

JULY 18, 2024

ABOUT EVENTUAL Eventual is a data platform that helps data scientists and engineers build data applications across ETL, analytics and ML/AI. OUR PRODUCT IS OPEN-SOURCE AND USED AT ENTERPRISE SCALE Our distributed data engine Daft [link] is open-sourced and runs on 800k CPU cores daily.

ML

AWS Machine Learning Blog

FEBRUARY 2, 2024

Overview of RAG The RAG pattern lets you retrieve knowledge from external sources, such as PDF documents, wiki articles, or call transcripts, and then use that knowledge to augment the instruction prompt sent to the LLM. Before you can start question and answering, embed the reference documents, as shown in the next section.

AWS

Flipboard

NOVEMBER 24, 2023

The SnapLogic Intelligent Integration Platform (IIP) enables organizations to realize enterprise-wide automation by connecting their entire ecosystem of applications, databases, big data, machines and devices, APIs, and more with pre-built, intelligent connectors called Snaps.

Database

Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Choosing the right ETL tool is crucial for smooth data management.

ETL

AWS Machine Learning Blog

AUGUST 2, 2024

The Product Stewardship department is responsible for managing a large collection of regulatory compliance documents. Example questions might be “What are the restrictions for CMR substances?”, “How long do I need to keep the documents related to a toluene sale?”, or “What is the reach characterization ratio and how do I calculate it?”

AWS

Smart Data Collective

APRIL 29, 2020

The storage and processing of data through a cloud-based system of applications. Master data management. The techniques for managing organisational data in a standardised approach that minimises inefficiency. Extraction, Transform, Load (ETL). Data transformation. Microsoft Azure.

Data Warehouse

AWS Machine Learning Blog

SEPTEMBER 18, 2024

An example direct acyclic graph (DAG) might automate data ingestion, processing, model training, and deployment tasks, ensuring that each step is run in the correct order and at the right time. Though it’s worth mentioning that Airflow isn’t used at runtime as is usual for extract, transform, and load (ETL) tasks.

AWS

Pickl AI

OCTOBER 10, 2024

Enhanced Data Quality : These tools ensure data consistency and accuracy, eliminating errors often occurring during manual transformation. Scalability : Whether handling small datasets or processing big data, transformation tools can easily scale to accommodate growing data volumes.

Data Quality

ODSC - Open Data Science

OCTOBER 18, 2024

The advent of big data, affordable computing power, and advanced machine learning algorithms has fueled explosive growth in data science across industries. However, research shows that up to 85% of data science projects fail to move beyond proofs of concept to full-scale deployment.

Data Science

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Reverse ETL tools. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means.

Data Warehouse

ODSC - Open Data Science

SEPTEMBER 29, 2023

But, the amount of data companies must manage is growing at a staggering rate. Research analyst firm Statista forecasts global data creation will hit 180 zettabytes by 2025. In our discussion, we cover the genesis of the HPCC Systems data lake platform and what makes it different from other big data solutions currently available.

Data Lakes

Precisely

APRIL 3, 2023

How can an organization enable flexible digital modernization that brings together information from multiple data sources, while still maintaining trust in the integrity of that data? To speed analytics, data scientists implemented pre-processing functions to aggregate, sort, and manage the most important elements of the data.

ETL

AWS Machine Learning Blog

SEPTEMBER 6, 2024

Each triplet describes a fact, and an encapsulation of the fact as a question-answer pair to emulate an ideal response, derived from a knowledge source document. We used Amazon’s Q2 2023 10Q report as the source document from the SEC’s public EDGAR dataset to create 10 question-answer-fact triplets.

AI

Pickl AI

JANUARY 28, 2025

Data can be structured (e.g., documents and images). The diversity of data sources allows organizations to create a comprehensive view of their operations and market conditions. Data Integration Once data is collected from various sources, it needs to be integrated into a cohesive format.

Business Intelligence

AWS Machine Learning Blog

NOVEMBER 29, 2023

For instance, a notebook that monitors for model data drift should have a pre-step that allows extract, transform, and load (ETL) and processing of new data and a post-step of model refresh and training in case a significant drift is noticed. Refer to SageMaker documentation for detailed instructions.

ML

DagsHub

NOVEMBER 11, 2024

So, we must understand the different unstructured data types and effectively process them to uncover hidden patterns. Textual Data Textual data is one of the most common forms of unstructured data and can be in the format of documents, social media posts, emails, web pages, customer reviews, or conversation logs.

AI

AWS Machine Learning Blog

APRIL 24, 2023

Amazon Comprehend is a fully managed and continuously trained natural language processing (NLP) service that can extract insight about the content of a document or text. Amazon Comprehend training workflow To start the training the Amazon Comprehend model, we need to prepare the training data.

ML

phData

JUNE 26, 2023

However, real-world data, especially in the context of big data, can often be well into the hundreds of millions or billions of records. KNIME, on the other hand, is designed to work with big data technologies and can handle much larger volumes of data without compromising performance.

Tableau

DagsHub

OCTOBER 23, 2024

Data Preprocessing Here, you can process the unstructured data into a format that can be used for the other downstream tasks. For instance, if the collected data was a text document in the form of a PDF, the data preprocessing—or preparation stage —can extract tables from this document. Unstructured.io

Machine Learning

Mlearning.ai

JULY 10, 2023

[link] Tables The table in GCP BigQuery is a collection of rows and columns that can store and manage massive amounts of data. It’s a managed, cloud-based service that’s designed to handle big data processing with ease. You can use stored procedures to handle complex ETL processes, make API calls, and perform data validation.

SQL

Pickl AI

JULY 18, 2024

MongoDB is a NoSQL database that handles large-scale data and modern application requirements. Unlike traditional relational databases, MongoDB stores data in flexible, JSON-like documents, allowing for dynamic schemas. In contrast, MongoDB’s document-based model allows for a more flexible and scalable approach.

Database

Flipboard

MAY 15, 2025

It secures your data in the lakehouse by defining fine-grained permissions, which are consistently applied across all analytics and ML tools and engines. You can bring data from operational databases and applications into your lakehouse in near real time through zero-ETL integrations. catalog_name}.client.region

AWS

databricks

JUNE 16, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

Data Science

AWS Machine Learning Blog

JANUARY 7, 2025

About the Authors Siokhan Kouassi is a Data Scientist at Parameta Solutions with expertise in statistical machine learning, deep learning, and generative AI. Martin Gregory is a Senior Market Data Technician at Parameta Solutions with over 25 years of experience.

AWS

Dataconomy

MARCH 7, 2025

ClickUp ClickUp is more than just a project management toolits an AI-powered productivity hub that consolidates task management, document collaboration, and workflow automation in one platform. Analysts and investors use it to identify trends, assess company performance, and stay ahead of market shifts with AI-powered data analysis.

AI