Flipboard

MAY 14, 2025

In this post, we show you how Amazon Q Business can help augment your generative AI needs in all the abovementioned use cases and more by answering questions, providing summaries, generating content, and securely completing tasks based on data and information in your enterprise systems. Traditionally, businesses face a challenge.

AWS 143

AWS AI AI Database 143

Dataversity

APRIL 23, 2021

Within the Data Management industry, it’s becoming clear that the old model of rounding up massive amounts of data, dumping it into a data lake, and building an API to extract needed information isn’t working. It’s outdated, it’s clunky, and it was built for a different era. […].

Database 90

Database Data Lakes Data Silos Data Governance 90

Flipboard

NOVEMBER 27, 2024

Customers want to search through all of the data and applications across their organization, and they want to see the provenance information for all of the documents retrieved. The application needs to search through the catalog and show the metadata information related to all of the data assets that are relevant to the search context.

AWS 149

AWS Database ML ML 149

AWS Machine Learning Blog

DECEMBER 3, 2024

Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. Connect your database in QuickSight to create a dataset. For pricing information, see Amazon Q Business pricing.

AWS 107

AWS Database Data Silos Data Lakes 107

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. In this article, we’ll focus on a data lake vs. data warehouse.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

AWS Machine Learning Blog

MAY 30, 2024

To serve their customers, Vitech maintains a repository of information that includes product documentation (user guides, standard operating procedures, runbooks), which is currently scattered across multiple internal platforms (for example, Confluence sites and SharePoint folders). langsmith==0.0.43 pgvector==0.2.3 streamlit==1.28.0

AI 134

AI AI AWS Database 134

Dataversity

MARCH 26, 2024

Writing data to an AWS data lake and retrieving it to populate an AWS RDS MS SQL database involves several AWS services and a sequence of steps for data transfer and transformation. This process leverages AWS S3 for the data lake storage, AWS Glue for ETL operations, and AWS Lambda for orchestration.

Data Lakes 64

Data Lakes AWS SQL ETL 64

AWS Machine Learning Blog

AUGUST 8, 2024

Data is the foundational layer for all generative AI and ML applications. Managing and retrieving the right information can be complex, especially for data analysts working with large data lakes and complex SQL queries. The following diagram illustrates the solution architecture.

SQL 132

SQL Data Lakes Data Analyst AWS 132

AWS Machine Learning Blog

DECEMBER 11, 2024

Heres a sampling of what some of our more active users had to say about their experience with Field Advisor: I use Field Advisor to review executive briefing documents, summarize meetings and outline actions, as well analyze dense information into key points with prompts. Field Advisor continues to enable me to work smarter, not harder.

AWS 114

AWS Database AI AI 114

Dataconomy

JUNE 1, 2023

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. OneLake is designed to store a single copy of data in a unified location, leveraging the open-source Apache Parquet format.

Power BI 194

Power BI Data Lakes Azure Data Silos 194

Tableau

MARCH 30, 2021

we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere. March 30, 2021.

Azure 102

Azure Tableau Data Lakes SQL 102

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

phData

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 Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

AWS Machine Learning Blog

NOVEMBER 14, 2024

When defining your tagging strategy, you need to determine the right tags that will gather all the necessary information in your environment. Avoid personally identifiable information (PII) when labeling resources because tags remain unencrypted and visible. This identifies teams or cost centers responsible for those resources.

ML 112

ML ML AWS Machine Learning 112

Dataconomy

FEBRUARY 26, 2025

Data mining has emerged as a vital tool in todays data-driven environment, enabling organizations to extract valuable insights from vast amounts of information. As businesses generate and collect more data than ever before, understanding how to uncover patterns and trends becomes essential for making informed decisions.

Data Mining 91

Data Mining Data Mining Data Mining Data Preparation 91

Dataconomy

MARCH 4, 2025

Data mining is a fascinating field that blends statistical techniques, machine learning, and database systems to reveal insights hidden within vast amounts of data. Businesses across various sectors are leveraging data mining to gain a competitive edge, improve decision-making, and optimize operations.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

Flipboard

MAY 30, 2025

A generative AI foundation can provide primitives such as models, vector databases, and guardrails as a service and higher-level services for defining AI workflows, agents and multi-agents, tools, and also a catalog to encourage reuse. Considerations here are choice of vector database, optimizing indexing pipelines, and retrieval strategies.

AWS 141

AWS AI AI Database 141

Flipboard

NOVEMBER 17, 2023

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. Set up the database access and network access.

K-nearest Neighbors 170

K-nearest Neighbors AWS Clustering Database 170

AWS Machine Learning Blog

NOVEMBER 12, 2024

The following is an example of a financial information dataset for exchange-traded funds (ETFs) from Kaggle in a structured tabular format that we used to test our solution. What would the LLM’s response or data analysis be when the user’s questions in industry specific natural language get more complex?

SQL 124

SQL AWS AI AI 124

Data Science Connect

JULY 28, 2023

The Crucial Role of Data Engineering in IoT As the IoT ecosystem continues to expand with an influx of connected devices generating massive volumes of data, data engineering becomes a critical component in realizing IoT’s true potential. Data Cleaning and Preprocessing IoT data can be noisy, incomplete, and inconsistent.

Internet of Things 130

Internet of Things Data Engineer Data Engineering Data Engineering 130

AWS Machine Learning Blog

JUNE 5, 2023

Many teams are turning to Athena to enable interactive querying and analyze their data in the respective data stores without creating multiple data copies. Athena allows applications to use standard SQL to query massive amounts of data on an S3 data lake. Create a data lake with Lake Formation.

Machine Learning 98

Machine Learning Machine Learning AWS Data Lakes 98

DagsHub

DECEMBER 11, 2023

Data auditing and compliance Almost each company face data protection regulations such as GDPR, forcing them to store certain information in order to demonstrate compliance and history of data sources. In this scenario, data versioning can help companies in both internal and external audits process.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Database 98

AWS Machine Learning Blog

JANUARY 29, 2025

One way to mitigate LLMs from giving incorrect information is by using a technique known as Retrieval Augmented Generation (RAG). RAG combines the powers of pre-trained language models with a retrieval-based approach to generate more informed and accurate responses.

AWS 105

AWS AI AI Database 105

IBM Journey to AI blog

APRIL 24, 2023

Why data warehousing is critical to a company’s success Data warehousing is the secure electronic information storage by a company or organization. Benefits of new data warehousing technology Everything is data, regardless of whether it’s structured, semi-structured, or unstructured.

Data Warehouse 112

Data Warehouse Data Lakes Database Artificial Intelligence 112

Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. Hopefully, it was informative and helpful to you. Well, let’s find out. Artificial intelligence (AI).

AWS 138

AWS Cloud Computing Data Lakes Database 138

AWS Machine Learning Blog

JANUARY 4, 2024

To do this, the text input is transformed into a structured representation, and from this representation, a SQL query that can be used to access a database is created. The primary goal of Text2SQL is to make querying databases more accessible to non-technical users, who can provide their queries in natural language. gymnast_id = t2.

SQL 141

SQL Database AI AI 141

Smart Data Collective

OCTOBER 17, 2022

Pipeline, as it sounds, consists of several activities and tools that are used to move data from one system to another using the same method of data processing and storage. Data pipelines automatically fetch information from various disparate sources for further consolidation and transformation into high-performing data storage.

Data Pipeline 145

Data Pipeline Data Warehouse ETL Exploratory Data Analysis 145

AWS Machine Learning Blog

JUNE 20, 2024

Our goal was to improve the user experience of an existing application used to explore the counters and insights data. The data is stored in a data lake and retrieved by SQL using Amazon Athena. The problem Making data accessible to users through applications has always been a challenge.

SQL 119

SQL Database AWS Machine Learning 119

Dataconomy

MAY 26, 2025

Business analytics is a powerful enabler for organizations seeking to harness the quintessence of information to optimize performance and drive strategic initiatives. It delves beyond mere data collection, engaging in the processes of extracting meaningful insights to inform better business decisions.

Analytics 91

Analytics Analytics Data Analysis Data Analysis 91

ODSC - Open Data Science

MAY 16, 2023

Comprehensive data privacy laws in at least four states are going into effect this year, and more than a dozen states have similar legislation in the works. Database management may become increasingly complex as organizations must account for more of these laws.

Database 98

Database Data Science Data Lakes Data Observability 98

Dataconomy

FEBRUARY 25, 2025

Variety Variety delineates the different data types involved, encompassing structured data like databases, unstructured data such as text and multimedia content, and semi-structured data found in logs and sensor data. Velocity Velocity describes the speed at which data is generated and processed.

Big Data 91

Big Data Big Data Data Lakes Machine Learning 91

Pickl AI

APRIL 21, 2025

Summary: Big Data refers to the vast volumes of structured and unstructured data generated at high speed, requiring specialized tools for storage and processing. Data Science, on the other hand, uses scientific methods and algorithms to analyses this data, extract insights, and inform decisions.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

AWS Machine Learning Blog

FEBRUARY 12, 2025

In such cases, using an FM to parse the data will provide better results. You can use advanced parsing options supported by Amazon Bedrock Knowledge Bases for parsing non-textual information from documents using FMs. Many organizations store their data in structured formats within data warehouses and data lakes.

AWS 105

AWS Machine Learning Machine Learning AI 105

Flipboard

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

AWS 167

AWS ML ML Analytics 167

Flipboard

DECEMBER 6, 2023

To meet the growing demand for efficient and dynamic data retrieval, Q4 aimed to create a chatbot Q&A tool that would provide an intuitive and straightforward method for IROs to access the necessary information they need in a user-friendly format. The generated query is then run against the database to fetch the relevant context.

SQL 168

SQL Database AWS Machine Learning 168

AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone is a data management service that makes it quick and convenient to catalog, discover, share, and govern data stored in AWS, on-premises, and third-party sources. The sample dataset Upload the dataset to Amazon S3 and crawl the data to create an AWS Glue database and tables.

Machine Learning 126

Machine Learning Machine Learning Data Governance ML 126

phData

NOVEMBER 9, 2023

The main goal of a data mesh structure is to drive: Domain-driven ownership Data as a product Self-service infrastructure Federated governance One of the primary challenges that organizations face is data governance. What is a Data Lake? What is the Difference Between a Data Lake and a Data Warehouse?

Data Warehouse 98

Data Warehouse Data Lakes Clustering Cloud Data 98