ODSC - Open Data Science

OCTOBER 13, 2024

Be sure to check out her talk, “ Don’t Go Over the Deep End: Building an Effective OSS Management Layer for Your Data Lake ,” there! Managing a data lake can often feel like being lost at sea — especially when dealing with both structured and unstructured data.

Data Lakes 40

Data Lakes Database Data Pipeline SQL 40

AWS Machine Learning Blog

AUGUST 8, 2024

Managing and retrieving the right information can be complex, especially for data analysts working with large data lakes and complex SQL queries. This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock.

SQL 110

SQL Data Lakes Data Analyst AWS 110

Data Science Blog

MAY 20, 2024

It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models. It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL. pipelines, Azure Data Bricks.

Data Pipeline 262

Data Pipeline Data Warehouse Azure Data Lakes 262

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 Modeling Data Models Data Warehouse 52

ODSC - Open Data Science

SEPTEMBER 29, 2023

Data management problems can also lead to data silos; disparate collections of databases that don’t communicate with each other, leading to flawed analysis based on incomplete or incorrect datasets. One way to address this is to implement a data lake: a large and complex database of diverse datasets all stored in their original format.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

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 following figure shows a search query that was translated to SQL and run. The challenge is to assure quality.

SQL 97

SQL Database AWS Machine Learning 97

Data Science Blog

JULY 20, 2024

Automatisierung: Erstellt SQL-Code, DACPAC-Dateien, SSIS-Pakete, Data Factory-ARM-Vorlagen und XMLA-Dateien. Vielfältige Unterstützung: Kompatibel mit verschiedenen Datenbankmanagementsystemen wie MS SQL Server und Azure Synapse Analytics. Data Lakes: Unterstützt MS Azure Blob Storage.

Azure 130

Azure Power BI SQL Data Lakes 130

AWS Machine Learning Blog

FEBRUARY 28, 2024

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL knowledge. This generative AI task is called text-to-SQL, which generates SQL queries from natural language processing (NLP) and converts text into semantically correct SQL.

SQL 121

SQL AWS Database ML 121

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models. Without business context, business users are less likely to use the data lake and insights will be hard to come by.

Data Lakes 52

Data Lakes Cloud Data AWS Data Governance 52

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

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 101

Azure Tableau Data Lakes SQL 101

Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Tableau 101

Tableau Data Lakes Data Warehouse SQL 101

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

Women in Big Data

NOVEMBER 27, 2024

Its PostgreSQL foundation ensures compatibility with most SQL clients. While it shares similarities with PostgreSQL, there are key differences that must be considered during application development. Strengths : High performance with SQL support, easy integration with other AWS services, and strong security features.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

AWS Machine Learning Blog

JANUARY 4, 2024

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing with complex technical code, business users and data analysts can ask questions related to data and insights in plain language.

SQL 131

SQL Database AI AI 131

Tableau

MARCH 29, 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 52

Azure Tableau Data Lakes SQL 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Dataversity

MARCH 12, 2021

blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source devops on the cloud with protected internal legacy tools, SQL with noSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […].

Data Lakes 52

Data Lakes SQL Database Data Science 52

DagsHub

DECEMBER 11, 2023

Dolt Created in 2019, Dolt is an open-source tool for managing SQL databases that uses version control similar to Git. It versions tables instead of files and has a SQL query interface for those tables. However, these tools have functional gaps for more advanced data workflows.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Database 98

Flipboard

DECEMBER 6, 2023

In this post, we discuss a Q&A bot use case that Q4 has implemented, the challenges that numerical and structured datasets presented, and how Q4 concluded that using SQL may be a viable solution. RAG with semantic search – Conventional RAG with semantic search was the last step before moving to SQL generation.

SQL 168

SQL Database AWS Machine Learning 168

Data Science Dojo

JULY 6, 2023

It offers extensibility and integration with various data engineering tools. dbt (Data Build Tool): dbt is an open-source data transformation and modeling tool. It allows data engineers to build, test, and maintain data pipelines in a version-controlled manner.

Data Engineering 195

Data Engineering Data Engineer Data Engineering Data Engineering 195

Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Tableau 52

Tableau Data Lakes Data Warehouse SQL 52

ODSC - Open Data Science

SEPTEMBER 12, 2023

Although setting up a database to run your analyses may seem like an arduous task, modern open-source time series databases can provide significant benefits to any scientist running time series analysis on a large data set — and with much less effort than you might imagine.

Data Scientist 97

Data Scientist Database Data Lakes Data Science 97

Smart Data Collective

FEBRUARY 23, 2022

Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. That is when data lake products started gaining popularity, and since then, more companies introduced lake solutions as part of their data infrastructure. Athena is serverless and managed by AWS.

Data Lakes 106

Data Lakes AWS SQL Big Data 106

Dataversity

JULY 9, 2021

blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source DevOps on the cloud with protected internal legacy tools, SQL with NoSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […].

Azure 52

Azure Data Lakes SQL ML 52

Dataversity

MAY 7, 2021

blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source DevOps on the cloud with protected internal legacy tools, SQL with noSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […].

Data Lakes 52

Data Lakes SQL Database Data Science 52

phData

NOVEMBER 8, 2024

Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It can also be integrated into major data platforms like Snowflake. Contact phData Today!

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

ODSC - Open Data Science

JULY 27, 2023

Choosing a Data Lake Format: What to Actually Look For The differences between many data lake products today might not matter as much as you think. When choosing a data lake, here’s something else to consider. Use this guide to get started with your prompt engineering skills! Register now for 60% off.

Data Lakes 52

Data Lakes AI SQL AI 52

AWS Machine Learning Blog

SEPTEMBER 27, 2024

Amazon Simple Storage Service (Amazon S3) stores the model artifacts and creates a data lake to host the inference output, document analysis output, and other datasets in CSV format. The model is then trained using a fully managed infrastructure, validated, and published to the Amazon SageMaker Model Registry.

AWS 115

AWS Data Lakes ML ML 115

Dataversity

FEBRUARY 2, 2022

blog series, we experiment with the most interesting blends of data and tools. In the “Will They Blend?”

Data Lakes 52

Data Lakes SQL Analytics Analytics 52

Towards AI

NOVEMBER 15, 2024

Resource Creation As Per the Requirements or Project After creating resource groups, we need to create resources that we are going to use to build our data pipelines. Here is the data pipeline building from ADLS to Azure SQL DB. So, We need to create a Storage Account Resource as ADLS, ADF, and then an SQL DB.

Azure 102

Azure Data Engineering Data Engineer Data Engineering 102

Data Science 101

NOVEMBER 11, 2019

Azure Synapse Analytics This is the future of data warehousing. It combines data warehousing and data lakes into a simple query interface for a simple and fast analytics service. SQL Server 2019 SQL Server 2019 went Generally Available.

Cloud Data 95

Cloud Data Data Science Azure Clustering 95

SAS Software

NOVEMBER 29, 2023

Azure Data Lake Storage (ADLS) Gen2のストレージアカウントの作成 3-2.ストレージアカウントのデータストレージコンテナの作成 Azure SynapseのSQLデータベースをSASライブラリとして定義 4-3.Azure Bulkload機能について 3.BULKLOAD機能を利用するためのAzure側で必要なサービスの作成 BULKLOAD機能を利用するためのAzure側で必要なサービスの作成 3-1.Azure ストレージアカウントのデータストレージコンテナの作成 3-3.ストレージアカウントの利用ユーザー権限の設定 ストレージアカウントの利用ユーザー権限の設定 3-4.データ書き込み用のSASコードの実行

Azure 59

Azure Data Lakes SQL Analytics 59

AWS Machine Learning Blog

NOVEMBER 12, 2024

NOTE : Since we used an SQL query engine to query the dataset for this demonstration, the prompts and generated outputs mention SQL below. The question in the preceding example doesn’t require a lot of complex analysis on the data returned from the ETF dataset. A user can ask a business- or industry-related question for ETFs.

SQL 97

SQL AWS AI AI 97

IBM Journey to AI blog

APRIL 24, 2023

A data lakehouse contains an organization’s data in a unstructured, structured, semi-structured form, which can be stored indefinitely for immediate or future use. This data is used by data scientists and engineers who study data to gain business insights.

Data Warehouse 123

Data Warehouse Data Lakes Artificial Intelligence Artificial Intelligence 123