Announcing the General Availability of Databricks SQL Serverless !
databricks
MAY 18, 2023
Today, we are thrilled to announce that serverless compute for Databricks SQL is Generally Available on AWS and Azure! Databricks SQL (DB SQL).
This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
databricks
MAY 18, 2023
Today, we are thrilled to announce that serverless compute for Databricks SQL is Generally Available on AWS and Azure! Databricks SQL (DB SQL).
databricks
AUGUST 13, 2024
Databricks SQL Serverless is now Generally Available on Google Cloud Platform (GCP)! SQL Serverless is available in 7 GCP regions and 40+ regions across AWS, Azure and GCP.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
databricks
NOVEMBER 5, 2024
We’re excited to announce that materialized views (MVs) and streaming tables (STs) are now Generally Available in Databricks SQL on AWS and Azure.
databricks
MARCH 6, 2023
Today, we are excited to announce the public preview of the Databricks SQL Statement Execution API, available on AWS and Azure. You can.
databricks
JUNE 27, 2023
We are thrilled to announce that materialized views and streaming tables are now publicly available in Databricks SQL on AWS and Azure. Streaming.
databricks
OCTOBER 13, 2023
Today, we are excited to announce the general availability of the Databricks SQL Statement Execution API on AWS and Azure, with support for.
databricks
AUGUST 2, 2023
We're excited to share a new set of security controls and compliance certifications that can help with regulatory compliance on Azure Databricks and.
databricks
APRIL 17, 2024
The next generation of Databricks SQL dashboards, also known as Lakeview Dashboards, is now generally available on AWS and Azure. This new dashboarding experience is optimized for ease of use, scalable and secure distribution, governance, and performance.
Data Science Blog
SEPTEMBER 19, 2023
The following Terraform script will create an Azure Resource Group, a SQL Server, and a SQL Database. Of course, Terraform and the Azure CLI needs to be installed before. Min Pool Size=0;Max Pool Size=30;Persist Security Info=true;`; }); Running the script will need the installation of Python, Pulumi and the Azure CLI.
Data Science Dojo
OCTOBER 31, 2024
Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Additionally, knowledge of cloud platforms (AWS, Google Cloud) and experience with deployment tools (Docker, Kubernetes) are highly valuable. Familiarity with machine learning, algorithms, and statistical modeling.
AWS Machine Learning Blog
MARCH 10, 2025
We walk through the journey Octus took from managing multiple cloud providers and costly GPU instances to implementing a streamlined, cost-effective solution using AWS services including Amazon Bedrock, AWS Fargate , and Amazon OpenSearch Service. Along the way, it also simplified operations as Octus is an AWS shop more generally.
Data Science 101
NOVEMBER 11, 2019
Microsoft Azure. Azure Arc You can now run Azure services anywhere (on-prem, on the edge, any cloud) you can run Kubernetes. Azure Synapse Analytics This is the future of data warehousing. SQL Server 2019 SQL Server 2019 went Generally Available. It can be used to do distributed Machine Learning on AWS.
Data Science 101
NOVEMBER 7, 2019
Azure Synapse. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. R Support for Azure Machine Learning. Azure Quantum.
Data Science 101
FEBRUARY 29, 2020
Google Announces Cloud SQL for Microsoft SQL Server Google’s Cloud SQL now supports SQL Server in addition to PostgreSQL and MySQL Google Opens a new Cloud Region Located in Salt Lake City, Utah, it is named us-west3. Azure Sphere for IoT security goes GA This is a comprehensive security solution for IoT.
Data Science Connect
JANUARY 27, 2023
Learn SQL: As a data engineer, you will be working with large amounts of data, and SQL is the most commonly used language for interacting with databases. Understanding how to write efficient and effective SQL queries is essential.
Data Science Blog
MAY 15, 2023
Data Lakehouses werden auf Cloud-basierten Objektspeichern wie Amazon S3 , Google Cloud Storage oder Azure Blob Storage aufgebaut. Data Warehouses wurden entwickelt, um strukturierte Daten aus Transaktionssystemen in einem zentralen Repository zu speichern, wo sie mit SQL-basierten Tools bereinigt, umgewandelt und analysiert werden konnten.
Pickl AI
APRIL 6, 2023
Accordingly, one of the most demanding roles is that of Azure Data Engineer Jobs that you might be interested in. The following blog will help you know about the Azure Data Engineering Job Description, salary, and certification course. How to Become an Azure Data Engineer?
Mlearning.ai
APRIL 24, 2023
I just finished learning Azure’s service cloud platform using Coursera and the Microsoft Learning Path for Data Science. In my last consulting job, I was asked to do tasks that Data Factory and Form Recognizer can easily do for AWS/Amazon cloud services. It will take a couple of months but it is worth it!
Data Science 101
NOVEMBER 29, 2019
Amazon Athena and Aurora add support for ML in SQL Queries You can now invoke Machine Learning models right from your SQL Queries. Use Amazon Sagemaker to add ML predictions in Amazon QuickSight Amazon QuickSight, the AWS BI tool, now has the capability to call Machine Learning models.
Data Science Blog
NOVEMBER 15, 2023
Example Event Log for Process Mining The following example SQL-query is inserting Event-Activities from a SAP ERP System into an existing event log database table. on Microsoft Azure, AWS, Google Cloud Platform or SAP Dataverse) significantly improve data utilization and drive effective business outcomes. Click to enlarge!
Pickl AI
NOVEMBER 18, 2024
Industry-recognised certifications, like IBM and AWS, provide credibility. Software like Microsoft Excel and SQL helps them manipulate and query data efficiently. Additionally, familiarity with Machine Learning frameworks and cloud-based platforms like AWS or Azure adds value to their expertise. Who is a Data Analyst?
Smart Data Collective
APRIL 29, 2020
Redshift is the product for data warehousing, and Athena provides SQL data analytics. AWS Glue helps users to build data catalogues, and Quicksight provides data visualisation and dashboard construction. The services from AWS can be catered to meet the needs of each business user. Microsoft Azure. SharePoint.
Smart Data Collective
SEPTEMBER 8, 2021
Azure Data Factory : This is a fully managed service that connects to a wide range of On-Premise and Cloud sources. It can easily transform, copy, and enrich the data, finally writing it to Azure data services as a destination. Azure Data Factory also supports Spark, Hadoop, and Machine Learning as transformation steps.
Smart Data Collective
OCTOBER 19, 2022
You can only deploy DynamoDB on Amazon Web Services (AWS), and it does not support on-premise deployments. With DynamoDB, you are essentially locked into AWS as your cloud provider. MongoDB is deployable anywhere, and the MongoDB Atlas database-as-a-service can be deployed on AWS, Azure, and Google Cloud Platform (GCP).
O'Reilly Media
SEPTEMBER 15, 2021
Cloud certifications, specifically in AWS and Microsoft Azure, were most strongly associated with salary increases. As we’ll see later, cloud certifications (specifically in AWS and Microsoft Azure) were the most popular and appeared to have the largest effect on salaries. The top certification was for AWS (3.9%
Women in Big Data
NOVEMBER 27, 2024
Decide between cloud-based solutions, such as AWS Redshift or Google BigQuery, and on-premises options, while considering scalability and whether a hybrid approach might be beneficial. Its PostgreSQL foundation ensures compatibility with most SQL clients.
Data Science Dojo
JULY 3, 2024
Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Databases and SQL : Managing and querying relational databases using SQL, as well as working with NoSQL databases like MongoDB.
Data Science Blog
SEPTEMBER 3, 2024
Während vor zehn Jahren ich für Celonis noch eine Installation erst einer MS SQL Server Datenbank, etwas später dann bevorzugt eine SAP Hana Datenbank auf einem on-prem Server beim Kunden voraussetzend installieren musste, bevor ich dann zur Installation der Celonis ServerAnwendung selbst kam, ist es heute eine 100% externe Cloud-Lösung.
phData
MAY 25, 2023
In a perfect world, Microsoft would have clients push even more storage and compute to its Azure Synapse platform. Snowflake was originally launched in October 2014, but it wasn’t until 2018 that Snowflake became available on Azure. This ensures the maximum amount of Snowflake consumption possible.
ODSC - Open Data Science
FEBRUARY 2, 2023
While knowing Python, R, and SQL are expected, you’ll need to go beyond that. As you’ll see in the next section, data scientists will be expected to know at least one programming language, with Python, R, and SQL being the leaders. Cloud Services The only two to make multiple lists were Amazon Web Services (AWS) and Microsoft Azure.
Analytics Vidhya
MARCH 8, 2023
The Biggest Data Science Blogathon is now live! Knowledge is power. Sharing knowledge is the key to unlocking that power.”― Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon.
Analytics Vidhya
JANUARY 8, 2023
Hey, are you the data science geek who spends hours coding, learning a new language, or just exploring new avenues of data science? If all of these describe you, then this Blogathon announcement is for you! Analytics Vidhya is back with its 28th Edition of blogathon, a place where you can share your knowledge about […].
phData
APRIL 29, 2024
SQL Server – The SQL Server connector, another widely-used database-type connector, provides similar functionality but is tailored for Microsoft’s SQL Server. Our team frequently configures Fivetran connectors to cloud object storage platforms such as Amazon S3, Azure Blob Storage, and Google Cloud Storage.
Becoming Human
MAY 15, 2023
One is a scripting language such as Python, and the other is a Query language like SQL (Structured Query Language) for SQL Databases. There is one Query language known as SQL (Structured Query Language), which works for a type of database. SQL Databases are MySQL , PostgreSQL , MariaDB , etc.
Pickl AI
DECEMBER 25, 2024
Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Data Analysts dive deeper into raw data, using tools like Excel, Tableau, and SQL to create reports and dashboards. These tools enable professionals to turn raw data into digestible insights quickly.
Analytics Vidhya
FEBRUARY 19, 2023
Introduction Google’s BigQuery is a powerful cloud-based data warehouse that provides fast, flexible, and cost-effective data storage and analysis capabilities. One of its unique features is the ability to build and run machine learning models directly inside the database without extracting the data and moving it to another platform.
phData
NOVEMBER 8, 2024
Cost Efficiency and Scalability Open Table Formats are designed to work with cloud storage solutions like Amazon S3, Google Cloud Storage, and Azure Blob Storage, enabling cost-effective and scalable storage solutions. Amazon S3, Azure Data Lake, or Google Cloud Storage).
ODSC - Open Data Science
APRIL 3, 2023
The Modern Data Stack: Apache Spark, Google Bigquery, Oracle Database, Microsoft SQL Server, Snowflake The modern data stack continues to have a big impact, and data analytics roles are no exception. Cloud Services: Google Cloud Platform, AWS, Azure.
IBM Journey to AI blog
SEPTEMBER 11, 2023
Boyce to create Structured Query Language (SQL). Developers can leverage features like REST APIs, JSON support and enhanced SQL compatibility to easily build cloud-native applications. Db2 can run on Red Hat OpenShift and Kubernetes environments, ROSA & EKS on AWS, and ARO & AKS on Azure deployments.
phData
FEBRUARY 14, 2023
If using a network policy with Snowflake, be sure to add Fivetran’s IP address list , which will ensure Azure Data Factory (ADF) Azure Data Factory is a fully managed, serverless data integration service built by Microsoft. Tips When Considering ADF: ADF will only write to Snowflake accounts that are based in Azure.
phData
MARCH 22, 2024
In this blog, we will review the steps to create Snowflake-managed Iceberg tables with AWS S3 as external storage and read them from a Spark or Databricks environment. Externally Managed Iceberg Tables – An external system, such as AWS Glue , manages the metadata and catalog. These tables support read-only access from Snowflake.
ODSC - Open Data Science
FEBRUARY 17, 2023
Knowing some SQL is also essential. AWS Cloud, Azure Cloud, and others are all compatible with many other frameworks and languages, making them necessary for any NLP skill set. Many popular NLP frameworks, such as NLTK and spaCy, are Python-based, so it makes sense to be an expert in the accompanying language.
Mlearning.ai
MAY 23, 2023
Familiarity with libraries like pandas, NumPy, and SQL for data handling is important. Check out this course to upskill on Apache Spark — [link] Cloud Computing technologies such as AWS, GCP, Azure will also be a plus. This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA).
Cambridge Intelligence
OCTOBER 19, 2023
In this post, we’ll take a look at some of the factors you could investigate, and introduce the six databases our customers work with most often: Amazon Neptune ArangoDB Azure Cosmos DB JanusGraph Neo4j TigerGraph Why these six graph databases? Relational databases (with recursive SQL queries), document stores, key-value stores, etc.,
Expert insights. Personalized for you.
We have resent the email to
Are you sure you want to cancel your subscriptions?
Let's personalize your content