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!

Azure 52

Azure SQL Database Python 52

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 Engineering 130

Data Engineering Data Engineer Data Engineering Data Engineering 130

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.

Cloud Data 95

Cloud Data Data Science Azure Clustering 95

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.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

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.

SQL 52

SQL Azure Data Warehouse Cloud Data 52

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 106

Data Science Azure SQL Machine Learning 106

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.

Cloud Data 106

Cloud Data Data Science SQL Deep Learning 106

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.

SQL 52

SQL AWS Database Data Lakes 52

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.

Cloud Data 115

Cloud Data Data Science Machine Learning Machine Learning 115

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 Warehouse 259

Data Warehouse Azure SQL Database 259

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.

Data Warehouse 84

Data Warehouse SQL Azure ETL 84

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.

Analytics 52

Analytics Analytics Data Analyst SQL 52

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).

Data Science 52

Data Science Data Scientist Apache Hadoop Machine Learning 52

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).

Big Data 112

Big Data Big Data Database AWS 112

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.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

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.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

Pickl AI

APRIL 26, 2024

It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques. Key Takeaways SQL Mastery: Understand SQL’s importance, join tables, and distinguish between SELECT and SELECT DISTINCT. How do you join tables in SQL?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

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%

AI 145

AI AI Azure AWS 145

phData

FEBRUARY 3, 2023

The second task requires you to code another solution using SQL. Data Engineer “During my Codility interview, I was given a Python, SQL, and AWS problems to solve. The AWS portion was multiple choice and the Python and SQL portions were coding challenges in codility’s IDE. ” Zach Golden - Sr.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Cloud Platforms: AWS, Azure, Google Cloud, etc. ETL Tools: Apache NiFi, Talend, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Towards AI

SEPTEMBER 26, 2023

The AI race is heating up further, and now it looks like the leading cloud providers have lined up their key LLM labs partners with Google Cloud behind Deepmind, Microsoft Azure backing OpenAI, and Amazon AWS backing Anthropic. Amazon Web Services (AWS) will be the primary cloud provider for Anthropic.

AI 64

AI AI AWS Artificial Intelligence 64

phData

SEPTEMBER 19, 2023

Thankfully, there are tools available to help with metadata management, such as AWS Glue, Azure Data Catalog, or Alation, that can automate much of the process. There are tools designed specifically to analyze your data lake files, determine the schema, and allow for SQL statements to be run directly off this data.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

ODSC - Open Data Science

JANUARY 18, 2024

These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. Microsoft Azure in particular allows users to explore the Azure ecosystem and provides on-site training for users of all levels. Learn more about the cloud.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

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.

Deep Learning 111

Deep Learning Deep Learning Data Science Natural Language Processing 111

ODSC - Open Data Science

JUNE 8, 2023

We had bigger sessions on getting started with machine learning or SQL, up to advanced topics in NLP, and how to make deepfakes. Shoutout to Microsoft Azure, Oracle Cloud + NVIDIA, Red Hat, Taipy, WGU, dotData, iguazio, and everyone else who helped make the expo hall a success!

Data Science 52

Data Science Machine Learning Machine Learning ML 52

phData

DECEMBER 1, 2023

Depending on the requirements, it could involve developing Python/Scala/SQL programs on AWS/Azure/Snowflake cloud platforms and setting up CI/CD pipelines for the seamless deployment of the project code. Yes, you heard that right. I do write code daily. How do you like working for a consulting company?

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

MAY 17, 2023

Understand Databases: SQL is useful in handling structured data, query databases and prepare and experiment with data. Accordingly, SQL is deployed alongside Python and its libraries thus, requiring you to develop your skills in using SQL. It will help you work with large datasets better and more efficiently.

Data Scientist 52

Data Scientist Data Science Data Wrangling SQL 52

Mlearning.ai

MARCH 15, 2023

Familiarity with Databases; SQL for structured data, and NOSQL for unstructured data. Experience with cloud platforms like; AWS, AZURE, etc. Technical requirements for a Data Scientist High expertise in programming either in R or Python, or both. Experience with visualization tools like; Tableau and Power BI.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

Mlearning.ai

JUNE 23, 2023

Relational databases (like MySQL) or No-SQL databases (AWS DynamoDB) can store structured or even semi-structured data but there is one inherent problem. A database that help index and search at blazing speed. Unstructured data is hard to store in relational databases.

Database 52

Database ML ML Natural Language Processing 52

ODSC - Open Data Science

JANUARY 29, 2024

SQL SQL’s importance stems from its role in data handling, and prompt engineers often need to query and manage large datasets, for which SQL is the standard language. You may be expected to use other cloud platforms like AWS, GCP, and others, so don’t neglect them and at least be vaguely familiar with how they work.

Machine Learning 52

Machine Learning Machine Learning Data Science Natural Language Processing 52

The MLOps Blog

JANUARY 23, 2023

It supports most major cloud providers, such as AWS, GCP, and Azure. datasets/images" ) In order to store artifacts from Amazon S3, we need to configure an IAM policy with “S3ReadAccessOnly” permissions and store our credentials for AWS as environment variables. size: Size of the file, in kilobytes.

ML 52

ML ML Data Lakes Machine Learning 52

phData

JULY 10, 2023

These files need to be in one of the Snowflake-supported cloud systems: Amazon S3, Google Cloud Storage, or Microsoft Azure Blob storage. Cost Efficiency: Storing data in Snowflake’s native storage is typically more expensive than storing data in cloud storage services like Amazon S3 or Azure Blob Storage.

Data Lakes 40

Data Lakes Azure Database AWS 40

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.

Data Science 319

Data Science Analytics Analytics Apache Hadoop 319

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 […].

Data Science 308

Data Science Analytics Analytics Hadoop 308

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.

Machine Learning 264

Machine Learning Machine Learning Data Warehouse Database 264

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.

Power BI 84

Power BI Analytics Analytics Azure 84

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!

Data Modeling 245

Data Modeling Data Models Business Intelligence Business Intelligence 245