The MLOps Blog

MARCH 21, 2023

Your data scientists develop models on this component, which stores all parameters, feature definitions, artifacts, and other experiment-related information they care about for every experiment they run. Machine Learning Operations (MLOps): Overview, Definition, and Architecture (by Kreuzberger, et al., AIIA MLOps blueprints.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69

IBM Journey to AI blog

JULY 16, 2024

In addition to its mainframe, the bank has a strong relationship with Microsoft and leverages Microsoft Azure cloud platform to extend its IT infrastructure. By using Azure, the bank can quickly respond to changing market conditions and customer needs, while also reducing its IT costs and improving its overall operational efficiency.

Azure 40

Azure Clustering AI AI 40

Data Science Blog

NOVEMBER 15, 2023

So whenever you hear that Process Mining can prepare RPA definitions you can expect that Task Mining is the real deal. on Microsoft Azure, AWS, Google Cloud Platform or SAP Dataverse) significantly improve data utilization and drive effective business outcomes. DATANOMIQ Data Mesh Cloud Architecture – This image is animated!

Data Modeling 245

Data Modeling Data Models Business Intelligence Business Intelligence 245

Flipboard

JANUARY 26, 2023

Its enterprise clients drive the vast majority of its revenue, through products like Microsoft 365 and Azure. The company also recently published a paper outlining its approach to AI and how important it is for that approach to be responsible (or Google’s definition of responsible, given the lack of government regulations).

Azure 153

Azure AI AI Artificial Intelligence 153

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

phData

SEPTEMBER 26, 2023

According to Microsoft, when you are designing a paginated report, you are creating a report definition that specifies where to get the data (i.e., The report definition is a template for your report’s look and how you want it to work. Then, when an end user runs the report, that definition/template is populated with data.

Power BI 64

Power BI SQL Azure Database 64

ODSC - Open Data Science

FEBRUARY 2, 2023

Much of what we found was to be expected, though there were definitely a few surprises. This will be a major theme moving forward, and is something definitely not seen 10 years ago. 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

JUNE 8, 2023

The only file type that Report Builder can open is.rdl (report definition language). Without Report Builder, you are not able to create paginated reports or edit existing ones within the Power Platform ecosystem.

Power BI 90

Power BI SQL Azure Database 90

Hacker News

JULY 18, 2023

If you have a smaller number of large tenants (B2B), and some require a custom table definition or permissions, then schema-based sharding is also a great fit. is just released, it is not yet available on Azure but it will be soon. Oh, and there is a free trial , too. This article was originally published on citusdata.com.

Database 123

Database SQL Data Modeling Data Models 123

DagsHub

JULY 25, 2024

Tutorials Microsoft Azure Machine Learning Microsoft Azure Machine Learning (Azure ML) is a cloud-based platform for building, training, and deploying machine learning models. Azure ML integrates seamlessly with other Microsoft Azure services, offering scalability, security, and advanced analytics capabilities.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

phData

MAY 10, 2024

During deployment: Download the manifest.json of the previous deployment from storage (AWS or Azure) and save it under the Airflows dags directory. Generates the manifest.json of the current state and uploads to storage (AWS or Azure). Download the manifest.json of the previous deployment from Azure storage.

Azure 52

Azure Database AWS Python 52

Mlearning.ai

JULY 9, 2023

I then posted it on github built the app on Azure web pages. It gives us this final result: Conclusion The app definitely isn’t perfect. After scaling the data, I used the XGBoost algorithm to train the model to classify the data and joblib to save the model.

Algorithm 52

Algorithm Azure Clustering ML 52

ODSC - Open Data Science

JUNE 12, 2023

A quick search on the Internet provides multiple definitions by technology-leading companies such as IBM, Amazon, and Oracle. Power BI Datamarts provide no-code/low-code datamart capabilities using Azure SQL Database technology in the background. What is a Datamart?

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

IBM Journey to AI blog

AUGUST 15, 2023

Representation of action liveness Then this definition is applied in the savings workflow: Once an action is executed on a cloud resource, it is actively tracked and we await confirmation of its successful implementation. It also captures the impact from optimizing popular PaaS services like Azure App Service.

Azure 73

Azure Database 73

How to Learn Machine Learning

APRIL 26, 2025

This definition specifically describes the Data Scientist as being the predictive powerhouse of the data science ecosystem. Data Scientist: The Predictive Powerhouse The pure data scientists are the most demanded within all the Data Science career paths.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Data Science 101

AUGUST 30, 2023

“Definitely – now it [programmer] seems like an obvious career choice. Definitely – now it seems like an obvious career choice. Threads Dev Interviews I am finding developers on Threads and interviewing them, right on Threads. Back then it really wasn’t that popular. Very nice, that makes sense.

Computer Science 111

Computer Science Computer Science Azure AWS 111

DrivenData Labs

MAY 21, 2024

Hello from our new, friendly, welcoming, definitely not an AI overlord cookie logo! We have now added support for Azure and GCS as well. The vision for V2 is to give CCDS users more flexibility while still making a great template if you just put your hand over your eyes and hit enter.

Data Science 233

Data Science Python Data Scientist Data Warehouse 233

O'Reilly Media

OCTOBER 19, 2021

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments.

ML 145

ML ML Data Scientist AWS 145

The MLOps Blog

JULY 18, 2024

Médéric told me that over the past few years, he explored various MLOps platforms and earned certifications on GCP , Databricks , and Azure to compare their user experience and advise his customers. For example, Databricks has a certain definition of URL and payload to interact with model endpoints.

ML 64

ML ML Data Scientist Azure 64

Hacker News

FEBRUARY 8, 2024

There are also well-founded worries about the security of the Azure cloud. Another reaction has been that I treat Docker unfairly, and that you could definitely use containers for good. Yet in the past year, we’ve learned that Microsoft’s email platform was thoroughly hacked , including classified government email.

Azure 181

Azure Cloud Computing AWS Python 181

ODSC - Open Data Science

MAY 29, 2023

Discrete data approaches are limited by definition while analyzing interconnections is fundamental to understanding complex interactions and behaviors. Collaborate and streamline the management of thousands of models across teams with new, innovative features in Azure Machine Learning.

Machine Learning 52

Machine Learning Machine Learning Data Science AI 52

ODSC - Open Data Science

MARCH 8, 2024

Definition Embedding is a process of transforming data into numerical vectors and it is used to represent text, images, audio, or other complex data types in a multi-dimensional space that preserves the semantic similarity and relevance of the original data. This step involves the concept of embedding.

Azure 52

Azure Data Science AI AI 52

Flipboard

JULY 7, 2023

And this is definitely not a case that anybody knows about. And even though OpenAI uses Azure, it’s not through this HIPAA-controlled process. And that was particularly mind-blowing because as a researcher in AI and as someone who understood how a transformer model works, where the hell was it getting this? I never published this case.

AI 168

AI AI Computer Science Computer Science 168

Pickl AI

JULY 27, 2023

Data Definition: SQL enables users to create and modify the structure of the database. Data Integrity: SQL allows the definition of constraints on the data to enforce data integrity. The main data manipulation commands are INSERT (for adding new records), UPDATE (for modifying existing records), and DELETE (for removing records).

SQL 52

SQL Database Azure Data Science 52

ODSC - Open Data Science

FEBRUARY 28, 2023

If this definition is taken as a basis, it can actually be argued that a system like ChatGPT fulfills this in many cases. The giant Microsoft is entering into a strategic partnership with the dwarf OpenAI to offer its systems on Microsoft’s Azure cloud platform. This is illustrated in Figure 5. So, it is all just exciting and great?

AI 105

AI AI Data Science Artificial Intelligence 105

phData

SEPTEMBER 15, 2023

Salesforce Sync Out is a crucial tool that enables businesses to transfer data from their Salesforce platform to external systems like Snowflake, AWS S3, and Azure ADLS. What is Salesforce Sync Out? The Salesforce Sync Out connector moves Salesforce data directly into Snowflake, simplifying the data pipeline and reducing latency.

Data Warehouse 52

Data Warehouse Tableau Data Silos Analytics 52

Pickl AI

JANUARY 31, 2025

As we delve into the world of cloud computing, we will explore its definitions, types, benefits, challenges, and future trends. Examples include Amazon Web Services (AWS) EC2 and Microsoft Azure. Examples include AWS Lambda and Azure Functions. Key Takeaways Cost efficiency transforms fixed costs into variable expenses.

Cloud Computing 52

Cloud Computing Azure Artificial Intelligence Artificial Intelligence 52

ODSC - Open Data Science

JANUARY 29, 2024

We don’t claim this is a definitive analysis but rather a rough guide due to several factors: Job descriptions show lagging indicators of in-demand prompt engineering skills, especially when viewed over the course of 9 months. The definition of a particular job role is constantly in flux and varies from employer to employer.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

IBM Journey to AI blog

JANUARY 18, 2023

This is an architecture that’s well suited for the cloud since AWS S3 or Azure DLS2 can provide the requisite storage. It can include technologies that range from Oracle, Teradata and Apache Hadoop to Snowflake on Azure, RedShift on AWS or MS SQL in the on-premises data center, to name just a few. Differences exist also.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Alation

NOVEMBER 15, 2021

A key part of the framework is the definition of 14 key controls and capabilities. The Snowflake data sources were multi-cloud (Azure, AWS, GCP) running in different regions around the world. The working group produced a new Cloud Data Management Framework for sensitive data, which was announced earlier this month.

Cloud Data 52

Cloud Data Tableau Azure Analytics 52

phData

JUNE 25, 2024

Snowpark Container Services is GA Snowpark Container Services (SPCS) is now Generally Available on AWS (and soon on Azure). The Git Integration works by syncing repositories to a Snowflake Stage (object store, akin to Amazon S3 or Azure ADLS). Synced code can then be edited in a Snowflake Worksheet or Notebook.

Data Scientist 52

Data Scientist ML ML Data Science 52

Pickl AI

AUGUST 30, 2024

Summary: This article provides a comprehensive overview of data migration, including its definition, importance, processes, common challenges, and popular tools. Microsoft Azure Data Factory A cloud-based data integration service that allows users to create data-driven workflows for orchestrating data movement and transformation.

Data Quality 52

Data Quality Data Governance Azure Database 52

Pickl AI

JUNE 7, 2024

Definition and Explanation of the ETL Process ETL is a data integration method that combines data from multiple sources. Azure Data Factory Azure Data Factory is a cloud-based ETL service offered by Microsoft that facilitates the creation of data workflows for moving and transforming data at scale.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Pickl AI

DECEMBER 16, 2024

Definition and Core Components Microsoft Fabric is a unified solution integrating various data services into a single ecosystem. Definition and Functionality Power BI is much more than a tool for creating charts and graphs. It handles data ingestion, transformation, storage, and advanced analytics within a unified platform.

Power BI 52

Power BI Analytics Analytics Machine Learning 52

Pickl AI

AUGUST 27, 2024

In this blog, we will delve into the world of serverless computing, exploring its definition, benefits, use cases, challenges, practical implementations, and the future outlook. Serverless Functions Serverless functions, such as AWS Lambda, Azure Functions, and Google Cloud Functions, are the building blocks of serverless applications.

Cloud Computing 52

Cloud Computing Analytics Analytics Azure 52

The MLOps Blog

MARCH 20, 2023

Tools such as AWS S3, Google Cloud Storage, and Microsoft Azure offer robust recovery solutions allowing data snapshots to be recovered at a specific time. Read more How to Version and Compare Datasets in neptune.ai Features / Considerations DVC MLflow Databricks Weights & Biases DagsHub neptune.ai

ML 59

ML ML Machine Learning Machine Learning 59

Mlearning.ai

JUNE 23, 2023

Another definition: A vector DB allow us to search across unstructured data by their content. For example : Below image depicts how we would store student course database. A new database — Vector Database A vector DB indexes and searches vector embeddings for faster and similarity search.

Database 52

Database ML ML Natural Language Processing 52