Data Science 101

NOVEMBER 15, 2019

Here are this weeks major announcements and news for doing data science in the cloud. Microsoft Azure. Microsoft and Salesforce form Partnership While not just for data science, this is big news. Azure has become the cloud provider for the Salesforce marketing cloud. Amazon AWS.

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Data Science 101

JANUARY 17, 2020

Azure Machine Learning Datasets Learn all about Azure Datasets, why to use them, and how they help. AI Powered Speech Analytics for Amazon Connect This video walks thru the AWS products necessary for converting video to text, translating and performing basic NLP. Some news this week out of Microsoft and Amazon.

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Data Science 101

NOVEMBER 22, 2019

Here are this week’s news and announcements related to Cloud Data Science. Google is launching Explainable AI which quantifies the impact of the various factors of the data as well as the existing limitations. AWS Storage Day On November 20, 2019, Amazon held AWS Storage Day. Announcements. Fascinating Stuff!

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Data Science 101

FEBRUARY 29, 2020

Lots of announcements this week, so without delay, let’s get right to Cloud Data Science 9. 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.

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Data Science 101

NOVEMBER 29, 2019

Sign Up for the Cloud Data Science Newsletter. 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. Azure Machine Learning Compute Instance What used to be called Notebook VMs, are now Compute Instances. Announcements.

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Data Science 101

MARCH 14, 2020

Even with the coronavirus causing mass closures, there are still some big announcements in the cloud data science world. Google introduces Cloud AI Platform Pipelines Google Cloud now provides a way to deploy repeatable machine learning pipelines. Azure Functions now support Python 3.8 So, here is the news.

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Data Science 101

JANUARY 6, 2020

As 2020 begins, there has been limited cloud data science announcements so I put together some predictions. Cloud Collaboration. I think we are going to see more interoperability between the major cloud providers. It only makes sense for the big cloud providers to start working with each other.

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Data Science 101

DECEMBER 27, 2019

AWS Deep Learning Containers now support Tensorflow 2.0 AWS Deep Learning Containers are docker images which are preconfigured for deep learning tasks. An intro to Azure FarmBeats An innovative idea to bring data science to farmers. It is called data-driven agriculture. It is called data-driven agriculture.

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Data Science 101

DECEMBER 16, 2019

Even though Amazon is taking a break from announcements (probably focusing on Christmas shoppers), there are still some updates in the cloud data science world. Azure Database for MySQL now supports MySQL 8.0 This is the latest major version of MySQL Azure Functions 3.0 Azure Database for MySQL now supports MySQL 8.0

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Data Science 101

DECEMBER 6, 2019

This week Amazon hosted the large AWS re:Invent Conference. Netflix and AWS open source Metaflow Making it easy to build and manage real-life data science projects. AWS re:Invent Machine Learning Announcements AWS CEO details all of the Machine Learning announcements during his keynote. Announcements.

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Data Science 101

FEBRUARY 7, 2020

All the large cloud providers had some announcements this past week, plus a global artificial intelligence organization had some news to share. Azure Stream Analytics Anomaly Detection Azure Stream Analytics now has built-in anomaly detection capabilities. The post Cloud Data Science 6 appeared first on Data Science 101.

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Data Science Blog

JULY 23, 2023

One of this aspect is the cloud architecture for the realization of Data Mesh. Data Mesh on Azure Cloud with Databricks and Delta Lake for Applications of Business Intelligence, Data Science and Process Mining. It offers robust IoT and edge computing capabilities, advanced data analytics, and AI services.

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Data Science 101

JANUARY 10, 2020

Data Drift Monitoring for Azure ML Datasets Azure ML now provides monitoring for when your data changes (called data drift). Data Drift Monitoring for Azure ML Datasets Azure ML now provides monitoring for when your data changes (called data drift). Courses & Learning.

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Data Science 101

NOVEMBER 7, 2019

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Azure Synapse. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Azure Quantum.

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Pickl AI

DECEMBER 26, 2024

Each platform offers unique capabilities tailored to varying needs, making the platform a critical decision for any Data Science project. Major Cloud Platforms for Data Science Amazon Web Services ( AWS ), Microsoft Azure, and Google Cloud Platform (GCP) dominate the cloud market with their comprehensive offerings.

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Data Science 101

MARCH 14, 2020

Even with the coronavirus causing mass closures, there are still some big announcements in the cloud data science world. Google introduces Cloud AI Platform Pipelines Google Cloud now provides a way to deploy repeatable machine learning pipelines. Azure Functions now support Python 3.8 So, here is the news.

Cloud Data 52

Cloud Data Data Science Data Warehouse Azure 52

IBM Journey to AI blog

FEBRUARY 2, 2023

These developments have accelerated the adoption of hybrid-cloud data warehousing; industry analysts estimate that almost 50% 2 of enterprise data has been moved to the cloud. What is holding back the other 50% of datasets on-premises? However, a more detailed analysis is needed to make an informed decision.

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Dataconomy

JUNE 16, 2023

Gamma AI is a great tool for those who are looking for an AI-powered cloud Data Loss Prevention (DLP) tool to protect Software-as-a-Service (SaaS) applications. The business’s solution makes use of AI to continually monitor personnel and deliver event-driven security awareness training in order to prevent data theft.

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Data Science Blog

NOVEMBER 15, 2023

They enable quicker data processing and decision-making, support advanced analytics and AI with standardized data formats, and are adaptable to changing business needs. DATANOMIQ Data Mesh Cloud Architecture – This image is animated! Central data models in a cloud-based Data Mesh Architecture (e.g.

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Flipboard

MARCH 22, 2023

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science.

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Alation

NOVEMBER 15, 2021

In 2019 the EDM Council decided that a new extension for managing sensitive data in the cloud was required, so they created the Cloud Data Management Capability (CDMC) working group. The working group produced a new Cloud Data Management Framework for sensitive data, which was announced earlier this month.

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phData

MARCH 20, 2023

The discussion points in this interview will include a review of your current experience as it relates to cloud data engineering and solution engineering. We pay for your technology certifications (AWS, Azure, Snowflake , etc.) This person will also discuss the daily duties of this role.

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Alation

NOVEMBER 11, 2021

Therefore, the question is not if a business should implement cloud data management and governance, but which framework is best for them. Whether you’re using a platform like AWS, Google Cloud, or Microsoft Azure, data governance is just as essential as it is for on-premises data.

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Smart Data Collective

APRIL 29, 2020

Usually the term refers to the practices, techniques and tools that allow access and delivery through different fields and data structures in an organisation. Data management approaches are varied and may be categorised in the following: Cloud data management. Master data management. Microsoft Azure.

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Dataconomy

SEPTEMBER 4, 2023

Dependency on service providers : Relying on third-party cloud service providers means your operations are dependent on their uptime and reliability. Downtime, like the AWS outage in 2017 that affected several high-profile websites, can disrupt business operations. Ensure that data is clean, consistent, and up-to-date.

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Smart Data Collective

NOVEMBER 15, 2022

Most cloud storage providers offer some kind of sharing feature that allows you to send a link to a file or folder to another person with just a few clicks. Where is Your Cloud Data Stored? The thing about cloud managed services is that they are often spread out across multiple servers in multiple locations.

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Smart Data Collective

JANUARY 10, 2023

Every company should clearly understand and plan in detail how the received data will be used further, how it can be distributed, and who will get access to it. Ensure cloud data storage. For enjoying all the benefits that IoT technologies can offer us today, it is vital to find a place where all the gathered data will be kept.

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Analytics Vidhya

APRIL 11, 2022

Introduction Cloud computing is the name of the game in Web 2.0 With the shifting to online and virtual business models, cloud computing has helped enhance corporate workflow and reduce office infrastructure costs. and will continue to extend to Web 3.0.

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phData

FEBRUARY 21, 2025

The Cloud represents an iteration beyond the on-prem data warehouse, where computing resources are delivered over the Internet and are managed by a third-party provider. Examples include: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

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phData

MAY 25, 2023

One big issue that contributes to this resistance is that although Snowflake is a great cloud data warehousing platform, Microsoft has a data warehousing tool of its own called Synapse. In a perfect world, Microsoft would have clients push even more storage and compute to its Azure Synapse platform.

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phData

FEBRUARY 14, 2023

Fivetran works with all three Snowflake cloud providers. 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.

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Smart Data Collective

APRIL 24, 2023

Innovations in the early 20th century changed how data could be used. Google’s Hadoop allowed for unlimited data storage on inexpensive servers, which we now call the Cloud. Data brokers have over 3,000 profiles on each individual, including personal information like political preferences and hobbies.

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How to Learn Machine Learning

APRIL 26, 2025

Data Storage and Management Once data have been collected from the sources, they must be secured and made accessible. The responsibilities of this phase can be handled with traditional databases (MySQL, PostgreSQL), cloud storage (AWS S3, Google Cloud Storage), and big data frameworks (Hadoop, Apache Spark).

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phData

APRIL 29, 2024

Fivetran enables healthcare organizations to ingest data securely and effectively from a variety of sources into their target destinations, such as Snowflake or other cloud data platforms, for further analytics or curation for sharing data with external providers or customers.

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Pickl AI

OCTOBER 15, 2024

Talend Talend is a leading open-source ETL platform that offers comprehensive solutions for data integration, data quality , and cloud data management. It supports both batch and real-time data processing , making it highly versatile. It is well known for its data provenance and seamless data routing capabilities.

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phData

NOVEMBER 8, 2024

Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data. Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature.

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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. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.

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