Data Science 101

NOVEMBER 11, 2019

Welcome to the first beta edition of Cloud Data Science News. This will cover major announcements and news for doing data science in the cloud. 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.

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Cloud Data Data Science Azure Clustering 95

Data Science Blog

SEPTEMBER 19, 2023

By automating the provisioning and management of cloud resources through code, IaC brings a host of advantages to the development and maintenance of Data Warehouse Systems in the cloud. So why using IaC for Cloud Data Infrastructures? apply(([serverName, rgName, dbName]) => { return `Server=tcp:${serverName}.database.windows.net;initial

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Data Warehouse Azure SQL Database 259

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 Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Here they are in my order of importance (based upon my opinion).

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Data Science Azure SQL Machine Learning 106

Flipboard

AUGUST 17, 2023

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. It provides a single web-based visual interface where you can perform all ML development steps, including preparing data and building, training, and deploying models.

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ML ML AWS Data Warehouse 123

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. With a cloud deployment, enterprises can leverage a “pay as you go” model; reducing the burden of incurring capital costs. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models.

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Data Lakes Cloud Data AWS Tableau 52

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. 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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Data Modeling Data Models Business Intelligence Business Intelligence 245

Data Science Blog

MAY 15, 2023

Data Warehousing ist seit den 1980er Jahren die wichtigste Lösung für die Speicherung und Verarbeitung von Daten für Business Intelligence und Analysen. Mit der zunehmenden Datenmenge und -vielfalt wurde die Verwaltung von Data Warehouses jedoch immer schwieriger und teurer. So basieren z.

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Data Warehouse Data Lakes Azure AWS 147

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. SharePoint.

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Data Warehouse SQL Azure ETL 97

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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Data Science Machine Learning Machine Learning Data Visualization 150

IBM Journey to AI blog

MAY 9, 2023

“We recognize the importance of watsonx.data and the development of the open-source components that it’s built upon,” said Das Kamhout, VP and Senior Principal Engineer of the Cloud and Enterprise Solutions Group at Intel. The solution will also be available in AWS Marketplace.

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Data Warehouse AWS AI AI 92

AWS Machine Learning Blog

DECEMBER 1, 2023

This is where the AWS suite of low-code and no-code ML services becomes an essential tool. As a strategic systems integrator with deep ML experience, Deloitte utilizes the no-code and low-code ML tools from AWS to efficiently build and deploy ML models for Deloitte’s clients and for internal assets. On the Create menu, choose Document.

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Machine Learning Machine Learning Data Preparation ML 110

AWS Machine Learning Blog

NOVEMBER 27, 2023

Set up OAuth for Salesforce Data Cloud in SageMaker Canvas. Connect to Salesforce Data Cloud data using the built-in SageMaker Canvas Salesforce Data Cloud connector and import the dataset. Configure the following scopes on your connected app: Manage user data via APIs ( api ).

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ML ML AWS SQL 90

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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SQL Data Warehouse Azure Cloud Data 52

IBM Journey to AI blog

SEPTEMBER 11, 2023

Codd published his famous paper “ A Relational Model of Data for Large Shared Data Banks.” 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. Chamberlin and Raymond F.

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Database SQL Data Warehouse Machine Learning 101

AWS Machine Learning Blog

JULY 17, 2023

Amazon Redshift is a fully managed, fast, secure, and scalable cloud data warehouse. Organizations often want to use SageMaker Studio to get predictions from data stored in a data warehouse such as Amazon Redshift. All SageMaker Studio traffic is through the specified VPC and subnets. Select VPC Only , then choose Next.

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Clustering AWS ML ML 83

AWS Machine Learning Blog

AUGUST 4, 2023

The following steps give an overview of how to use the new capabilities launched in SageMaker for Salesforce to enable the overall integration: Set up the Amazon SageMaker Studio domain and OAuth between Salesforce and the AWS account s. The endpoint will be exposed to Salesforce Data Cloud as an API through API Gateway.

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ML ML AWS AI 94

IBM Journey to AI blog

MAY 15, 2024

As a result, users boost pipeline performance while ensuring data security and controls. Hybrid cloud data integration Traditional data integration solutions often face latency and scalability challenges when integrating data across hybrid cloud environments.

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Data Pipeline ETL SQL Database 85

Pickl AI

APRIL 9, 2025

Integration : Can it connect with existing systems like AWS, Azure, or Google Cloud? Integration capabilities are crucial for leveraging cloud services. It supports complex data transformations and offers advanced features like data quality management and metadata management.

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phData

SEPTEMBER 2, 2024

Matillion is a SaaS-based data integration platform that can be hosted in AWS, Azure, or GCP. It offers a cloud-agnostic data productivity hub called Matillion Data Productivity Cloud. This will ensure if anyone is rerunning the entire job after resolving the failure, data duplication won’t happen.

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ETL Data Warehouse SQL Database 52

Data Science Blog

SEPTEMBER 3, 2024

Celonis unterscheidet sich von den meisten anderen Tools noch dahingehend, dass es versucht, die ganze Kette des Process Minings in einer einzigen und ausschließlichen Cloud-Anwendung in einer Suite bereitzustellen. in Databricks oder den KI-Tools von Google, AWS und Mircosoft Azure (Azure Cognitive Services, Azure Machine Learning etc.).

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Data Science Power BI Azure Data Warehouse 130

IBM Journey to AI blog

JULY 17, 2023

.” Das Kamhout, VP and Senior Principal Engineer of the Cloud and Enterprise Solutions Group at Intel Watsonx.data supports our customers’ increasing needs around hybrid cloud deployments and is available on premises and across multiple cloud providers, including IBM Cloud and Amazon Web Services (AWS).

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AI AI Machine Learning Machine Learning 74

phData

FEBRUARY 14, 2023

Matillion Matillion is a complete ETL tool that integrates with an extensive list of pre-built data source connectors, loads data into cloud data environments such as Snowflake, and then performs transformations to make data consumable by analytics tools such as Tableau and PowerBI.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

phData

MAY 31, 2023

The Snowflake Data Cloud is a powerful and industry-leading cloud data platform. The SQL editor is quite helpful as it allows you to customize your query as needed. When using the Input Data tool, it is crucial to leverage the Pre SQL and Post SQL statements to define the context for the query you want to run.

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SQL Database Cloud Data Data Governance 52

phData

JUNE 14, 2023

Each migration SQL script is assigned a unique sequence number to facilitate the correct order of application. Step-B The objective of this step is to copy the inventory data file from the AWS S3 location to the staging inventory table using the Snowflake pipe object.

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Data Pipeline Database SQL Data Engineering 52

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 Lakes Data Warehouse Database Azure 52

IBM Journey to AI blog

JULY 11, 2023

Cloud object storage support The next generation of Db2 Warehouse introduces support for cloud object storage as a new storage medium within its storage hierarchy. Additionally, moving the cloud storage from block to object storage results in a 34x reduction in cloud storage costs. Try Db2 Warehouse for free today 1.

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Data Warehouse Database Cloud Data Big Data 60

phData

AUGUST 9, 2023

Open source big data tools like Hadoop were experimented with – these could land data into a repository first before transformation. Thus, the early data lakes began following more of the EL-style flow. But then, in the 2010s, cloud data warehouses, particularly ones like Snowflake , came along and really changed the game.

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ETL Data Warehouse Cloud Data Big Data 52

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. The June 2021 release of Power BI Desktop introduced Custom SQL queries to Snowflake in DirectQuery mode.

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Power BI Analytics Analytics Azure 84

Alation

JULY 18, 2022

And the highlight, for us data intelligence folks, was the Databricks’ announcement that Unity Catalog , its unified governance solution for all data assets on its Lakehouse platform, will soon be available on AWS and Azure in the upcoming weeks. A simple model to control access to data via a UI or SQL.

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AI AI Data Lakes Azure 52

phData

DECEMBER 4, 2023

However, if there’s one thing we’ve learned from years of successful cloud data implementations here at phData, it’s the importance of: Defining and implementing processes Building automation, and Performing configuration …even before you create the first user account. And once again, for loading data, do not use SQL Inserts.

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Clustering Database SQL Data Pipeline 98

Women in Big Data

DECEMBER 9, 2024

Lookers strength lies in its ability to connect to a wide variety of data sources. Examples include SQl, DWH, and Cloud based systems (Google Bigquery). With Looker, you can share dashboards and visualizations seamlessly across teams, providing stakeholders with access to real-time data.

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Big Data Big Data Power BI Tableau 52

phData

JUNE 3, 2024

Snowflake AI Data Cloud has become a premier cloud data warehousing solution. Maybe you’re just getting started looking into a cloud solution for your organization, or maybe you’ve already got Snowflake and are wondering what features you’re missing out on. Snowflake has you covered with Cortex.

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Machine Learning Machine Learning Database Cloud Data 52

phData

JULY 19, 2023

Use Cases of Successful Application of Fivetran Case Study 1 Automating Reporting and Cloud Transition: PhData Empowers Regional Bank with Snowflake Data Cloud PhData assisted a regional bank in automating manual reporting processes and transitioning to a cloud data system. Services (AWS) compliance programs.

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Data Warehouse Database Data Pipeline Cloud Data 52

phData

JULY 19, 2023

Use Cases of Successful Application of Fivetran Case Study 1 Automating Reporting and Cloud Transition: PhData Empowers Regional Bank with Snowflake Data Cloud PhData assisted a regional bank in automating manual reporting processes and transitioning to a cloud data system. Services (AWS) compliance programs.

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Data Warehouse Database Data Pipeline Cloud Data 52

phData

AUGUST 6, 2024

Organizations must ensure their data pipelines are well designed and implemented to achieve this, especially as their engagement with cloud data platforms such as the Snowflake Data Cloud grows. For customers in Snowflake, Snowpark is a powerful tool for building these effective and scalable data pipelines.

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Data Pipeline Python Data Engineering Data Engineering 52

phData

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

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Data Warehouse Analytics Analytics Cloud Data 52

Alation

FEBRUARY 8, 2022

Examples include public cloud vendors like AWS, Azure, and GCP. Plane 2: Data Product Developer Experience Plane. This plane uses “ declarative interfaces to manage the lifecycle of a data product ” to help developers, for example, build, deploy, and monitor data products.

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