Data Science Dojo

SEPTEMBER 11, 2024

With this full-fledged solution, you don’t have to spend all your time and effort combining different services or duplicating data. OneLake, being built on Azure Data Lake Storage (ADLS), supports various data formats, including Delta, Parquet, CSV, and JSON.

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phData

FEBRUARY 21, 2025

In this post, we will be particularly interested in the impact that cloud computing left on the modern data warehouse. We will explore the different options for data warehousing and how you can leverage this information to make the right decisions for your organization. Understanding the Basics What is a Data Warehouse?

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Data Warehouse Cloud Data ETL Cloud Computing 52

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

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Data Science Blog

SEPTEMBER 3, 2024

auf den Analyse-Ressourcen der Microsoft Azure Cloud oder in auf der databricks-Plattform. Alternativ zu Databricks können auch andere Data Warehouse Datenbankplattformen zur Anwendung kommen, beispielsweise auch snowflake mit dbt. Umgesetzt werden diese Anwendungsfälle bisher vor allem auf dritten Plattformen, wie z.

Data Science 130

Data Science Power BI Azure Data Warehouse 130

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. Data transformation.

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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. FAQs What is a Data Lakehouse?

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Data Lakes Data Warehouse Database Azure 52

Dataconomy

SEPTEMBER 4, 2023

Data integration: Integrate data from various sources into a centralized cloud data warehouse or data lake. Ensure that data is clean, consistent, and up-to-date. Use ETL (Extract, Transform, Load) processes or data integration tools to streamline data ingestion.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

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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Power BI Analytics Analytics Azure 84

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.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

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Data Warehouse Azure AWS Database 59

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. Below is a sample scenario for 3 business units within an organization for the data mart layer of the data warehouse.

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Mlearning.ai

FEBRUARY 16, 2023

The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency.

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Data Warehouse Business Intelligence Business Intelligence Database 52

IBM Journey to AI blog

SEPTEMBER 11, 2023

Db2 can run on Red Hat OpenShift and Kubernetes environments, ROSA & EKS on AWS, and ARO & AKS on Azure deployments. Customers can also choose to run IBM Db2 database and IBM Db2 Warehouse as a fully managed service. Db2 stands ready to embrace new challenges and opportunities within AI in the hybrid cloud data ecosystem.

Database 101

Database SQL Data Warehouse Machine Learning 101

Analytics Vidhya

OCTOBER 25, 2023

Introduction Struggling with expanding a business database due to storage, management, and data accessibility issues? To steer growth, employ effective data management strategies and tools. This article explores data management’s key tool features and lists the top tools for 2023.

Database 220

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Pickl AI

OCTOBER 15, 2024

ETL (Extract, Transform, Load) is a core process in data integration that involves extracting data from various sources, transforming it into a usable format, and loading it into a target system, such as a data warehouse. It supports both batch and real-time data processing , making it highly versatile.

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phData

NOVEMBER 28, 2023

Matillion is also built for scalability and future data demands, with support for cloud data platforms such as Snowflake Data Cloud , Databricks, Amazon Redshift, Microsoft Azure Synapse, and Google BigQuery, making it future-ready, everyone-ready, and AI-ready. Or would you even go to that directly?

Data Warehouse 52

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ODSC - Open Data Science

FEBRUARY 6, 2024

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

The MLOps Blog

MAY 17, 2023

Focus Area ETL helps to transform the raw data into a structured format that can be easily available for data scientists to create models and interpret for any data-driven decision. A data pipeline is created with the focus of transferring data from a variety of sources into a data warehouse.

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phData

MAY 4, 2023

To date, the company’s data warehousing solutions are largely built from the same template used in 1979. In short, they are still the model of multiple processors and massive disk storage with data warehouse software on the top layer managing it all. Oh, and let’s not forget those cost savings too!

SQL 52

SQL Data Warehouse Azure Big Data 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.

Machine Learning 52

Machine Learning Machine Learning Database Cloud Data 52

Alation

APRIL 14, 2022

This two-part series will explore how data discovery, fragmented data governance , ongoing data drift, and the need for ML explainability can all be overcome with a data catalog for accurate data and metadata record keeping. The Cloud Data Migration Challenge. Data pipeline orchestration.

Data Governance 59

Data Governance ML ML Cloud Data 59

phData

MAY 11, 2023

Snowflake has so many features that make it the leader in the Cloud Data Warehouse market. Cloning in Snowflake simply means that the data in the clone is not a copy of the original data but simply points back to the original data. Two of these tools are Terraform and phData’s own Provision tool.

Database 52

Database SQL DataOps Data Warehouse 52

phData

JANUARY 19, 2024

Matillion is also built for scalability and future data demands, with support for cloud data platforms such as Snowflake Data Cloud , Databricks, Amazon Redshift, Microsoft Azure Synapse, and Google BigQuery, making it future-ready, everyone-ready, and AI-ready. Additional setup is typically optional.

Data Pipeline 52

Data Pipeline Data Warehouse ETL Azure 52

phData

SEPTEMBER 20, 2023

A data mesh is a conceptual architectural approach for managing data in large organizations. Traditional data management approaches often involve centralizing data in a data warehouse or data lake, leading to challenges like data silos, data ownership issues, and data access and processing bottlenecks.

Data Silos 52

Data Silos Database Data Quality Data Engineer 52

ODSC - Open Data Science

JULY 11, 2023

Co-location data centers: These are data centers that are owned and operated by third-party providers and are used to house the IT equipment of multiple organizations. Edge data centers: These are data centers that are located closer to the edge of the network, where data is generated and consumed, rather than in central locations.

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Alation

FEBRUARY 8, 2022

The three technology planes of a self-service data mesh are: Plane 1: Data Infrastructure Plane. Examples include public cloud vendors like AWS, Azure, and GCP. Plane 2: Data Product Developer Experience Plane. While some may call it a data marketplace, others see the data catalog as the mesh supervision plane.

Data Governance 52

Data Governance Data Engineer Data Engineering Data Engineering 52

phData

SEPTEMBER 27, 2024

Here’s how a composable CDP might incorporate the modeling approaches we’ve discussed: Data Storage and Processing : This is your foundation. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery. Here’s where it gets really interesting.

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52

phData

OCTOBER 28, 2024

Understanding Matillion and Snowflake, the Python Component, and Why it is Used Matillion is a SaaS-based data integration platform that can be hosted in AWS, Azure, or GCP and supports multiple cloud data warehouses.

Python 52

Python ETL AWS Database 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

Women in Big Data

DECEMBER 9, 2024

Microsoft Power BI – Power BI is a comprehensive suite of tools which allows you to visualize data and create interactive reports and dashboards. Tableau – Tableau is celebrated for its advanced data visualization and interactive dashboard features. You can also share insights across organizations.

Big Data 52

Big Data Big Data Power BI Tableau 52

IBM Journey to AI blog

AUGUST 3, 2023

IBM Security® Guardium® Data Protection empowers security teams to safeguard sensitive data through discovery and classification, data activity monitoring, vulnerability assessments and advanced threat detection.

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Azure Database Analytics Analytics 71