Dataconomy

SEPTEMBER 4, 2023

Diagnostic analytics: Diagnostic analytics goes a step further by analyzing historical data to determine why certain events occurred. By understanding the “why” behind past events, organizations can make informed decisions to prevent or replicate them. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

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.

Data Warehouse 98

Data Warehouse Azure SQL ETL 98

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.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

phData

APRIL 29, 2024

Recognizing these specific needs, Fivetran has developed a range of connectors, including dedicated applications, databases, files, and events, which can accommodate the diverse formats used by healthcare systems. Addressing these needs may pose challenges that lead to the implementation of custom solutions rather than a uniform approach.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

IBM Journey to AI blog

MARCH 20, 2024

What is a public cloud? A public cloud is a type of cloud computing in which a third-party service provider (e.g., Amazon Web Services (AWS), Google Cloud Platform, IBM Cloud or Microsoft Azure) makes computing resources (e.g., Most often, only the most relevant data is processed at the edge.

Cloud Computing 112

Cloud Computing Internet of Things Big Data Big Data 112

phData

FEBRUARY 14, 2023

What Are the Best Third-Party Data Ingestion Tools for Snowflake? Fivetran Fivetran is a tool dedicated to replicating applications, databases, events, and files into a high-performance data warehouse, such as Snowflake. Fivetran works with all three Snowflake cloud providers.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

phData

JUNE 11, 2025

Depending on the requirement, it is important to choose between transient and permanent tables, as well as data recovery needs and downtime considerations. Implement scripts or workflows to automatically tag new resources based on predefined criteria or events, reducing manual effort and ensuring timely and accurate cost attribution.

Clustering 59

Clustering SQL Database Data Lakes 59

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. Db2 Warehouse SaaS, on the other hand, is a fully managed elastic cloud data warehouse with our columnar technology. Many consider a NoSQL database essential for high data ingestion rates.

Database 101

Database SQL Data Warehouse Machine Learning 101

ODSC - Open Data Science

FEBRUARY 6, 2024

Google BigQuery When it comes to cloud data warehouses, Snowflake, Amazon Redshift, and Google BigQuery are often at the forefront of discussions. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences. Interested in attending an ODSC event?

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

NOVEMBER 2, 2023

Google has specifically designed TPUs for neural network processing , which is one example of how these organizations had to get creative when melding AI with the cloud. Companies running enormous data centers like Microsoft, Google, and Amazon are kickstarting their AI-powered cloud platforms, like Azure.

Cloud Computing 52

Cloud Computing Data Science AI AI 52

Pickl AI

JANUARY 31, 2025

Resource Pooling: Cloud providers serve multiple customers from the same physical resources through a multi-tenant model. Workload Resilience: Cloud providers often deploy redundant resources to ensure that workloads remain operational even in the event of a failure. Examples include AWS Lambda and Azure Functions.

Cloud Computing 52

Cloud Computing Azure Artificial Intelligence Artificial Intelligence 52

IBM Journey to AI blog

AUGUST 3, 2023

Enforce security policies in near real-time that protect data across the enterprise—for all data access, change control and user activities. Guardium supports deployment on several cloud platforms, including Amazon AWS, Google, IBM Cloud, Microsoft Azure and Oracle OCI.

Azure 71

Azure Database Analytics Analytics 71

Mlearning.ai

FEBRUARY 16, 2023

The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data. The solution was built on top of Amazon Web Services and is now available on Google Cloud and Microsoft Azure. Therefore, the tool is referred to as cloud-agnostic. What does Snowflake do?

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 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

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

Mlearning.ai

JANUARY 26, 2023

EO data is not yet a commodity and neither is environmental information, which has led to a fragmented data space defined by a seemingly endless production of new tools and services that can’t interoperate and aren’t accessible by people outside of the deep tech community ( read more ). A summary of this discussion is provided below.

AWS 98

AWS Database Data Science Clean Data 98

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.

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

ODSC - Open Data Science

JULY 20, 2023

Depending on the size and complexity of the data and the company’s budget, there are several alternatives to a data center that can be considered. Cloud Services: A company with limited data resources may find that cloud services are a cost-effective solution.

AI 52

AI AI Cloud Computing Data Scientist 52

Data Science Blog

SEPTEMBER 3, 2024

Dabei darf gerne in Erinnerung gerufen werden, dass Process Mining im Kern eine Graphenanalyse ist, die ein Event Log in Graphen umwandelt, Aktivitäten (Events) stellen dabei die Knoten und die Prozesszeiten die Kanten dar, zumindest ist das grundsätzlich so. Es handelt sich dabei also um eine Analysemethodik und nicht um ein Tool.

Data Science 130

Data Science Power BI Azure Data Warehouse 130

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. If not, it will retry after a certain duration (E.g., 30 minutes).

Python 52

Python ETL AWS Database 52

phData

SEPTEMBER 27, 2024

Methods that allow our customer data models to be as dynamic and flexible as the customers they represent. In this guide, we will explore concepts like transitional modeling for customer profiles, the power of event logs for customer behavior, persistent staging for raw customer data, real-time customer data capture, and much more.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52