DagsHub

DECEMBER 11, 2023

LakeFS Most big data storage solutions such as Azure, Google cloud storage, and Amazon S3 have good performance, cost-effective, and have good connectivity with other tooling. However, these tools have functional gaps for more advanced data workflows. This can also make the learning process challenging.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Database 98

Data Science Dojo

SEPTEMBER 10, 2024

Additionally, Azure Machine Learning enables the operationalization and management of large language models, providing a robust platform for developing and deploying AI solutions. It also excels at creating concise, relevant, and customizable summaries of text and documents.

Machine Learning 369

Machine Learning Machine Learning Natural Language Processing ML 369

Pickl AI

FEBRUARY 23, 2025

Look for features such as scalability (the ability to handle growing datasets), performance (speed of processing), ease of use (user-friendly interfaces), integration capabilities (compatibility with existing systems), security measures (data protection features), and pricing models (licensing costs).

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52

The MLOps Blog

JUNE 27, 2023

User support arrangements Consider the availability and quality of support from the provider or vendor, including documentation, tutorials, forums, customer service, etc. Microsoft Azure ML Platform The Azure Machine Learning platform provides a collaborative workspace that supports various programming languages and frameworks.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Pickl AI

DECEMBER 2, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

DagsHub

OCTOBER 23, 2024

To combine the collected data, you can integrate different data producers into a data lake as a repository. A central repository for unstructured data is beneficial for tasks like analytics and data virtualization. Data Cleaning The next step is to clean the data after ingesting it into the data lake.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Pickl AI

APRIL 21, 2025

Semi-Structured Data: Data that has some organizational properties but doesn’t fit a rigid database structure (like emails, XML files, or JSON data used by websites). Unstructured Data: Data with no predefined format (like text documents, social media posts, images, audio files, videos).

Big Data 52

Big Data Big Data Data Science Machine Learning 52

phData

APRIL 29, 2024

Oracle – The Oracle connector, a database-type connector, enables real-time data transfer of large volumes of data from on-premises or cloud sources to the destination of choice, such as a cloud data lake or data warehouse. and delivers them to analytics platforms downstream.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

phData

FEBRUARY 14, 2023

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. Data Collector can use Snowflake’s native Snowpipe in its pipelines.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

DagsHub

NOVEMBER 11, 2024

So, we must understand the different unstructured data types and effectively process them to uncover hidden patterns. Textual Data Textual data is one of the most common forms of unstructured data and can be in the format of documents, social media posts, emails, web pages, customer reviews, or conversation logs.

AI 52

AI AI Data Lakes Database 52

ODSC - Open Data Science

OCTOBER 3, 2024

AI and Data: Enhancing Development with GitHub Copilot How can GitHub Copilot be used in environments like Visual Studio Code, JetBrains IDEs, or Azure Data Studio to significantly reduce coding time? When your data consists of various patient chart document types (e.g.

Data Science 40

Data Science Data Lakes Data Scientist AI 40

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. Assign appropriate roles and privileges to users based on their responsibilities and requirements, ensuring secure and streamlined budget management processes.

Clustering 59

Clustering SQL Database Data Lakes 59

phData

JULY 10, 2023

It can be used to store data outside the database while retaining the ability to query its data. These files need to be in one of the Snowflake-supported cloud systems: Amazon S3, Google Cloud Storage, or Microsoft Azure Blob storage. What are Directory Tables in Snowflake?

Data Lakes 40

Data Lakes Azure Database AWS 40

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

Pickl AI

APRIL 9, 2025

This includes operations like data validation, data cleansing, data aggregation, and data normalization. The goal is to ensure that the data is consistent and ready for analysis. Loading : Storing the transformed data in a target system like a data warehouse, data lake, or even a database.

ETL 52

ETL Data Warehouse AWS Business Intelligence 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. Record-keeping in a data catalog is key.

Data Governance 59

Data Governance ML ML Cloud Data 59

phData

DECEMBER 4, 2023

The software you might use OAuth with includes: Tableau Power BI Sigma Computing If so, you will need an OAuth provider like Okta, Microsoft Azure AD, Ping Identity PingFederate, or a Custom OAuth 2.0 For greater detail, see the Snowflake documentation. authorization server.

Clustering 98

Clustering Database SQL Data Pipeline 98

The MLOps Blog

OCTOBER 20, 2023

References : Links to internal or external documentation with background information or specific information used within the analysis presented in the notebook. Data to explore: Outline the tables or datasets you’re exploring/analyzing and reference their sources or link their data catalog entries. documentation.

SQL 52

SQL Database Data Scientist Python 52

phData

SEPTEMBER 28, 2023

Attach a Common Data Model Folder (preview) When you create a Dataflow from a CDM folder, you can establish a connection to a table authored in the Common Data Model (CDM) format by another application. This path is essential for accessing and manipulating the CDM data within your Dataflow.

Power BI 78

Power BI Data Preparation Machine Learning Machine Learning 78

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

The MLOps Blog

MARCH 21, 2023

Solution Data lakes and warehouses are the two key components of any data pipeline. The data lake is a platform where any kind or amount of data can be stored, processed, and analyzed. Data engineers are mostly in charge of it. Data Lake Vs. Feature Store.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69