Pickl AI

NOVEMBER 4, 2024

Key Takeaways Data Engineering is vital for transforming raw data into actionable insights. Key components include data modelling, warehousing, pipelines, and integration. Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

phData

APRIL 29, 2024

Understanding Fivetran Fivetran is a popular Software-as-a-Service platform that enables users to automate the movement of data and ETL processes across diverse sources to a target destination. Our team frequently configures Fivetran connectors to cloud object storage platforms such as Amazon S3, Azure Blob Storage, and Google Cloud Storage.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

ODSC - Open Data Science

JUNE 12, 2023

From a data governance perspective, this is a massive risk to organizations by exposing them to the whole laundry of privacy and security breaches. With the Power BI Datamarts technology, Microsoft provides a governed self-service datamart capability in the Power BI Service.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

Data Governance 59

Data Governance ML ML Cloud Data 59

ODSC - Open Data Science

JANUARY 18, 2024

So as you take inventory of your existing skill set, you’ll want to start to identify the areas where you need to focus on to become a data engineer. These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. Learn more about the cloud.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

The MLOps Blog

JUNE 27, 2023

Microsoft Azure ML Platform The Azure Machine Learning platform provides a collaborative workspace that supports various programming languages and frameworks. LakeFS LakeFS is an open-source platform that provides data lake versioning and management capabilities.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

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

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. Data Security and Governance Maintaining data security is crucial for any company.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 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

Alation

AUGUST 2, 2022

Customer centricity requires modernized data and IT infrastructures. Too often, companies manage data in spreadsheets or individual databases. This means that you’re likely missing valuable insights that could be gleaned from data lakes and data analytics.

Data Silos 52

Data Silos Data Lakes Data Analyst Data Scientist 52

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Data Science Blog

JULY 20, 2024

Vielfältige Unterstützung: Kompatibel mit verschiedenen Datenbankmanagementsystemen wie MS SQL Server und Azure Synapse Analytics. Data Lakes: Unterstützt MS Azure Blob Storage. Pipelines/ETL : Unterstützt Technologien wie SQL Server Integration Services und Azure Data Factory.

Azure 130

Azure SQL Power BI Data Lakes 130

phData

SEPTEMBER 27, 2024

Both persistent staging and data lakes involve storing large amounts of raw data. But persistent staging is typically more structured and integrated into your overall customer data pipeline. Building a composable CDP requires some serious data engineering chops. Looking for purchase data? New user sign-up?

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52