Dataconomy

SEPTEMBER 4, 2023

Downtime, like the AWS outage in 2017 that affected several high-profile websites, can disrupt business operations. 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.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Alation

MARCH 1, 2022

Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed). Time is money,” said Leonard Kwok, Senior Data Analyst, ARC. And connectivity is the crux of a powerful data catalog.

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

phData

NOVEMBER 12, 2024

Snowflake is one of the most powerful cloud-based data warehouses on the market, offering a scalable solution built for analytics. However, when storing sensitive data in Snowflake, it’s crucial to implement every security measure possible to protect it from unauthorized access and potential breaches.

Azure 52

Azure Data Warehouse AWS Data Analyst 52

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Data Modeling: Entity-Relationship (ER) diagrams, data normalization, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Also Read: Top 10 Data Science tools for 2024. What is ETL?

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Alation

MAY 24, 2022

By augmenting rich human data curation in Alation with purpose-built data quality from partners, customers will have a complete view into the trustworthiness of data. It is advantageous to data consumers, such as data analysts and data scientists , to connect data quality context into their workflow in Alation.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. SageMaker Unified Studio provides a unified experience for using data, analytics, and AI capabilities. The table metadata is managed by Data Catalog.

SQL 136

SQL Data Analyst Data Warehouse AWS 136

phData

JUNE 3, 2024

Taking it one step further, if you don’t want your data traversing the public internet, you can implement one of the private connections available from the cloud provider your Snowflake account is created on, i.e., Azure Private Link, AWS Privatelink, or Google Cloud Service Private Connect. Snowflake has you covered with Cortex.

Machine Learning 52

Machine Learning Machine Learning Database Cloud Data 52

Pickl AI

DECEMBER 10, 2024

It ensures that businesses can process large volumes of data quickly, efficiently, and reliably. Whether managing transactional systems or handling massive data warehouses , Exadata guarantees seamless operations and top-tier reliability. Core Features Exadata delivers standout features tailored to enhance database performance.

Database 52

Database Analytics Analytics Business Intelligence 52

Flipboard

DECEMBER 4, 2024

Currently, organizations often create custom solutions to connect these systems, but they want a more unified approach that them to choose the best tools while providing a streamlined experience for their data teams. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

Data Lakes 134

Data Lakes Data Warehouse AWS Database 134