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Sky’s the Limit: Learn how JetBlue uses Monte Carlo and Snowflake to build trust in data and improve model accuracy

KDnuggets

Join JetBlue on 12/8 10AM PT to learn how their data engineering team achieves end-to-end coverage in their Snowflake data warehouse with the power of Monte Carlo and data observability.

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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

Scalable data pipelines: Seasoned data teams are facing increasing pressure to respond to a growing number of data requests from downstream consumers, which is compounded by the drive for users to have higher data literacy and skills shortage of experienced data engineers.

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Alation 2022.2: Open Data Quality Initiative and Enhanced Data Governance

Alation

This has created many different data quality tools and offerings in the market today and we’re thrilled to see the innovation. People will need high-quality data to trust information and make decisions. For example, a data steward can filter all data by ‘“endorsed data’” in a Snowflake data warehouse, tagged with ‘bank account’.

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Top ETL Tools: Unveiling the Best Solutions for Data Integration

Pickl AI

Also Read: Top 10 Data Science tools for 2024. It is a process for moving and managing data from various sources to a central data warehouse. This process ensures that data is accurate, consistent, and usable for analysis and reporting. This process helps organisations manage large volumes of data efficiently.

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Maximize the Power of dbt and Snowflake to Achieve Efficient and Scalable Data Vault Solutions

phData

The implementation of a data vault architecture requires the integration of multiple technologies to effectively support the design principles and meet the organization’s requirements. Data Acquisition: Extracting data from source systems and making it accessible. as well as calculating business keys.

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Five benefits of a data catalog

IBM Journey to AI blog

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

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Data Quality Framework: What It Is, Components, and Implementation

DagsHub

Datafold is a tool focused on data observability and quality. It is particularly popular among data engineers as it integrates well with modern data pipelines (e.g., Source: [link] Monte Carlo is a code-free data observability platform that focuses on data reliability across data pipelines.