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Enhancing Data Fabric with SQL Asset Type in IBM Knowledge Catalog

IBM Data Science in Practice

In this blog, we explore how the introduction of SQL Asset Type enhances the metadata enrichment process within the IBM Knowledge Catalog , enhancing data governance and consumption. Introducing SQL Asset Type A significant enhancement to the metadata enrichment process is the introduction of SQL Asset Type.

SQL 130
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Choosing the Right Programming Language for A Corporate Database

Smart Data Collective

Structured Query Language (SQL). When it comes to industry standards for creating corporate databases, SQL is one of the most popular programming languages utilized by organizations. SQL is a query language, which means it retrieves or changes information from a database through queries.

Database 112
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Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

Flipboard

For more information about using Athena to query an AWS Glue table, refer to Running SQL queries using Amazon Athena. For example, you can run the following SQL query: SELECT * FROM "c360_workshop_db"."source_auto_address" Under Data classification tools, choose Record Matching. This will open the ML transforms page.

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Upcoming Snowflake Features

phData

Below are several of the upcoming features announced during the Summit: Cortex Analyst : this upcoming feature, built with Meta’s Llama 3 and Mistral Large models, allows business users to chat with their data on Snowflake. Snowflake Copilot, soon-to-be GA, allows technical users to convert questions into SQL.

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How To Use Dynamic Data Masking for Virtual Columns in Snowflake External Tables

phData

However, the default non-virtual column VALUE will still show the unmasked or unobfuscated data to the end user, which is not the intended behavior. You can refer to Figure 3 to observe the outcome of the SELECT SQL statement on the customer external table. Review the list based on the classification and make adjustments as necessary.

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How to Migrate from dbt Core to dbt Cloud: phData’s Simplified Approach

phData

These projects should include all functional areas within the data platform including analytics engineering, machine learning , and data science. Data governance and data classification are potential reasons to separate projects in dbt Cloud.

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, data classification, organization and tagging.