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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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The Best Data Management Tools For Small Businesses

Smart Data Collective

As the world is gradually becoming more dependent on data, the services, tools and infrastructure are all the more important for businesses in every sector. Data management has become a fundamental business concern, and especially for businesses that are going through a digital transformation. What is data management?

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. It can be used with both on-premise and multi-cloud environments.

Risk 71
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How HR&A uses Amazon Redshift spatial analytics on Amazon Redshift Serverless to measure digital equity in states across the US

AWS Big Data

HR&A has used Amazon Redshift Serverless and CARTO to process survey findings more efficiently and create custom interactive dashboards to facilitate understanding of the results. The following are sample screenshots of the dashboards that show survey responses by zip code.

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Simplify Metrics on Apache Druid With Rill Data and Cloudera

Cloudera

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Data is made queryable in real time.

Metrics 90
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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. dbt emerged as the perfect choice for this transformation within their existing AWS environment.

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Accelerate analytics on Amazon OpenSearch Service with AWS Glue through its native connector

AWS Big Data

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. Solution overview The new native OpenSearch Service connector is a powerful tool that can help organizations unlock the full potential of their data.