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5 Ways Data Modeling Is Critical to Data Governance

erwin

They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. Today’s data modeling is not your father’s data modeling software.

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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Ontotext

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

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Throwing Your Data Into the Ocean

Ontotext

According to this article , it costs $54,500 for every kilogram you want into space. It has been suggested that their Falcon 9 rocket has lowered the cost per kilo to $2,720. That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency.

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Data architecture strategy for data quality

IBM Big Data Hub

Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues. Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few.

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A hybrid approach in healthcare data warehousing with Amazon Redshift

AWS Big Data

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. They often negate many benefits of data vaults, and require more business logic, which can be avoided.

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How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. We also discuss the benefits Ruparupa gained after the implementation. Let’s look at each main component in more detail.

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AML: Past, Present and Future – Part III

Cloudera

It supports a variety of storage engines that can handle raw files, structured data (tables), and unstructured data. It also supports a number of frameworks that can process data in parallel, in batch or in streams, in a variety of languages. The foundation of this end-to-end AML solution is Cloudera Enterprise.