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Sisu Data is an analytics platform for structureddata that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions.
Sisu Data is an analytics platform for structureddata that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions.
This is where LLMs can extend the systems capabilities by converting raw data into actionable insights on a zero-shot basis , without the need for specialized machine learning models, namely: Automatic reporting: LLMs can analyze time series data and generate detailed reports in natural language.
It is possible to structuredata across a broad range of spreadsheets, but the final result can be more confusing than productive. By using an online dashboard , you will be able to gain access to dynamic metrics and data in a way that’s digestible, actionable, and accurate.
Whether you need to drill down for a granular view of a particular data set or create a high-level summary to describe a particular system and the data it relies on, end-to-end data lineage must be documented and tracked, with an emphasis on the dynamics of data processing and movement as opposed to datastructures.
Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. Benchmarking is more accurate.
With its integrated search feature, Octopai’s visual metadata tools can find all the information within a given context, such as terminology, definitions, technical metadata, keyperformanceindicators, and process areas. . Data lineage is incomplete without the business layer provided by an Automated Business Glossary.
To address the issue of data quality, Amazon DataZone now integrates directly with AWS Glue Data Quality, allowing you to visualize data quality scores for AWS Glue Data Catalog assets directly within the Amazon DataZone web portal. Amazon DataZone natively supports data sharing for Amazon Redshift data assets.
You can use simple SQL to analyze structured and semi-structureddata across data warehouses, data marts, operational databases, and data lakes to deliver the best price performance at any scale. Data in Amazon S3 can be easily queried in place using SQL with Amazon Redshift Spectrum.
Feedback analytics and fine-tuning It’s important for data operation managers and AI/ML developers to get insight about the performance of the generative AI application and the FMs in use. OpenSearch Service offers visualization capabilities powered by OpenSearch Dashboards and Kibana (1.5 versions).
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