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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

To fill in the gaps in existing data, HR&A creates digital equity surveys to build a more complete picture before developing digital equity plans. 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.

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

The rise of SaaS business intelligence tools is answering that need, providing a dynamic vessel for presenting and interacting with essential insights in a way that is digestible and accessible. The future is bright for logistics companies that are willing to take advantage of big data.

Big Data 275
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Improve power utility operational efficiency using smart sensor data and Amazon QuickSight

AWS Big Data

In this series of posts, we walk you through how we use Amazon QuickSight , a serverless, fully managed, business intelligence (BI) service that enables data-driven decision making at scale. Solution overview The following highly simplified architectural diagram illustrates the smart sensor data collection and processing.

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Mastering Data Analysis Report and Dashboard

FineReport

As we explore examples of data analysis reports and interactive report data analysis dashboards, we embark on a journey to unravel the nuanced art of transforming raw data into meaningful narratives that empower decision-makers. User Analysis If we delve into the core of big data analysis, it lies in user analysis.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches.

Analytics 107
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Harnessing Streaming Data: Insights at the Speed of Life

Sisense

Every data professional knows that ensuring data quality is vital to producing usable query results. Streaming data can be extra challenging in this regard, as it tends to be “dirty,” with new fields that are added without warning and frequent mistakes in the data collection process.

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AI, the Power of Knowledge and the Future Ahead: An Interview with Head of Ontotext’s R&I Milena Yankova

Ontotext

Milena Yankova : The professions of the future are related to understanding and processing data, transforming it into information and extracting knowledge from it. Milena Yankova : If they decide to work in IT, I would advise them to better understand the value of the data that machines collect from their interactions with us.