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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. What is the difference between business analytics and business intelligence?

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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. Now’s the time to strike.

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

AWS Big Data

For files with known structures, a Redshift stored procedure is used, which takes the file location and table name as parameters and runs a COPY command to load the raw data into corresponding Redshift tables. Finally, the dashboard’s user-friendly interface made survey data more accessible to a wider range of stakeholders.

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8 data strategy mistakes to avoid

CIO Business Intelligence

“Establishing data governance rules helps organizations comply with these regulations, reducing the risk of legal and financial penalties. Clear governance rules can also help ensure data quality by defining standards for data collection, storage, and formatting, which can improve the accuracy and reliability of your analysis.”

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The Modern Data Stack Explained: What The Future Holds

Alation

A typical modern data stack consists of the following: A data warehouse. Extract, load, Transform (ELT) tools. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. How Did the Modern Data Stack Get Started? How Can I Build a Modern Data Stack?

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How to Include BI in Your 2020 Budget

Sisense

Yet with this surge in data, many organizations are either not able to draw insights from their data, or are not able to do so quickly enough. It is estimated that of all data collected, less than 1% is actually analyzed and used. Your data is a gold mine and you’re barely scratching the surface of its value!