Remove Business Intelligence Remove Data Scientist Remove Data Silos
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Self-Service BI vs Traditional BI: What’s Next?

Alation

Business intelligence has a long history. Today, the term describes that same activity, but on a much larger scale, as organizations race to collect, analyze, and act on data first. With remote and hybrid work on the rise, the ability to locate and leverage data and expertise — wherever it resides — is more critical than ever.

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Exploring the fundamentals of online transaction processing databases

Dataconomy

Conversely, OLAP systems are optimized for conducting complex data analysis and are designed for use by data scientists, business analysts, and knowledge workers. OLAP systems support business intelligence, data mining, and other decision support applications.

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Connecting Amazon Redshift and RStudio on Amazon SageMaker

AWS Machine Learning Blog

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

AWS 140
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How to harness a new wave of data-driven decision-making

Tableau

They have access to trusted, live data sources and use data often as they experiment, test, innovate, and learn. Eliminate business and data silos to increase collaboration. Data in isolation isn’t useful. Here are some tips we have as you look ahead: . Finance: Finance moves fast.

Tableau 105
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How to harness a new wave of data-driven decision-making

Tableau

They have access to trusted, live data sources and use data often as they experiment, test, innovate, and learn. Eliminate business and data silos to increase collaboration. Data in isolation isn’t useful. Here are some tips we have as you look ahead: . Finance: Finance moves fast.

Tableau 98
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Why Move SAP ERP Data to Snowflake?

phData

Employing a modular structure, SAP ERP encompasses modules such as finance, human resources, supply chain , and more, facilitating real-time collaboration and data sharing across different departments through a centralized database. Example Solution Here is a high-level overview of how the solution works.

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Tackling AI’s data challenges with IBM databases on AWS

IBM Journey to AI blog

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

AWS 93