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Business Intelligence for Fairs, Congresses and Exhibitions

Smart Data Collective

While different companies, regardless of their size, have different operational processes, they share a common need for actionable insight to drive success in their business. Advancement in big data technology has made the world of business even more competitive. This eliminates guesswork when coming up with business strategies.

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Navigate your way to success – Top 10 data science careers to pursue in 2023

Data Science Dojo

Top 10 Professions in Data Science: Below, we provide a list of the top data science careers along with their corresponding salary ranges: 1. Data Scientist Data scientists are responsible for designing and implementing data models, analyzing and interpreting data, and communicating insights to stakeholders.

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Object-centric Process Mining on Data Mesh Architectures

Data Science Blog

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg.

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Dimensional Data Modeling in the Modern Era: A Timeless Blueprint for Data Architecture

ODSC - Open Data Science

In a world of ever-evolving data tools and technologies, some approaches stand the test of time. Thats the case Dustin DorseyPrincipal Data Architect at Onyx makes for dimensional data modeling , a practice born in the 1990s that continues to provide clarity, performance, and scalability in modern data architecture.

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A Comprehensive Guide to Business Intelligence Analysts

Pickl AI

Summary: Business Intelligence Analysts transform raw data into actionable insights. They use tools and techniques to analyse data, create reports, and support strategic decisions. Key skills include SQL, data visualization, and business acumen. Introduction We are living in an era defined by data.

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Natural Language Query (NLQ)

Dataconomy

This capability, rooted in the sophisticated world of Natural Language Processing (NLP), removes the barriers that often complicate data retrieval and analysis, making insights accessible to everyone, regardless of their technical expertise. What is Natural Language Query (NLQ)?

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Essential data engineering tools for 2023: Empowering for management and analysis

Data Science Dojo

It allows data engineers to build, test, and maintain data pipelines in a version-controlled manner. dbt focuses on transforming raw data into analytics-ready tables using SQL-based transformations. Looker: Looker is a business intelligence and data visualization platform.