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Diving Deep into OLAP: Unveiling the Power of Multidimensional Data Analysis

Pickl AI

Summary: Online Analytical Processing (OLAP) systems in Data Warehouse enable complex Data Analysis by organizing information into multidimensional structures. Key characteristics include fast query performance, interactive analysis, hierarchical data organization, and support for multiple users.

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

Data Science Dojo

Business Intelligence Analyst Business intelligence analysts are responsible for gathering and analyzing data to drive strategic decision-making. They require strong analytical skills, knowledge of data modeling, and expertise in business intelligence tools.

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How to Optimize Data Warehouse with STAR Schema?

Analytics Vidhya

Introduction The STAR schema is an efficient database design used in data warehousing and business intelligence. It organizes data into a central fact table linked to surrounding dimension tables. A major advantage of the STAR […] The post How to Optimize Data Warehouse with STAR Schema?

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Understanding SQL language: The backbone of relational databases

Dataconomy

The SQL language, or Structured Query Language, is essential for managing and manipulating relational databases. It has become indispensable for those working with data across various industries. Introduction to SQL language SQL language stands for Structured Query Language. Why learn SQL language?

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How Twilio generated SQL using Looker Modeling Language data with Amazon Bedrock

AWS Machine Learning Blog

Managing and retrieving the right information can be complex, especially for data analysts working with large data lakes and complex SQL queries. RAG optimizes language model outputs by extending the models’ capabilities to specific domains or an organization’s internal data for tailored responses.

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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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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

They have structured data such as sales transactions and revenue metrics stored in databases, alongside unstructured data such as customer reviews and marketing reports collected from various channels. Use Amazon Athena SQL queries to provide insights.

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