Data Modeling, Data Warehouse and Power BI

CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog

MAY 20, 2024

It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models. It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL.

Data Pipeline

Data Pipeline Data Warehouse Azure Data Lakes

Data Modeling Fundamentals in Power BI

phData

JUNE 13, 2023

When thinking about Power BI , the platform’s visuals and report side immediately come to mind. While the front-end report visuals are important and the most visible to end users, a lot goes on behind the scenes that contribute heavily to the end product, including data modeling. What is Data Modeling?

Power BI

Power BI Data Models Data Modeling Data Warehouse

How to Optimize Power BI and Snowflake for Advanced Analytics

phData

MAY 25, 2023

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Table of Contents Why Discuss Snowflake & Power BI?

Power BI

Power BI Analytics Analytics Azure

Introduction to Power BI Datamarts

ODSC - Open Data Science

JUNE 12, 2023

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. Before we look into the Power BI Datamarts, let us take a step back and understand the meaning of a Datamart. in an enterprise data warehouse. What is a Datamart?

Power BI

Power BI Data Warehouse ETL Data Preparation

Data science vs data analytics: Unpacking the differences

IBM Journey to AI blog

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. js and Tableau Data science, data analytics and IBM Practicing data science isn’t without its challenges. Watsonx comprises of three powerful components: the watsonx.ai

Data Science

Data Science Analytics Analytics Data Scientist

What Are Business Intelligence Tools

Pickl AI

JANUARY 15, 2025

ETL (Extract, Transform, Load) Tools ETL tools are crucial for data integration processes. They extract data from various sources, transform it into a suitable format, and load it into a target database or data warehouse for analysis.

Business Intelligence

Business Intelligence Business Intelligence Power BI Data Visualization

Understanding Business Intelligence Architecture: Key Components

Pickl AI

JANUARY 28, 2025

This involves several key processes: Extract, Transform, Load (ETL): The ETL process extracts data from different sources, transforms it into a suitable format by cleaning and enriching it, and then loads it into a data warehouse or data lake. Data Lakes: These store raw, unprocessed data in its original format.

Business Intelligence

Business Intelligence Business Intelligence ETL Data Lakes

Who is a BI Developer: Role, Responsibilities & Skills

Pickl AI

JULY 3, 2023

It is the process of converting raw data into relevant and practical knowledge to help evaluate the performance of businesses, discover trends, and make well-informed choices. Data gathering, data integration, data modelling, analysis of information, and data visualization are all part of intelligence for businesses.

Business Intelligence

Business Intelligence Business Intelligence SQL Data Visualization

Hierarchies in Dimensional Modelling

Pickl AI

AUGUST 9, 2024

Hierarchies align data modelling with business processes, making it easier to analyse data in a context that reflects real-world operations. Designing Hierarchies Designing effective hierarchies requires careful consideration of the business requirements and the data model.

Data Warehouse

Data Warehouse Data Quality ETL Business Intelligence

From zero to BI hero: Launching your business intelligence career

Dataconomy

MARCH 24, 2023

Some of the common career opportunities in BI include: Entry-level roles Data analyst: A data analyst is responsible for collecting and analyzing data, creating reports, and presenting insights to stakeholders. They may also be involved in data modeling and database design.

Business Intelligence

Business Intelligence Business Intelligence Data Analysis Data Analysis

From zero to BI hero: Launching your business intelligence career

Dataconomy

MARCH 24, 2023

Some of the common career opportunities in BI include: Entry-level roles Data analyst: A data analyst is responsible for collecting and analyzing data, creating reports, and presenting insights to stakeholders. They may also be involved in data modeling and database design.

Business Intelligence

Business Intelligence Business Intelligence Data Analysis Data Analysis

Best Practices for Fact Tables in Dimensional Models

Pickl AI

AUGUST 11, 2024

Retail Sales In a retail data warehouse , the sales fact table might include metrics such as sales revenue, units sold, discounts applied, and profit margins. Web Analytics In a web analytics data warehouse, the page views fact table might include metrics such as total page views, unique visitors, session duration, and bounce rate.

Data Quality

Data Quality Data Warehouse Data Governance Analytics

The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

JULY 25, 2023

Their primary responsibilities include: Data Storage and Management Data Engineers design and implement storage solutions for different types of data, be it structured, semi-structured, or unstructured. They work with databases and data warehouses to ensure data integrity and security.

Data Engineering

Data Engineering Data Engineering Data Engineer Data Engineering

Benefits of Learning Tableau for Data Analysts

Pickl AI

MAY 7, 2024

Their tasks encompass: Data Collection and Extraction Identify relevant data sources and gather data from various internal and external systems Extract, transform, and load data into a centralized data warehouse or analytics platform Data Cleaning and Preparation Cleanse and standardize data to ensure accuracy, consistency, and completeness.

Data Analyst

Data Analyst Tableau Data Science Power BI

BI Tools Comparison to Improve Data Clarity | Women in Big Data

Women in Big Data

DECEMBER 9, 2024

There is a plethora of BI tools available in the market today, with new ones being added yearly. Through a comparative analysis of some of the leading BI tools: Google Looker, Microsoft Power BI, Tableau and Qlik Sense, discover which BI solution best fits your organization’s data analytics needs to empower informed decision-making.

Big Data

Big Data Big Data Power BI Tableau

Data Science Current

CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Modeling Fundamentals in Power BI

Trending Sources

How to Optimize Power BI and Snowflake for Advanced Analytics

Introduction to Power BI Datamarts

Data science vs data analytics: Unpacking the differences

What Are Business Intelligence Tools

Understanding Business Intelligence Architecture: Key Components

Who is a BI Developer: Role, Responsibilities & Skills

Hierarchies in Dimensional Modelling

From zero to BI hero: Launching your business intelligence career

From zero to BI hero: Launching your business intelligence career

Best Practices for Fact Tables in Dimensional Models

The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Benefits of Learning Tableau for Data Analysts

BI Tools Comparison to Improve Data Clarity | Women in Big Data

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