Data Models, ETL and Power BI - Data Science Current

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

How and When to Use Dataflows in Power BI

phData

SEPTEMBER 28, 2023

Power BI Desktop enables the connection and retrieval of data from various sources, followed by data transformation using Power Query. To address this challenge, Microsoft introduced Dataflows within the Power BI service. What are Dataflows in Power BI?

Power BI

Power BI Data Preparation Machine Learning Machine Learning

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. What is Power BI Datamarts? What is a Datamart?

Power BI

Power BI Data Warehouse ETL Data Preparation

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How to Create a Power BI Dataflow with Snowflake Data

phData

DECEMBER 2, 2024

We at phData have written extensively about creating centralized data products in Power BI. Most Power BI developers are familiar with Power Query , Which is the data transformation layer of Power BI. This step can be performed as many times as needed across as many data models.

Power BI

Power BI Data Modeling Data Models Data Visualization

How to Build a Power BI Datamart Using Snowflake Data

phData

JULY 11, 2023

Power BI Datamarts is one of the most exciting features that Microsoft has released for the Power Platform in recent years. If you need high-level information on what a Power BI Datamart is and some example use cases, check out our other blog, What Are Power BI Datamarts?

Power BI

Power BI SQL Azure ETL

Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

Data Science Dojo

OCTOBER 31, 2024

Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Strong analytical skills and the ability to work with large datasets are critical, as is familiarity with data modeling and ETL processes.

Data Science

Data Science Data Scientist Machine Learning Machine Learning

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

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

5 Reasons Why SQL is Still the Most Accessible Language for New Data Scientists

ODSC - Open Data Science

APRIL 6, 2023

But its status as the go-between for programming and data professionals isn’t its only power. Within SQL you can also filter data, aggregate it and create valuations, manipulate data, update it, and even do data modeling. One set of tools that are becoming more important in our data-driven world is BI tools.

SQL

SQL Data Scientist Database Data Science

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

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Warehousing: Amazon Redshift, Google BigQuery, etc.

Data Engineering

Data Engineering Data Engineering Data Engineer Data Engineering

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

Why Improving Problem-Solving Skills is Crucial for Data Engineers?

DataSeries

AUGUST 15, 2024

Knowledge of Core Data Engineering Concepts Ensure one possess a strong foundation in core data engineering concepts, which include data structures, algorithms, database management systems, data modeling , data warehousing , ETL (Extract, Transform, Load) processes, and distributed computing frameworks (e.g.,

Data Engineering

Data Engineering Data Engineering Data Engineer Data Engineering

Best Practices for Fact Tables in Dimensional Models

Pickl AI

AUGUST 11, 2024

These tools enable effective data structuring, transformation, and analysis, supporting best practices for dimensional modelling and ensuring high-quality, consistent business metrics. These tools are essential for populating fact tables with accurate and timely data.

Data Quality

Data Quality Data Warehouse Data Governance Analytics

Your Essential Guide to MongoDB Interview Questions and Answers

Pickl AI

JULY 18, 2024

MongoDB is a NoSQL database that uses a document-oriented data model. It stores data in flexible, JSON-like documents, allowing for dynamic schemas. Each document can have a different structure, allowing for flexibility in data modelling. 2024’s top Power BI interview questions simplified.

Database

Database SQL Data Analyst Database Administration

Data Science Current

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

How and When to Use Dataflows in Power BI

Webinars

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Introduction to Power BI Datamarts

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How to Create a Power BI Dataflow with Snowflake Data

How to Build a Power BI Datamart Using Snowflake Data

Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

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From zero to BI hero: Launching your business intelligence career

From zero to BI hero: Launching your business intelligence career

5 Reasons Why SQL is Still the Most Accessible Language for New Data Scientists

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

Hierarchies in Dimensional Modelling

Why Improving Problem-Solving Skills is Crucial for Data Engineers?

Best Practices for Fact Tables in Dimensional Models

Your Essential Guide to MongoDB Interview Questions and Answers

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