Data Analytics
At Steve Young Creative, we are passionate about equipping those either starting their data journey or taking that next step with the skills needed to thrive in the world of data. Our platform is structured around pivotal areas of data expertise:
Data Visualization and Storytelling: Our content unveils the power of data, emphasizing the visualization and narrative behind the numbers. Learn to craft stories that resonate and influence, transforming raw data into impactful visuals.
Data and Analytics: Gain in-depth knowledge with our comprehensive guides on analytics tools. From cost estimation to advanced analytics techniques, we cover all you need to become proficient in cloud-based data solutions.
Data Storytelling Explore deeper into data's significance in our broader analytics context. We dissect methodologies and impart understanding, equipping you to interpret and convey data's language with authority and creativity.
Discover the essential steps to launch a career in data analytics with no experience. This guide covers critical skills, educational pathways, and practical tips for aspiring data analysts, helping you turn your analytical prowess and problem-solving abilities into a thriving career.
Discover how implementing a style guide can revolutionize your data development projects. With our expert insights into the best style guide practices for your team, you can ensure consistency, enhance collaboration, and reduce errors.
This tutorial and sample workbook demonstrate how to enhance Excel tables and improve data usability within 5 minutes. Users learn to convert AI-created CSV files into tables, name tables for easier reference, format columns, insert slicers, and create dynamic filtered graphs. The tutorial includes a sample workbook on GitHub for reference.
This comprehensive guide explores the future of data analytics. It uncovers insights into its evolving types, techniques, and tools and explains how they shape opportunities in technical education. It is ideal for students and educators seeking to navigate and leverage the dynamic landscape of data-driven decision-making and innovation.
Drive impactful insights with expert data project management. Learn more today!
Managing data visualization, analytics, and AI projects requires a unique approach. Success hinges on clearly defining project goals, ensuring data quality, and adopting an iterative, agile process. A customized strategy is essential for data collection to security, governance, and visualization.
A deep understanding of your solution's architecture is essential for successful data visualization and business intelligence projects, as it enables the delivery of impactful insights and drives effective decision-making processes. This guide provides an in-depth look at the various parts that come into play when reviewing your data visualization project.
Being a Power BI enthusiast, I always find DAX a challenge but have found success by keeping to a couple of simple tricks. In this Power BI Tutorial, we review my DAX development workflow through an example case where we will use Power BI Desktop to create a KPI measure
Whether selecting the appropriate Power BI subscription for individuals or businesses, this guide analyzes the Power BI Free, Pro, and Premium plans. We'll explore the key differences and share some tips on signing up for Power BI if you need a work email address.
How To create a Power BI calculation that tests for the presence of a string in another column's text values. There are two ways to solve this, but the first is an interesting example you can use in several situations. This solution plays on the true-false values of the DAX IF function in PowerBI.
How do I make it easy for the end user to move the source Excel File around while making it easy to update the source location in PowerBI? Query Parameters solved that issue making the solution a lot easier to maintain.
Tackle data analytics on a budget! Smart scoping, requirements gathering, and strategic tips for a successful project.
This article offers valuable insights into the difference between data wrangling and data engineering in data analytics with Power BI, emphasizing the collaborative nature of the process. It is recommended for those seeking to improve their knowledge of data analytics using Power BI.
Data preparation is crucial in data analysis and machine learning projects. This article will explore basic concepts and extensive details on the various aspects of data preparation.
