Blog Post

Analytics vs. Advanced Analytics

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Summary

Advanced analytics goes beyond traditional data analysis, helping businesses predict trends, manage risks, and uncover new opportunities. It works with all types of data—structured or not—and uses techniques like machine learning to provide deeper insights. In this article, we’ll explain what advanced analytics is, how it differs from standard methods, and how it can help your business grow. If you’re ready to learn more about how it can keep you ahead of the curve, let’s dive in! 

Introduction

People have been using analytics in their daily lives for ages, often without even realizing it. We analyze countless aspects—our emotions, expenses, and interactions with others. The same goes for companies; to effectively meet customer needs, they must analyze their processes, services, and more. This is analytics in its simplest form. 

But what about advanced analytics? What sets it apart? In this article, we’ll break down the concept of advanced analytics in straightforward terms, making it easier to understand, even if you find the technical details challenging. Let’s explore what makes advanced analytics so powerful and essential for today’s businesses. 

Why and How is Analytics Used? 

Traditional analytics is extremely valuable for analyzing historical and current data. For instance, after launching a new product, you would typically use analytics to track sales figures, identify which products are most popular, and understand market adoption. This analysis helps you pinpoint mistakes, recognize areas for improvement, and refine your strategies. 

To conduct any kind of analytics, you need structured data organized in tables or databases. Common tools and technologies for this include Excel, Tableau, and SAS, which help generate financial and sales reports. 

But what happens when you’re dealing with unstructured data? Or if you want to minimize the risk of low market adoption? What if you want to uncover patterns and automatically create statistical models? That’s where advanced analytics comes into play. 

What is Advanced Analytics? 

While traditional analytics can answer many questions and be valuable for businesses, it falls short when it comes to predicting future outcomes and managing risks. Advanced analytics, on the other hand, tackles more complex and nuanced questions. It can work with not just structured data, but also semi-structured and unstructured data—and a lot of it. 

Advanced analytics employs techniques like data mining, sentiment analysis, and machine learning to predict future trends and recognize patterns. We won’t dive into these technicalities here, and there’s no need to worry if you’re unfamiliar with them. Unless you aim to become a data engineer or scientist, it’s enough to understand what advanced analytics is, the use cases it can address, and whether it can benefit your business.  

What Can Advanced Analytics Help Me With? 

With advanced analytics, you’ll gain insights into what actions to take to shape a better future for your business. It can help you understand customer behavior and uncover new opportunities. With the right data, you’ll make more accurate predictions, reduce risks, detect and prevent fraud, identify where to invest, and much more. Here are a few key questions advanced analytics can answer: 

What factors drive customer churn, and how can we reduce it?

How can we detect and prevent fraudulent transactions more effectively?

Which products should be stocked in each store to maximize regional sales?

How can we forecast customer buying patterns for the upcoming quarter?

Which suppliers are the most reliable based on past performance?

Which processes are causing bottlenecks and how can we streamline them to improve efficiency?

Which areas of our operations can benefit the most from process automation, and how do we implement it?

What steps can we take to ensure a more resilient and agile value chain in the face of disruptions?

How can we predict machine maintenance needs to reduce downtime and increase production capacity?

How can we better predict supply and demand fluctuations to optimize inventory levels and avoid stockouts? 

The advanced analytics market is projected to grow from $47.38 billion in 2024 to $125.26 billion by 2029, reflecting a robust CAGR of 21.46%.

Moving Forward 

Advanced analytics might seem complex at first, but once you start gaining the benefits, you won’t regret your decision to integrate it into your business. It saves money, boosts revenue, and helps you stay competitive. The bad news is that more companies are starting to take advantage of advanced analytics. The good news is that if you’re ready to take the next step, we can help you stay ahead. The best time to implement advanced analytics was yesterday. The second-best time is now. 

Let’s make data smart for you.

Contact our consultants and Excel at your board meetings.
My mission is to change your life in how you make everyday decisions based on proper data. I do this by helping corporate data leaders create and adopt data strategies built on Microsoft platforms using artificial intelligence. Over my 15+ year career, I have gained experience which I use to mentor clients and pass on to community as a speaker and data leader in the industry.

Jaroslav Reken

Co-Founder & Data Strategist

 

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The post Analytics vs. Advanced Analytics appeared first on Joyful Craftsmen.

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