Business Intelligence, Analytics & Predictive Analytics for Consultants- Without the Tech Jargon

[lauravalentina_guevaradavila]

Breaking into the world of Consulting has never been more exciting. Whether you’re aiming to specialize in business or cloud technologies, one skillset cuts across all: understanding Business Intelligence and Analytics.  

Why? Because you’ll be advising clients on how to make decisions, and knowing the basics of BI and Analytics enables you to connect technical solutions with real business value, and this is something you can’t afford to ignore if you want to stand out as a tech consultant in the SAP ecosystem. Read through -> at the end, we’ll share the key resource that connects directly to your next step as a consultant.

What is Business Intelligence (BI), in simple terms? 

Business Intelligence (BI) is all about using tools and procedures to analyze and transform data into meaningful information. The goal? Helping companies make better and faster decisions. Whether it's a sales team spotting trends or the finance department looking for cost-saving opportunities, BI turns data into actionable insights for decision makers.  

Let’s break it down with a simple example 👇:   

Imagine you are advising a small grocery store with a cash register. After each sale, they print the receipt and pile them up on your desk.  Each receipt provides details like: 

• What product was sold 
• The price 
• The brand 
• The time of the sale 
• Which store location 

Now, if all those receipts just sit there in a messy pile without having structure or meaning, it’s nothing more than clutter!  This is where BI, analytics, and Predictive Analytics come in. By using BI, you can turn the cash register’s data into simple visuals that show: 

• Your top-selling products 
• Peak sales hours 
• Brands that bring the most profit 
• Stores that are performing best 

Wow! Now your client can make decisions with information that makes sense and leads to action. Therefore, if you see that soda sales double on Saturdays, you can advise them to stock more and keep folks happy. 

And what are the 5 stages of Business Intelligence? 

1. Collecting data from your store, customers, etc. 
2. Storing it in one place (like a database) 
3. Cleaning and modeling it (Analytics again) 
4. Visualizing and examining it (BI) 
5. Taking action with that insight 

 What is the difference between Analytics and BI? 

Analytics is the behind-the-scenes work: gathering all those receipts, cleaning mistakes (like wrong prices or product names), calculating new stuff (like profit or days payable outstanding), and structuring the data so it makes sense. However, Business Intelligence comes after: it’s visualizing the cleaned data in charts or dashboards, reports, and charts that anyone can understand. 

So, what about Predictive Analytics? 

If BI helps you understand the past and present, Predictive Analytics helps you plan, using past records to predict the future. For example, if December always brings a 40% uptick in chocolate sales, you can predict it’ll happen again and advise your client to prepare for this seasonal demand.  

Types of Predictive Analytics You’ll Encounter 

Depending on what you want to peek into the future, you’ll need to use different approaches:  

• Regression: Predicting numbers (e.g., next month’s sales) 
• Classification: Predicting categories (e.g., “Will this customer churn?”) 
• Segmentation: Grouping customers with similar behavior 
• Time-series: Forecasting trends over time (e.g., seasonal trend sales) 

Now, imagine scaling that grocery store to a multinational retailer client with millions of daily transactions. At that scale, you need robust tools to handle massive amounts of data, and that’s where SAP comes in. 

• In SAP Datasphere, you can gather, integrate, and model your cash register data (and other sources) for data analytics. 
• SAP Analytics Cloud (SAC) turns those models into dashboards, planning tools, and interactive visual stories (known as Intelligent Applications in SAP). This is where BI is done.   
• SAP Business Data Cloud (BDC), a cloud-native SaaS solution, combines Datasphere, SAC, SAP Business Warehouse (BW), and adds SAP Databricks for advanced AI and machine learning capabilities, allowing you to perform predictive analytics.  

Knowing how these pieces fit together will enable you to communicate confidently with both technical teams and business stakeholders, making you a more valuable consultant. 

🔵Ready to kickstart your career as a Consultant in SAP’s Ecosystem? 

Explore the SAP Digital Skills Center and discover our programs in your region (Only applicable for fresh graduates, unemployed, or underemployed in the EMEA region).  

Co-authored by @ByronCarvajalP and  @lauravalentina_guevaradavila 

[lauravalentina_guevaradavila]

Breaking into the world of Consulting has never been more exciting. Whether you’re aiming to specialize in business or cloud technologies, one skillset cuts across all: understanding Business Intelligence and Analytics.  

Why? Because you’ll be advising clients on how to make decisions, and knowing the basics of BI and Analytics enables you to connect technical solutions with real business value, and this is something you can’t afford to ignore if you want to stand out as a tech consultant in the SAP ecosystem. Read through -> at the end, we’ll share the key resource that connects directly to your next step as a consultant.

What is Business Intelligence (BI), in simple terms? 

Business Intelligence (BI) is all about using tools and procedures to analyze and transform data into meaningful information. The goal? Helping companies make better and faster decisions. Whether it's a sales team spotting trends or the finance department looking for cost-saving opportunities, BI turns data into actionable insights for decision makers.  

Let’s break it down with a simple example 👇:   

Imagine you are advising a small grocery store with a cash register. After each sale, they print the receipt and pile them up on your desk.  Each receipt provides details like: 

• What product was sold 
• The price 
• The brand 
• The time of the sale 
• Which store location 

Now, if all those receipts just sit there in a messy pile without having structure or meaning, it’s nothing more than clutter!  This is where BI, analytics, and Predictive Analytics come in. By using BI, you can turn the cash register’s data into simple visuals that show: 

• Your top-selling products 
• Peak sales hours 
• Brands that bring the most profit 
• Stores that are performing best 

Wow! Now your client can make decisions with information that makes sense and leads to action. Therefore, if you see that soda sales double on Saturdays, you can advise them to stock more and keep folks happy. 

And what are the 5 stages of Business Intelligence? 

1. Collecting data from your store, customers, etc. 
2. Storing it in one place (like a database) 
3. Cleaning and modeling it (Analytics again) 
4. Visualizing and examining it (BI) 
5. Taking action with that insight 

 What is the difference between Analytics and BI? 

Analytics is the behind-the-scenes work: gathering all those receipts, cleaning mistakes (like wrong prices or product names), calculating new stuff (like profit or days payable outstanding), and structuring the data so it makes sense. However, Business Intelligence comes after: it’s visualizing the cleaned data in charts or dashboards, reports, and charts that anyone can understand. 

So, what about Predictive Analytics? 

If BI helps you understand the past and present, Predictive Analytics helps you plan, using past records to predict the future. For example, if December always brings a 40% uptick in chocolate sales, you can predict it’ll happen again and advise your client to prepare for this seasonal demand.  

Types of Predictive Analytics You’ll Encounter 

Depending on what you want to peek into the future, you’ll need to use different approaches:  

• Regression: Predicting numbers (e.g., next month’s sales) 
• Classification: Predicting categories (e.g., “Will this customer churn?”) 
• Segmentation: Grouping customers with similar behavior 
• Time-series: Forecasting trends over time (e.g., seasonal trend sales) 

Now, imagine scaling that grocery store to a multinational retailer client with millions of daily transactions. At that scale, you need robust tools to handle massive amounts of data, and that’s where SAP comes in. 

• In SAP Datasphere, you can gather, integrate, and model your cash register data (and other sources) for data analytics. 
• SAP Analytics Cloud (SAC) turns those models into dashboards, planning tools, and interactive visual stories (known as Intelligent Applications in SAP). This is where BI is done.   
• SAP Business Data Cloud (BDC), a cloud-native SaaS solution, combines Datasphere, SAC, SAP Business Warehouse (BW), and adds SAP Databricks for advanced AI and machine learning capabilities, allowing you to perform predictive analytics.  

Knowing how these pieces fit together will enable you to communicate confidently with both technical teams and business stakeholders, making you a more valuable consultant. 

🔵Ready to kickstart your career as a Consultant in SAP’s Ecosystem? 

Explore the SAP Digital Skills Center and discover our programs in your region (Only applicable for fresh graduates, unemployed, or underemployed in the EMEA region).  

Co-authored by @ByronCarvajalP and  @lauravalentina_guevaradavila 

[Mobembe]

The application link says the role has been filled. Could you please confirm this is accurate?

[lauravalentina_guevaradavila]

Hi Mobembe! 

I'm glad to know you're interested in the SAP Young Professionals program! 🙌

Applications will open again in the upcoming weeks, so I’d definitely encourage you to stay tuned for the next announcement (we open cohorts per region).  In the meantime, you can keep building your skills at this link, where you’ll find free resources and learning journeys. That way, you’ll be ready to apply as soon as the next YPP cohort opens. 

Best regards, 

Valentina.