Business Analytics vs. Data Analytics: What’s the Difference?

Data analytics and business analytics subfields of data science have gained traction in the world of business.

Businesses are collecting more data than ever and basing their decisions on this trove of information.

Yet, it can be challenging to determine which data analytics is ideal for your course. Therefore, exhausting the topic of data analytics vs. business analytics is crucial.

Assume you’ve been promoted to CEO of a manufacturing firm. Let’s see how you can use data and business analytics together to your benefit.

You can use data analytics to examine production data and spot efficient processes. Consequently, optimize the production process to cut expenses and boost revenue.

Business analytics will help you analyze customer data to determine which products sell best. Thus, you can decide which products to promote and which ones to stop producing.

Are you trying to understand the differences between business analytics and data analytics? You have come to the right place. This article will explain data analytics vs. business analytics and how you can gain insights from both.

Table of Content:

1. Exploring Data Analytics?
2. Exploring Business Analytics?
3. Business Analytics vs. Data Analytics: Key Differences
4. Types of Data Analytics & Business Analytics
5. How to Get Insights in Business and Data Analytics?
6. Wrap Up

Exploring Data Analytics

Data analytics involves analyzing large amounts of data to draw valuable insights. It entails using a variety of approaches and techniques, including algorithms and statistical models, to uncover trends and patterns.

But what does a data analyst do in this process? A data analyst plays a crucial role by interpreting the data, identifying trends, and providing actionable insights that help organizations make informed decisions.

Data analytics is applicable in various industries, including healthcare analytics, manufacturing, finance, marketing, and education.

Exploring Business Analytics

Business analytics is the process of examining and interpreting data to assess business operations and performance. Consequently, helps with solving problems.

Typically, business analytics is used to:

• Study market and customer trends.
• Find areas for improvement.
• Evaluate the results of marketing initiatives.
• Find areas for cost savings.
• Mitigate potential risks.

Business analytics help businesses with decision-making and developing strategies for growth and success.

Business Analytics vs. Data Analytics: Key Differences

Now, let’s see how business analytics and data analytics compare.

• Scope

The scope of business analytics is assessing performance and creating plans to address business problems. In contrast, data analytics concentrates on developing algorithms and predicting models to glean valuable insights from data.

• Objectives

Business analytics aims to improve business operations by assisting in problem-solving and decision-making. Analytics Visual plays a crucial role here, as it helps in translating data into visual insights, making complex information easier to understand and act upon. Data analytics aims to glean insights into various disciplines for various uses.

• Approach

Data analytics relies on predictive and prescriptive analytics and involves statistical and quantitative analysis. Business analytics uses descriptive analytics and involves qualitative analysis.

• Data

Business analytics relies heavily on structured data, while data analytics often focuses on analyzing structured data and unstructured data to extract valuable insights from diverse information sources.

• Audience

Business analytics is for decision-makers inside an organization, involving data and analytics services to resolve issues and make operations improvement decisions. On the other hand, data analytics is for professionals like statisticians, data scientists, marketers, and others who utilize data and analytics services to drive insights and strategies.

Types of Data Analytics & Business Analytics

• Descriptive Analytics

Descriptive analytics provide a summary of the data. It aims to provide a better understanding of the data allowing for improved decision-making.

Descriptive analytics helps uncover relationships between factors such as customer demographics and purchase amounts. For example, descriptive analytics can show that customers aged 25-35 tend to make larger purchases than customers aged 55-65.

• Diagnostic Analytics

Understanding the cause of something is easier with the use of diagnostic analytics. You can make wiser decisions if you know why something is happening.

It enables you to spot potential problems before they become serious. Additionally, it aids in identifying opportunities for increased effectiveness and efficiency.

• Predictive Analytics

Predictive analytics forecasts future outcomes using mathematical models, statistical algorithms, and machine learning. It entails evaluating historical data to build a predictive model capable of anticipating future events.

It aids in forecasting consumer behavior, tracking user activity, and predicting stock prices, among other applications. By leveraging a marketing analytics platform, you can strategize on improving customer experience, streamlining processes, and increasing revenue.

• Prescriptive Analytics

Prescriptive analytics combines data from several sources to provide a solution or recommendation for a problem. It generates insights and informs decision-making by utilizing predictive models and data.

Prescriptive analytics helps businesses identify opportunities, develop strategies, and execute tactics to maximize outcomes. You can use it to forecast the outcomes of various actions and scenarios. Consequently, suggest the best course of action for achieving desired objectives.

How to Get Insights in Business and Data Analytics?

When it comes to data analytics and business analytics, Excel reigns supreme.

However, gleaning insights from data in Excel can be challenging.

That’s why we created ChartExpo to get insights from your data easily.

ChartExpo is a potent visualization tool that seamlessly integrates with Excel. With ChartExpo, you can turn your data into insightful charts and dashboards in a few clicks. You can also create complex charts, like Sankey Charts, for deeper gleaning of insights.

Benefits of Using ChartExpo

• You can customize your visualizations to provide the most accurate and up-to-date visual representation of the data through effective information design. These customized visuals enable your audience to quickly discern crucial information from the data.
• The interface has an intuitive design. You can complete complex tasks with a few clicks. As a result, even without coding skills, you can quickly learn how to create insightful visualizations.
• ChartExpo is an excellent choice for cost-conscious users who want to create insightful visuals without breaking the bank. ChartExpo also offers free trial versions for testing the features and functions before committing to a plan. Nevertheless, it has an affordable $10 monthly plan.

How to Install ChartExpo in Excel?

1. Open your Excel application.
2. Open the worksheet and click the “Insert” menu.
3. You’ll see “My Apps”.
4. In the office Add-ins window, click “Store” and search for ChartExpo on my Apps Store.
5. Click the “Add” button to install ChartExpo in your Excel.

ChartExpo charts, available as data visualization tools for both Google Sheets and Microsoft Excel, let you create beautiful visualizations with just a few clicks. Use the following CTAs to install the tool of your choice and enhance your data presentations effortlessly.

Example

Let’s use the data below to create a meaningful visualization with ChartExpo. Then use the visualization to glean insights from the data.

Total Cost	Company Type	Company Name	Expertise Categories	Expertise	Cost
Total Cost	Subcontractor	Skyline Contractors	Mechanical Installation	Plumbing & Heating	15456
Total Cost	Subcontractor	Skyline Contractors	Mechanical Installation	Mechanical Work	10159
Total Cost	Subcontractor	Onyx General Contractors	Mechanical Installation	Plumbing & Heating	18045
Total Cost	Subcontractor	Onyx General Contractors	Mechanical Installation	Mechanical Work	12695
Total Cost	Subcontractor	Living Well Remodeling	Mechanical Installation	Plumbing & Heating	14589
Total Cost	Subcontractor	Living Well Remodeling	Mechanical Installation	Welding	11456
Total Cost	Supplier	Power-up Builders	Raw Material	Cement	20561
Total Cost	Supplier	Power-up Builders	Raw Material	Steel	32456
Total Cost	Supplier	Five-star Construction	Raw Material	Bricks	10253
Total Cost	Supplier	Five-star Construction	Raw Material	Timber	9000

• To get started with ChartExpo, install ChartExpo in Excel.
• Now Click on My Apps from the INSERT menu.

• Choose ChartExpo from My Apps, then click Insert.

• Once ChartExpo is loaded. Click on “Sankey Chart” from the list of charts.

• Click the “Create Chart From Selection” button after selecting the data from the sheet, as shown.

• The Sankey Chart will look as follows.

• The Level 4 (Expertise Categories) Node of “Mechanical Installation” has a messy flow of outgoing links.

• To make the outgoing smoother, you need a clear understanding of the links coming out of that node. There is a specific order. The image below has link sequence numbers in it.

• To alter the sequence of the link, click “Edit Chart”.

• Go to the top of the Mechanical Installation node. Click the pencil icon to open the “Sort Outgoing Links” property. You can then see the sequence of nodes.

• Rearrange the links in the desired order.

• • Link 1
  • Link 3
  • Link 5
  • Link 2
  • Link 4
  • Link 6

• Click the “Apply” button to save the changes.

• You can now observe that the flow of the Mechanical Installation is seamless.

• To change the title of the chart, click on the pencil icon that is available very next to Chart Header.
• It will open the properties dialog. Under the Text section, you can add a heading in Line 1 and enable the Show option. Give the appropriate title of your chart and click on the Apply button.

• To change the node color, click on the pencil icon available with the node. Expand the Node properties and change color from the Node Color property.

• Click on the highlighted pencil icon to add a Prefix (e.g., the $ sign) to the numeric values in the chart.
• Open the “Symbols” properties and enter the Prefix (e.g., the $ sign). Then click the “Apply” button to save all the changes.
• To maintain the changes made to the chart, click on the “Save Changes” button.

• Your final chart will look like the as below.

Insights

• At Level 1 (Total Cost), the procurement cost was $154.67K.
• At Level 2 (Company Type), $72.27K was spent on suppliers, which accounted for 47% of the Cost. $82.4K was spent on subcontractors, making up the remaining 53%.
• At Level 3 (Company Name), the $72.27K supplier costs were divided between the following;
  • Power-up Builder who charged$53.02K.
  • Five-star Construction, who charged $19.25K.
• The $82.4K subcontractor costs were divided as follows;
  • Skyline Contractors (25.62K)
  • Onyx General Contractors (30.74K)
  • Living Well Remodeling ($26.05K)
• At Level 4 (Expertise Categories), $72.27K was spent on suppliers providing raw materials. While $82.4K was spent on companies providing mechanical installations.
• The total raw material cost of $72.27k was spent on the following;
  • Cement ($20.56k)
  • Steel ($32.46k)
  • Timber ($10.25k)
• The total mechanical installation cost of $82.4k was allocated as follows;
  • Plumbing Heating ($48.09k)
  • Mechanical Work ($22.85k)
  • Welding ($11.46k)

FAQs:

What is the difference between data analytics and business analytics?

You can glean insights from different sources of data using data analytics. Business analytics aims to boost bottom-line results by resolving issues and increasing efficiency.

What are the types of data analytics and business analytics?

Data analytics and business analytics are divided into four categories:

• Descriptive analytics provide a better analysis of the data.
• Diagnostic analytics explains why something is happening/happened.
• Predictive analytics forecasts future outcomes.
• Prescriptive analytics provides solutions or recommendations to a problem.

Which is better, data analytics or business analytics?

The type of analytics depends on your objectives and the data you need to analyze. Data analytics is useful in gleaning insights. On the other hand, business analytics helps you identify ways to improve operations and create effective strategies.

Wrap Up

This blog post has discussed the topic of business analytics vs. data analytics.

Data analytics analyzes said data to gain useful insights. Business analytics aims to help businesses solve problems and make better decisions.

Data analytics is for professionals like statisticians, data scientists, marketers, and others. Business analytics is for problem solvers and decision-makers through descriptive and qualitative models.

Making sense of data in Excel can be challenging.

Luckily, ChartExpo comes to your rescue.

ChartExpo is a powerful visualization that smoothly integrates with Excel. You can quickly transform your data into insightful charts and graphs using ChartExpo.

ChartExpo helps you visualize your data to glean valuable insights for use in instances such as decision-making. You can also use these insights to strategize on improving customer experience, streamlining processes, and increasing revenue.