Business Analytics
Quick definition: Business analytics means using data science to build models that help inform decision-making to improve organizational processes through a variety of methods.
Key takeaways:
- There are several different types of business analytics, including descriptive analytics, predictive analytics, and more. Each of these types of analytics has its purpose and method to improve business performance.
- Business analytics is the best and most effective way to gain insights about what’s working — and what’s not working — in your business processes to make your organization more successful.
- In the future, artificial intelligence (AI) and machine learning will have a big impact on business analytics. AI in business analytics will make the process much more democratized.
The following information was provided during an interview with Nate Smith, group product marketing manager for Adobe Analytics.
What is business analytics?
Is it always necessary for a business to use business analytics?
What are the different types of business analytics?
What’s the difference between business analytics and data analytics?
What’s the difference between business analytics and business intelligence?
What are the requirements to perform business analytics?
What are the challenges that come with business analytics?
How will business analytics look in the future?
What is business analytics?
Business analytics involves examining specific data sets designed to help businesses make accurate decisions that usually result in improved efficiency and higher profits.
This data comes from a variety of places but is most likely stored in one large data repository. Business analysts turn this data into insights to help improve their organization using a variety of methods and models.
Is it always necessary for a brand to use business analytics?
Business analytics is a necessary capability to be competitive in your industry. It’s extremely important for optimizing your business — how it runs, how customers interact with it, and how it earns revenue.
Business analytics is the most effective way to gain insights into what’s working — and what’s not working — in your business operations.
The only time that business analysis could be considered optional is if your business is just starting out.
It’s all right to focus first on building your products and making profits, but once your business has grown, you should start to use business analytics to make better decisions about how you run your company.
What are the different types of business analytics?
There are a few different types of business analytics:
Descriptive analytics
This involves using historical data to identify trends within a company’s business processes.
Diagnostic analytics
This is a deeper form of descriptive analytics that investigates the reasons behind certain outcomes. It means taking data and determining correlations.
Predictive analytics
This means using historical data to determine likely outcomes or events. With predictive analytics, you can employ machine learning and artificial intelligence for more accurate predictions.
Prescriptive analytics
This is a more advanced form of predictive analytics that’s used to recommend actions businesses can take to reach their goals. Most business analysts primarily use descriptive and predictive analytics, but the other two types of analytics can also prove valuable for businesses.
What’s the difference between business analytics and data analytics?
With business analytics, to a large extent, you’re using the same technologies as data analytics.
But though both types of analytics employ the same types of tools, business analytics is more focused on existing workflows and processes that pertain to business-informed decisions.
When reviewing data, a business analyst looks at things like purchase processes, revenue optimization, and other ways to improve business processes.
On the other hand, data analysis is performed by data scientists and is the broader, more technical part of the process.
Business analysts aren’t as technical as data scientists. Data scientists transform data, then business analysts take the transformed data sets and communicate information to other parts of the organization about how to optimize existing processes and metrics.
Data scientists take deep dives into data, determining trends and connections. Business analysts translate that work into useful insights about organizational processes.
What’s the difference between business analytics and business intelligence?
Most of the time, business intelligence(BI) is just data visualization. But this data is historical data — it doesn’t determine future outcomes but informs them of past occurrences.
This is where business analytics is different from business intelligence: because BI is only for descriptive reporting, not making predictions.
Business analytics can be used for diagnostic and predictive insights, while business intelligence cannot. It could be said that business intelligence is just an aspect of business analytics.
What are the requirements to perform business analytics?
To begin, your organization needs a fair amount of data from which to draw insights. You can gather this data from a variety of sources and keep it all in a data warehouse. You should also have proper data management tactics to keep things organized.
After you have your data sets, a team of data scientists explores the data and prepares it for visualization with a data visualization tool.
Once the data has been visualized, a team of business analysts can use methods like descriptive and predictive analytics with analytics tools to gain business insights.
Then they can present their findings to the appropriate stakeholders, who can make business decisions based on those data insights.
What are the challenges that come with business analytics?
There are many people involved with business processes who could improve them if they had access to the right data.
But in many cases, only the analytics groups have the data and can make sense of it. It’s critical to democratize business analytics as broadly as possible so that people throughout the organization have data to help them make better decisions.
How will business analytics look in the future?
In the future, purpose-built AI technology can handle the more advanced tasks of business analytics. This shift in technology will optimize the process of business analytics and make it more accessible to those who aren’t data scientists.