What is Business Analytics

What is Business Analytics

Business analytics (BA) is a set of disciplines and technologies for solving business problems using data analysis, statistical models and other quantitative methods. It involves an iterative, methodical exploration of an organization's data, with an emphasis on statistical analysis, to drive decision-making.

Data-driven companies treat their data as a business asset and actively look for ways to turn it into a competitive advantage. Success with business analytics depends on data quality, skilled analysts who understand the technologies and the business, and a commitment to using data to gain insights that inform business decisions.

Types of Business Analytics

When you use these four types of analytics, your data can be cleaned, dissected, and absorbed in a way that makes it possible to create solutions for no matter what challenges your organization may face.

Descriptive analytics: Interpretation of historical data and KPIs to identify trends and patterns. This allows for a big picture look of what happened in the past and what is happening currently using data aggregation and data mining techniques.

Many companies use descriptive analytics for a deeper look into the behavior of customers and how they can target marketing strategies to those customers. 

Diagnostic analytics: Focuses on past performance to determine which elements influence specific trends.

This is done using drill-down, data discovering, data mining, and correlation to reveal the cause of specific events. Once an understanding is reached regarding the likelihood of the event, and why an event may occur, algorithms are used for classification and regression. 

Predictive analytics: Uses statistics to forecast and assess future outcomes using statistical models and machine learning techniques. This often takes the results of descriptive analytics to create models that determine the likelihood of specific outcomes.

This type is often used by sales and marketing teams to forecast opinions of specific customers based on social media data.

Prescriptive analytics: Uses past performance data to recommend how to handle similar situations in the future. Not only does this type of business analytics determine outcomes, but it can also recommend the specific actions that need to occur to have the best possible result. This is often achieved using deep learning and complex neural networks.

This type of business analytics is often used to match various options to real-time needs of a consumer.

Using business analytics tools

Business data analytics has many individual components that work together to provide insights. While business analytics tools handle the elements of crunching data and creating insights through reports and visualization, the process actually starts with the infrastructure for bringing that data in. A standard workflow for the business analytics process is as follows:

Data collection: Wherever data comes from, be it IoT devices, apps, spreadsheets, or social media, all of that data needs to get pooled and centralized for access. Using a cloud database makes the collection process significantly easier.

Data mining: Once data arrives and is stored (usually in a data lake), it must be sorted and processed. Machine learning algorithms can accelerate this by recognizing patterns and repeatable actions, such as establishing metadata for data from specific sources, allowing data scientists to focus more on deriving insights rather than manual logistical tasks.

Descriptive analytics: What is happening and why is it happening? Descriptive data analytics answers these questions to build a greater understanding of the story behind the data.

Predictive analytics: With enough data—and enough processing of descriptive analytics —business analytics tools can start to build predictive models based on trends and historical context. These models can thus be used to inform future decisions regarding business and organizational choices.

Visualization and reporting: Visualization and reporting tools can help break down the numbers and models so that the human eye can easily grasp what is being presented. Not only does this make presentations easier, but these types of tools can also help anyone from experienced data scientists to business users quickly uncover new insights.

What is business analytics in MBA

An MBA in Business Analytics is a program that explores the data analytics component of running a business. This course teaches how to leverage statistics and tools dealing with data analytics. The syllabus includes material on business fundamentals, management practices and technical skills.

Surveys have shown that hiring managers look for candidates with business analytical skills and an MBA in the same definitely gives an edge. At the same time, a dearth of qualified business analysts also adds value to this degree.

In this blog, we will explore the various facets of this degree in terms of the scope of the course, fees, admission procedure and eligibility. You will also get to know about the career prospects, salary estimates and job opportunities. This blog will also inform you about the interesting facets of an MBA degree.

Also Read: MBA Courses List: Specialization, Eligibility, Top Colleges, 

Business Analytics vs BI

On the face of it, there may not seem to be much difference between business analytics and business intelligence. Some overlap does exist between the two, but looking at business analytics versus business intelligence still creates a gap that needs some explanation.

Certainly, the terms are extremely connected, but business intelligence uses historical and current data to understand what happened in the past and what is happening now. Business analytics, on the other hand, builds on the foundation of business intelligence and attempts to make educated predictions about what might happen in the future. In order to make data-driven predictions about the likelihood of future outcomes, business analytics uses next-generation technology, such as machine learning, data visualization, and natural language query.

Business Analytics Vs Data Science

Business Analytics vs Data Analytics

Data analytics and business analytics each involve a slightly different skillset. While both occupations work with data, they do so in different ways. Here’s a look at some common skills for each.

Top 10 business analyst certifications

• Certified Analytics Professional (CAP)
• IIBA Entry Certificate in Business Analysis (ECBA)
• IIBA Certification of Competency in Business Analysis (CCBA)
• IIBA Certified Business Analysis Professional (CBAP)
• IIBA Agile Analysis Certification (AAC)
• IIBA Certification in Business Data Analytics (CBDA)
• IQBBA Certified Foundation Level Business Analyst (CFLBA)
• IREB Certified Professional for Requirements Engineering (CPRE)
• PMI Professional in Business Analysis (PBA)
• SimpliLearn Business Analyst Masters Program

Benefits of Business Analytics For a company and Individual

Business analytics benefits impact every corner of your organization. When data across departments consolidates into a single source, it syncs up everyone in the end-to-end process. This ensures there are no gaps in data or communication, thus unlocking benefits such as:

Data-driven decisions: With business analytics, hard decisions become smarter—and by smart, that means that they are backed up by data. Quantifying root causes and clearly identifying trends creates a smarter way to look at the future of an organization, whether it be HR budgets, marketing campaigns, manufacturing and supply chain needs, or sales outreach programs.

Easy visualization: Business analytics software can take unwieldy amounts of data and turn it into simple-yet-effective visualizations. This accomplishes two things. First, it makes insights much more accessible for business users with just a few clicks. Second, by putting data in a visual format, new ideas can be uncovered simply by viewing the data in a different format.

Modeling the what-if scenario: Predictive analytics creates models for users to look for trends and patterns that will affect future outcomes. This previously was the domain of experienced data scientists, but with business analytics software powered by machine learning, these models can be generated within the platform. That gives business users the ability to quickly tweak the model by creating what-if scenarios with slightly different variables without any need to create sophisticated algorithms.

Go augmented: All of the points above consider the ways that business data analytics expedite user-driven insights. But when business analytics software is powered by machine learning and artificial intelligence, the power of augmented analytics is unlocked. Augmented analytics uses the ability to self-learn, adapt, and process bulk quantities of data to automate processes and generate insights without human bias.

Importance of Business Analytics

More and more departments are trying to better understand how their decisions and budgets affect the business at large. With business analytics software, it’s possible to use data to drive strategic decisions, regardless of task or department:

Marketing: Analytics to identify success and impact
Which customers are more likely to respond to an email campaign? What was the last campaign’s ROI? More and more marketing departments are trying to better understand how their programs affect the business at large. With AI and machine learning powering analysis, it’s possible to use data to drive strategic marketing decisions. Learn more

Human Resources: Analytics to find and share talent insights
What actually drives employee decisions regarding their career? More and more HR leaders are trying to better understand how their programs affect the business at large. With the right analytical capabilities, HR leaders are able to quantify and predict outcomes, understand recruitment channels, and review employee decisions en masse. Learn more

Sales: Analytics to optimize your sales
What is the critical moment that converts a lead to a sale? In-depth analytics can break down the sales cycle, taking in all of the different variables that lead to a purchase. Price, availability, geography, season, and other factors can be the turning point on the customer journey—and analytics offer the tool to decipher that key moment. Learn more

Finance: Analytics to power predictive organizational budgets
How can you increase your profit margins? Finance works with every department, be it HR or sales. That means that innovation is always key, especially as finance departments face larger volumes of data. With analytics, it’s possible to bring finance into the future for predictive modeling, detailed analysis, and insights from machine learning. 

Business Analytics: Job and Salary

Starting Salary

The starting salary of a professional in Business Analysts can earn anywhere between INR 2,50,000 - 4,50,000 per annum. Given below is a list of starting salaries based on various job profiles.

Experience - Wise Salary

The Salary of a Business Analyst may also differ depending on the experience of an employee. The salaries at entry level and experience level are different. Given below are the details of the salaries depending on the experience.