In a changing marketplace, it is crucial to stay relevant for a successful business. Considering this, business analytics can offer valuable insights to a company to beat competitors. When used effectively, it can prove to be a powerful tool for business growth.
Considering the increasing demand for business analytics professionals, one can pursue this lucrative career option by enrolling in a reputable course like IIM Calcutta Senior Management Programme in Business Analytics. Read ahead to learn more about business analytics and how data analytics influences business decisions.
Understanding Business Analytics
Involving a process of collecting, organising, analysing, and interpreting data, business analytics helps gain insights to make informed business decisions. Featuring statistical and quantitative analysis, it can be applied to different aspects of business that include sales, finance, marketing, operations, and customer service. Data analysis of various areas of business can help organisations identify trends, patterns, and correlations to make decisions, optimising their business processes.
Further, business analytics uses data mining, machine learning algorithms, data visualisation and predictive analytics to process and analyse large volumes of data. It helps improve the competitiveness and profitability of businesses in today's data-driven environment. For instance, analysing customer data can not only help improve customer retention, but also increase sales.
How data analytics influences business decisions? Answering this question, business analytics helps identify opportunities for expansion, make strategic decisions about resource allocation, predict future outcomes and improve overall performance.
Business Analytics Types
The following are some of the most common types of business analytics that businesses use to gain key insights:
- Descriptive analytics: Involves analysing historical data
- Diagnostic analytics: Includes analysing data to learn why something happened in the past
- Prescriptive analytics: Uses data and insights to make decisions about future actions
- Predictive analytics: Involves analysing data to make predictions for future
- Spatial analytics: Includes analysing geographic data
- Text analytics: Involves analysing unstructured data like customer feedback and social media posts
Business Intelligence vs. Data Science
Business intelligence (BI) involves the process of collecting, analysing, and presenting data to support decision-making. It focuses on sharing data summary in the form of reports and dashboards.
On the other hand, data science involves different techniques like statistical analysis, machine learning, and data visualisation to gain insights from data. It typically focuses on analysing large and complex data sets, such as text data, image data, and social media data.
Notably, business analytics and data science are related to using data to extract insights for effective decision-making. But, they differ in their focus and techniques. Also, it is to be noted that though related, business analytics and business intelligence are distinct concepts.
Business Analytics Essentials
The following are some essentials of business analytics:
- Data collection and management
- Data analysis
- Data visualisation
- Predictive modeling
- Business intelligence
- Data-driven decision-making
Importance of Business Analytics
Here are the reasons for adopting business analytics:
- Get insights that help make data-driven decisions to effectively achieve goals, improve efficiency and optimise business operations
- Gain a competitive advantage by identifying opportunities and risks
- Identify areas for improvement for enhanced performance
- Better understanding of customers to meet their needs and increase satisfaction
- Mitigate risk by predicting potential outcomes and reducing the odds of negative consequences
Benefits of Business Analytics
The following are the benefits of using business analytics tools:
- Eliminate guesswork and reduce potential financial loss
- Reveal vulnerabilities in processes and improve security
- Optimise customer outreach
- Spot risk factors and take preventive measures
Conclusion
In today’s day and age, the business landscape has become data-driven. This makes it essential for managers across different business operations to acquire analytics skills. The valuable insights gained as a result of analysing vast amounts of data can not only help tackle different challenges effectively, but also make informed business decisions, enabling growth.
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