Business Analytics

What is business analytics?

Business analytics is the process of analyzing business data to understand and improve business operations and performance. It involves using techniques such as data mining, statistical analysis, modeling, and machine learning to analyze large amounts of data and discover patterns and trends. This information can then be used to make better business decisions, a process characterized by business intelligence (BI).

Adopting business analytics with diverse data sets is now vital for modern organizations. Leveraging better data for competitive value is crucial for maximizing future outcomes. “Analytics and business intelligence platforms are an essential part of a flexible, end-to-end architecture for integrating and analyzing diverse data sources,” as Gartner describes. With the right data, companies across all sectors can apply business analytics to improve their understanding of key business elements, such as customer experience, operational efficiencies, supply chain risks, and others.

How does business analytics work?

Business analytics relies on data. Data experts first need to collect data from a variety of sources, including business transactions, social media activity, customer behavior, sensors, and many others. There are a number of methods available for data teams to collect data for analysis, the most effective of which are part of today’s modern business analytics technologies.

Once the raw data is collected, business data experts cleanse and process the desired data to remove any errors or inaccuracies. When the data is ready, business intelligence analysts assess any actionable insights and begin applying various analytical techniques to it to discover patterns and trends. The most common techniques used in business analytics include:

• Statistical analysis: a set of methods used to describe, summarize, and interpret data.
• Data mining: a technique that involves automatically discovering hidden patterns in large data sets.
• Modeling: the process of creating a mathematical representation of a real-world phenomenon.
• Machine learning: the process of teaching computers to learn from data without being explicitly programmed.
• Data storytelling: the process of using data to tell a story that informs, persuades, or inspires.

It is through these methods that business analytics facilitates a transition from collecting and housing data to using that data to drive future outcomes.

What are the different types of business analytics?

Over several decades, business analytics has evolved from the manual analysis of statistical data to become a multidisciplinary field that incorporates a wide range of techniques and technologies, oftentimes using BI software. As business analytics has become more sophisticated, so too have the different types of business analytics that organizations can leverage. Here are five of the most common types:

• Descriptive analytics:  Analysts create a representation of something that has happened in the past. Descriptive analytics is often used to generate reports and dashboards that summarize business performance.
• Diagnostic analytics:  Analysts attempt to understand why something happened. Diagnostic analytics involves drilling down into data to identify the root cause of a problem, issue, or event.
• Predictive analytics:  Analysts use historical data to make predictions about future events. Predictive analytics is often used for market forecasting, business planning, cybersecurity, or preventing equipment breakdowns, among other purposes.
• Prescriptive analytics:  Analysts go one step further than predictive analytics by predicting something and then recommending what should be done about it to achieve a desired outcome.
• Decision intelligence (DI):  The next evolutionary step of business intelligence (BI), decision intelligence is a type of business analytics that focuses on helping users throughout an organization make better decisions. DI platforms like Pyramid Analytics can provide users of all backgrounds with advanced analytics capabilities via easy-to-use tools and dashboards.

Businesses can leverage any combination of these different types of business analytics to suit their specific needs and improve business operations.

What are the key benefits of business analytics?

Better data-driven decisions can yield a variety of business benefits depending on how companies utilize their capabilities. Some ways business analytics brings about better business outcomes include:

• Improved business performance:  Business analytics can be used to identify inefficiencies and areas for improvement within an organization. By making data-driven decisions, businesses can optimize their operations and improve their bottom line.
• Increased customer satisfaction:  Businesses that leverage business analytics can gain a deeper understanding of their customers. This enables them to provide a better customer experience, which can lead to increased satisfaction, loyalty, and revenue.
• Reduced business risks:  Business analytics help organizations identify and mitigate risks. For example, procurement teams can use advanced analytics to select the most dependable suppliers and reduce supply chain disruptions in the future.

There is no limit to the applications of business analytics. Data and business leaders continue to find new use cases for business analytics as new technologies emerge, so the opportunity for improvement is truly endless.

What is Pyramid Analytics?

Pyramid Analytics is a leading provider of decision intelligence technologies — the next evolutionary stage of business analytics. Our software helps companies by providing them with the tools they need to make better decisions faster.

Contact us today to learn more about how we can help your business with business analytics.