Business data analytics is a practice by which a specific set of techniques, capabilities, and procedures are applied to perform the continuous exploration and investigation of past and current business data for the purposes of obtaining an understanding about a business that can lead to improved decision-making. Data plays an essential role when it comes to crucial decision making for businesses. It essentially consists of quantitative and statistical analysis, predictive modeling, data mining, multivariate testing, and more. Today, almost every organization is trying its best to use business analytics for its decision-making purposes. Business data analysts are professionals with a very active role to play in an organization. The role of a business data analyst is multi-dimensional and he manages various aspects of a business. In modern digital times, the significance of a business data analyst has grown even further. He runs the business and takes decisions on a day-to-day basis. He’ll be communicating with the IT side and the business side simultaneously. A business analyst analyzes the historical data to find out how a unit may respond to a set of variables; predictive analytics. He looks at historical data to determine the possibility of particular future outcomes.
A business data analyst has the responsibility to analyze the business, document the organizational processes, evaluate the business models, and suggest new technological changes. Furthermore, a business data analyst is also responsible for upgrading the existing process, products, services, and software, performing data analysis. Applying new technological changes also improves the functioning of the business and reduces the time taken to complete a particular task while enhancing the overall process.
Another important reason why a business data analyst is useful to organizations today is to make the digital transformation easier. They simplify the complexities of digital transformation.
Business data analysis also helps managers make strategic decisions, achieve major goals, and solve complex problems by collecting, interpreting, and reporting the most useful information relevant to managers’ needs. Through data analysis, business operators can get a logical view of what they are doing efficiently and inefficiently within their organizations.
Some of the tools used tremendously in business analytics are Excel, Tableau, SQL, Python. The most commonly used techniques are – Statistical Methods, Forecasting, Predictive Modeling, and storytelling.
There are four main types of analytics which are descriptive, diagnostic, predictive, and prescriptive. The four types of analytics are usually applied in stages and no one type of analytics is said to be better than the other. They are interrelated and each of these offers a unique insight.
Descriptive Analytics: Representing or summarising the existing data using existing business intelligence tools to better understand what is going on or what has happened. The main purpose of descriptive analytics is to find out the reasons behind precious success or failure in the past.
Diagnostic Analytics: Focus on past performance to find out what happened and why.
Predictive Analytics: Analysing past data patterns and trends in business can perfectly inform about what could happen in the future. This helps in setting genuine goals for the business, effective planning, and restraining expectations. Predictive analytics helps predict the risk of a future outcome by using various statistical and machine learning algorithms.
Prescriptive Analytics: It is a type of predictive analytics that is used to recommend one or more courses of action on examining the data. Prescriptive analysis suggests possible acts depending on the results of descriptive and predictive analytics of a given dataset.
Business analytics gives businesses an excellent review of how companies can become more efficient, and these outlines will enable such businesses to optimize their processes. It also allows organizations to automate their entire decision-making process, so as to provide real-time responses when needed.
It helps in understanding the available primary and secondary data more extensively, which enhances the operational efficiency of several departments in the organization.
It makes the decision-making process more perfect as it helps in understanding the opinions of the customers towards the company, its brand, and products. With productivity in decision making, the organization can stay ahead of its competitors. Business analytics can also help to enhance the profitability of the business, increase market share, and bring better returns to a shareholder. There is no denying that business analytics have come to modify the dynamics of businesses and how they operate. Its importance cannot be overrated and with more and more companies relying on it for their decision-making process.