Businesses need continued monitoring and evaluation of operations and policies to stay competent. Business intelligence and business analytics are processes that identify trends in past and current business data and predict future outcomes as well.
A large volume of data is generated by businesses and this data can be used to examine different facets of an organization. It is important to understand current and past performance in sufficient depth so that strategies and processes can be tweaked or revamped to optimize operations and maximize profits. Predictions of future performance that are extrapolated from existing data are also important for the same. Business analytics services and plenty of software tools are available, which can help in business data reporting and analysis so that actionable inferences can be made from the overwhelming amount of data.
We, at NB Business Consulting Group, can analyze various aspects of your organization such as structure, accounting, and logistical practices, IT systems, and others, and devise actionable solutions to help maintain your competitive edge.
What is the Difference Between Business Intelligence and Business Analytics?
Business intelligence and business analytics are data management solutions that analyze historical and contemporary data, glean insights into trends, and recognize patterns that may need to be altered.
Business intelligence involves collecting and analyzing past and current data that is generated by business operations. It will identify trends and provide a comprehensive “big picture” about the strengths and weaknesses of your business. The results of business intelligence gathering will help you see where your business goals are met and where you may need to alter strategy or make processes more efficient. It is descriptive in nature. It is broad in scope, summarizes what has happened and what is currently going on, and helps with business strategy at a high level.
Business analytics is a subset of business intelligence. It uses data mining and modeling tools and methodologies to predict future outcomes from current data. It is predictive and in-depth. While business intelligence tells you what has happened, business analytics tells you how and why those trends occurred. Analytics will give you an insight into positive patterns in your business operations that have increased your productivity, efficiency, or revenue. This will help you decide which practices to retain and replicate. It will show you negative trends, if any, which expose practices that could be draining your resources. As a result, you can alter these procedures to make your operations more efficient.
At NB Business Consulting Group, we have an extensive list of services to delve into your business data, make fact-based inferences, and recognize trends that can help you make informed decisions about your business models.
Which Are The Four Types of Business Analytics?
Descriptive analytics: This is the most basic form of business analytics and is usually the logical first step in the process of big data analysis. To make sense of the sheer overwhelming amount of data, statistical tools are used to mine the data and summarize it to make it easy to assimilate and understand. It converts raw data into a form on which further in-depth and specific analysis can be applied. Descriptive statistics and analysis also make it easier to interpret and communicate business performance to management, company stakeholders, and teams who are not involved in the core financial aspects of the business. The results of descriptive analysis are comprised of reports and dashboards.
Diagnostic analytics: This type of analysis goes a step further from descriptive analysis by building upon it. It explores the specific underlying reasons for the statistical results of the descriptive phase. It pinpoints key trends in the results and identifies correlations and causal relationships between factors that have led to those trends. This is also a phase that analyses existing data, but unlike descriptive analysis, it involves making inferences.
Predictive analytics: It extrapolates from existing data to predict the probability of future trends. Since it involves projections, it is carried out through machine learning algorithms and statistical modeling of future trends. Sales forecasts and predictions that take into account more subjective measurements like popular opinion are examples of predictive business analytics.
Prescriptive analytics: Once predictions of future trends have been made, actionable solutions need to be formulated to counter any potentially unfavorable outcomes that have been foreseen. This is where prescriptive analytics come in by mainly using optimization techniques. It provides multiple paths to a favorable outcome or all possible outcomes of an existing business practice. This is as far as the process of business analytics can go. It provides actionable suggestions to business managers based on the extensive analysis performed in the preceding three phases.