What is the difference between business intelligence and business analytics?

business analytics

To progress in the modern business world, the more tech knowledge and skills you have under your belt the better whether this is a detailed knowledge of web design, web development, cybersecurity, or data analytics (DA). 

What is DA and how can it help your career?

Just about anything we do in life generates mountains of data and this is just as true in the business world. To keep their edge, businesses need to collect, analyze, and make meaningful use of this information which is why knowledge of DA is an invaluable tool along your career path. Using the information created by analytics, businesses can embrace new and existing technologies. For example, sales may be closed using social media platforms alone or Artificial Intelligence (AI) can help you avoid the tricky position of customers filling shopping carts and then abandoning them. Business intelligence (BI) and business analytics (BA) both sit within the scope of DA. They have many points of similarity (which often leads to them being confused) but there are also some definite points of difference between them.

Business Intelligence

Business Intelligence (BI) looks to the past as well as evaluating the present to make immediate improvements. Historical statistics on finances, performance, operations, media reach, conversions, and so on are collated and summarized into information that is easy for businesses to visualize. BI then uses this information to isolate the source of any issues that might be holding a business back before presenting solutions designed to remove these pain points. With knowledge of BI, you gain a better understanding and perspective on business operations whether it is your employer's business or your own. Use BI alongside reports, briefing books, and audits to make informed data-driven decisions that increase the organizational productivity of any business.

When BI such as real-time dashboards, visualizations, decision services, integration features, and online analytical processing (OLAP) is used competently and creatively, readable reports are generated that contain relevant info for businesses to act on. Dashboards and visualizations present information in easy-to-interpret ways, decision services present a more specific focus such as financial reporting while integration features pull information from multiple sources together. Online analytical processing gives a multi-dimensional analysis that is sophisticated in its concept and breadth. When all of these tools are brought together, BI creates the situation needed for successful goal provision and management. To provide BI as a solution, you'll need an in-depth knowledge of software such as Python, Git, API, and SQL. Business Intelligence is the optimal solution for businesses that are satisfied with their performance on the whole but wish to improve weak areas such as decision making, productivity, or specific work processes.

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Business Analytics

Where Business Analytics (BA) differs from BI is that it makes predictions directly based on data mining and past business trends and offers specific solutions when this reveals weak points in an organization. As with BI, it analyzes historical information but with the intention of predicting future business trends. The information BA generates is also presented in easy-to-read and understandable visualizations. BA is generally accompanied by ad-hoc reporting in real-time, allowing business managers and owners to make fast and effective business decisions. At its best, BA can solve a problem before it occurs! Software dedicated to successful BA includes Pentaho BA, SQL, and Tableau. If you intend to make major changes in your business processes or even redesign your entire business model then BA gives you the necessary insight.

Having extensive and informed knowledge of both BI and BA is a definite bonus for any successful career path in business. It opens the door to a variety of roles such as database developer (creating databases to handle raw information), database administrator (maintaining and securing these databases), data engineer (creating data sets to help in the analysis of incoming information), and data analysis manager (interpreting and communicating the data to your team so they can make informed future decisions). Along the way, you will also develop transferable skills in the world of computer science, critical thinking, machine learning, artificial intelligence, statistics, and mathematics.

Our Ironhack Data Analytics Immersive Bootcamp can be taken over nine full weeks of study or 24 weeks of part-time study. No previous IT background is necessary. You can even start studying without a degree. The course gives you the hands-on skills for success in the fast-growing tech industry. During the course, you'll create and work on your own real-world projects before moving on to presentation and visualization techniques and complete analysis of real data sets. Your training finishes with the basics of machine learning as you build, train, and evaluate models. Your final project challenges you to apply what you have learned in an innovative way. This project then forms part of your data analytics portfolio, your first step towards success.

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