Business Intelligence vs. Business Analytics — What’s Hot and What’s Not?
Today’s business problem solutions have business intelligence and Business Analytics. They both have become an integral part of how are answered. Both involve data gathering, modeling, and insight gathering and are used interchangeably. However, they are quite different from each other, particularly the scope of the problem each address.
The Business Analytics and business intelligence has revolutionized the computer and software field to an extent that this has created a rift and a question in today's world on what to do and what not.
Let's talk about a degree in these, A degree gives one the entry path or recognition, and when it comes from the best institutions or universities of the world, it gives you an extra edge over others. A degree or course also is a scientific and systematic approach to give one the best learning experience which he or she can use in career development and knowledge transfer.
Organizations across the globe gather tremendous amounts of data and the ways they manage this data and analyze it can define their success. Mastering their own raw data means understanding the differences between business analytics (BA) and business intelligence (BI), and how they interact and their best practices.
Business Intelligence (BI)?
BI is a software collection used to support the decision-making process by analysts and managers. It can be defined as analyzing and processing a large amount of data and then converting it into knowledge-based information to support some profitable business decisions. BI environment comprises business models, data models, and ETL tools to organize and transform the data into useful information.
Importance of Business Intelligence?
Descriptive analytics takes data and provides management, stakeholders, and other users with insights into historical performance. Reports with descriptive analytics are run often to answer questions about the lackluster performance or to explain success. The term business intelligence comes to life in the form of every dashboard, custom data report, and data query process that runs over company databases. BI becomes a necessary part of an organization when they want to better understand what they have done right to this point. This is where business intelligence and business analytics differ
Terms used in (BI)
Big Data — A collection of large and complex data sets that contains structured and unstructured data that may be difficult to process and analyze using traditional database management tools.
Data Warehouse — a subject-oriented and integrated system for reporting and analyzing the data to support a decision-making process.
Data Mining — a process of applying some statistical techniques on a large amount of raw data and turns it into useful information with new patterns and relationships among large relational databases.
Business Analytics (BA)?
BA is a catch-all expression for approaches and technologies you can use to access and explore your company’s data, with a view to drawing out vital insights to improve business planning and boost performance. Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and make educated guesses about how things will pan out in the future.
Importance of Business analytics
Both BI and business analytics rely on the same data points in order to function correctly. The insights you are looking for are what tend to differentiate the two. Descriptive analytics lies beneath the surface of BI, but predictive analytics powers BA.
BA puts a higher focus on trying to generate actionable insights for decision-makers. Instead of just summarizing historical data points as the BI process is doing, BA also tries to predict trends.
The tools being used in BI are mainly simple descriptive statistics — e.g., moving average of e-commerce conversion rate — where BA can take advantage of machine learning and other sophisticated statistical models.
Descriptive or Predictive Analytics?
One way to look at this is that BI tells you what happened or is happening right now in your business — it describes the situation to you. Not only that, but a good BI platform also describes this to you in real-time in as much granular, forensic detail you need. So, BI deals with historical data leading right up to the present, and what you do with that information is up to you. Your expertise and judgment are crucial.
BA primarily tries to predict what will happen in the future. It combines advanced statistical analysis and predictive modeling to give you an idea of what to expect so that you can anticipate developments or make changes now to improve outcomes.
Both approaches are valuable, just in different ways. It’s important to know whether you are more in need of descriptive analysis, predictive analysis, or both before you invest in a platform.
Business analytics takes BI and attempts to provide insight into potential future successes and failures. The predictive analytics is supposed to highlight correlations between different customer segments and guide future business planning. Organizations planning their future turn to predictive analytics rather than descriptive analytics.
The predictive atmosphere with business analytics shows itself in the tools used. Data mining, statistical analysis, and predictive modeling are heavily relied upon in business analytics, and this means having a strong data science team.
Business Intelligence — part of Business Analytics?
Confused yet? Some experts see BA as the whole package: data warehousing, information management, predictive data analytics, reporting, etc. with BI just being one strand of that.
Under this model, BI is still the “descriptive” part of data analysis, but BA means BI, plus the predictive element, plus all the extra bits and pieces that make up the way you handle, interpret and visualize data.
The BI/BA debate
Case closed, right?
Unfortunately, not: there’s no real consensus on exactly what constitutes BI and BA, or where the lines are drawn.
Select the right technology on the data to answer your business questions.
If it’s all just semantics, why does this matter? Well, for one reason: at some point, you need to figure out which technologies, tools, and approaches you should invest in to get the insights you need.
We could argue over which definition of BA and BI are most accurate forever, but the real problem here is that different people use them to mean wildly different things.
That means it’s not terribly helpful to frame your purchasing decision as business analytics vs business intelligence. It’s more important to find out what’s really going on under the hood than to get hung up on whether a vendor bills their product as BA or BI.
Focus on what you need the system to do, and who will use it. How detailed do you need your insights to be? How tech-savvy are the people that need to run queries the most? How much control and visibility do you need over the process and the source data itself? Are you more interested in understanding how you got here or getting an idea of where you’ll go next?
Ultimately, these questions will help you establish the level of self-service you need, and whether your data requirements are geared more towards descriptive or predictive analytics, leading your business in the right direction — regardless of what you call it.