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Business Analytics

Business Intelligence vs Business Analytics: Simplified

Admin | July 14, 2022

Key takeaways:

  • Business intelligence and business analytics help companies to analyse data and make more informed decisions
  • Business intelligence provides a wide range of tools and methodologies to aid in making reliable and precise judgments
  • Although BI systems are growing more complex and powerful, data professionals are still necessary for predictive business analytics
  • Starting with a business intelligence programme and then merging business analytics to develop estimates aimed at improving productivity, revenue generation, and so on is typically the ideal option

Today businesses are generating an enormous quantity of data. You need strategies and resources to transform the data into insights to make effective decisions, detect problems, and be profitable. Business intelligence (BI) and its subsets, business analytics, and data analytics are data management tools used to comprehend and generate insights from historical and current data. 

Professionals frequently use the concepts of business intelligence and business analytics identically. However, business professionals often disagree over whether business intelligence is a subset of business analytics or vice versa.

In this article, we’ll look at BI and BA differences. Acknowledging the contrasts between business intelligence and business analytics can assist executives in selecting the right technologies and expertise to help their company’s management. Present and prospective business students may use this information to choose which school programmes will begin preparing them for a lucrative career in their professional life.

What is business intelligence?

Business intelligence is a framework that helps collect and analyse data from systems and processes. BI gives complete company analytics in relatively close to resources in strategic planning. With ample business information, you may set quality standards, identify market trends, raise accountability, and improve every aspect of your organisation. 

A range of development tools and other technologies can be used as business intelligence tools. Spreadsheets, online analytical processing, reporting programmes, corporate performance monitoring software, and data gathering software are a few examples. Some experts think business intelligence tools should incorporate more analytical and scientific techniques in business analytics.

BI systems are comprised of four major components:

  • A data warehouse that consolidates and makes available firm information gathered from many sources.
  • Business analytics or data management technologies to harvest and analyse data.
  • Business performance management (BPM) technologies to track and assess progress toward organisational objectives.
  • A graphical user interface to enable easy access to information.

What is business analytics?

Business analytics is a statistically driven area where data specialists employ quantitative tools to create forecasts and design future growth strategies. Business intelligence may inform business executives what their existing customers look like, whereas business analytics may tell them what their prospective consumers are doing. Some experts define business analytics as a set of prediction techniques utilised in business intelligence.

Many functions are performed using business analytics tools, such as correlational analysis, regression analysis, factor analysis, forecasting analysis, text mining, image analytics, and others. Many of these technologies need the hiring or contracting of data scientists, which has boosted the demand for business analytics training.

Read more: What is Business Analytics?

What are the distinctions between business intelligence and business analytics? 

With awareness and expertise in the business intelligence and analysis field, there is a noticeable increase in misconceptions about the true distinction between Business Analysis and Business Analytics. The following are the distinctions between Business Intelligence and Business Analytics:

Business intelligenceBusiness analytics
It uses historical and present data.It uses historical data to extract insights and conduct company operations 
It  focuses mostly on reporting the studied data and gaining insights from it.It focuses on tools that conduct various operational applications utilising various tools.
It is a method of evaluating existing data. It uses Business Intelligence reports as inputs to process the extracted information more complexly to display the examined data.
It employs statistical analysis, predictive analysis, and predictive modelling to establish trends and determine the causes of current outcomes or occurrences. It lacks control over vast amounts of data to retrieve, analyse, report, and publish.
It relies mostly on User Interface Dashboards to conduct analysis and operations. It uses quantitative analysis.
It provides insights or information about the data rather than making additional transformations or conversions to provide data insights.It involves a method of problem-solving by enabling technologies to transform the raw form of data into a meaningful way to convey the solution efficiently.
It is used more to structure data from corporate programs such as Financial Software Systems or Enterprise Resource Planning (ERP) to get insight from prior financial information or past financial transactions and in supply chain and operations. It is applied to unstructured and semi-structured data by converting it into useful data before analysing it to get insights.
It  consumes data in the same format to gain insightsIt changes or splits current data into multiple forms or pieces and studies them to gain insights.
It looks at the past data.It looks at future data.
It accesses large amounts of data.It approaches managing large amounts of data.
It is used to manage firms It is a method of altering a business
It is strategic in nature.It is tactical in nature.
The process is descriptive and static.The process is exploratory.

BI and BA applications in the real world

Let’s highlight these distinctions using real-world BI and BA applications in the real world. In this case, you market unique products via an internet store. Business intelligence delivers useful reports about your company’s past and current status. BI informs you that sales of your particular product have increased significantly in the region over the last few weeks. Consequently, you decide to produce the most sold product to meet demand.

A business analyst would examine how visitors use your website, discover traffic trends, assess visitor profiles, and maybe even develop a system for tracking how consumers navigate different sites. A business analyst would be more concerned with the actual implications of this data and how it may assist you in making decisions about purchasing advertisements, developing new goods, and upgrading your website.

Read more: How to become a business analyst?

Future of business intelligence and business analytics

Business intelligence and business analytics are quickly becoming a need for modern businesses. The top priorities for business intelligence software developments in the coming year are collaboration, automation, and data-driven business.

Business intelligence collaboration

  • Many experts believe that one important business intelligence future trend will be expanding the digital business intelligence world into a place where tools and platforms will become more broad-spectrum and, eventually, more collaborative.
  • Many of today’s tools are isolated and operated separately by individuals, unattached to a larger network. There is an agreement, however, that the next generation of business intelligence will be directed toward larger groups of users and increasingly integrated into larger systems.
  • This sort of movement is currently seen as certain BI platforms evolve toward more advanced collaboration and machine learning systems.

System integration is expanding

  • Business intelligence tools are projected to become more integrated into existing procedures. Many manufacturers are already striving toward more integration, with application programming interfaces (API) allowing customers to analyse data within their existing systems. 
  • Integration capabilities in BI software are projected to grow from the inside out, giving third-party capability from within a business intelligence tool while also incorporating BI features in other applications.
  • A data analyst may see that the marketing expenditure for a certain advertising firm is excessively costly to attract a new consumer, and you may want to reduce your budget for that marketing company, or you may want to discontinue the ad entirely. 
  • Third-party system functions will be integrated into your business intelligence tool, providing a full-service platform. You can make data-driven decisions without ever leaving your business intelligence.
  • Business intelligence software users will be able to obtain data analysis without launching their business intelligence application. The system may send out notifications and emails as data changes.  
  • Native language processing will enable immediate responses to BI queries from consumers. Another important development likely to take off in the business intelligence software sector in the future is machine learning.

Insight and self-service will be driven by machine learning.

  • In the approaching years, BI software is projected to become more intuitive. These systems’ prediction skills are expected to evolve into identifying characteristics that give information depending on the context of the proposition. 
  • A business intelligence tool will be able to make a decision differently based on the criteria mentioned in the query and personalise the answer to the user’s needs.
  • These predictive capabilities will help to simplify decision-making while also accounting for compliance. Artificial intelligence may generate intelligent estimates about your data inquiries by analysing trends and prior patterns.

Data promotion

  • You eventually reach a point where human users are no longer required to kickstart business intelligence activities. Instead, you’re more likely to passively get this knowledge than actively seek it out in a report or dashboard. 
  • The information provided to you is data promotion. This might be as basic as making crucial data points stand out in a graphic or as complex as alerts offering direct replies.
  • Companies have been widely touting creativity in their visual panel designs up to this point. More complex graphing and plotting have become essential, and data visualisation has become the buzzword.
  • Third-party program integrations and artificial intelligence are strongly tied to the idea of data proactivity. Clearly, all of these functionalities provide the benefit of offering replies based on your company’s recorded data. 
  • Whether you use the system directly or indirectly, a straightforward tool will provide you with the answers.
  • Data proactivity capabilities will eventually extend outside BI systems. Similar alerts will be provided in third-party apps, eliminating the need to request data or directly ask for an inquiry.

Network developments

  • Emerging networking architectures are evolving to handle these vast troves of data as they move into and out of corporate systems as software technologies do more with BI data. 
  • The cloud has taken over broad swaths of the corporate sector, with third-party organisations offering services to individual clients to assist them in managing business information and analytical data. 
  • However, there are innovations such as network virtualisation beyond that vendor barrier. Engineers are working on new ways to install hardware designs and automatically grow with data volume.
  • A solid network design is required for any program to serve as the system’s skeleton. Business intelligence solutions are no exception since strong data storage is required in addition to standard infrastructure requirements. 
  • This serves as the foundation of your business intelligence solution and can serve as a differentiator in how your firm uses the system.
  • By providing this structure, business intelligence architecture guarantees that the development efforts of numerous projects fit neatly together as a coherent whole to accomplish the intended BI system. In summary, network improvements will aid in the development of the tool you desire.

ALSO READ: Scope of M.Sc. in Business Analytics

Online Manipal can help you upskill

The Master of Science degree in Business Analytics offered by Online Manipal from the well-known Manipal Academy of Higher Education (MAHE) is intended for individuals who want to make a difference in the emerging subject of business analytics. Business analytics has become critical for company development and survival to achieve a competitive advantage. Companies are increasingly relying on business analytics tools and approaches to make quicker and better decisions and solve problems. This multidisciplinary master’s programme integrates business domain and analytics skills, preparing students to flourish in Business Analyst careers across industries.

Online Manipal also offers one-year Postgraduate Certificate in Business Analytics from MAHE. This 100% online programme will help you fast-track your career in short span of time. Check out more details here.

Bottom line

A company’s success requires both business intelligence and business analytics descriptive and predictive analytics. Additionally, individuals in the business world frequently use both phrases alternately, deciding on the type of technology, tools, and talent to engage in. 

You must focus less on BI vs BA rather than on what you need the database server to perform and who will be utilising it. Business intelligence’s future is anticipated to be considerably more automatic and intensively used, with fewer interface constraints and data flow obstacles. Future BI innovations are all part of a rapidly changing paradigm that is critical to the advancement of modern enterprises.

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