Business Intelligence (BI) is a technological process where data is analysed and transformed into actionable insights, which help executives in business make informed decisions. This process involves collecting, storing and analysing data produced by a company. Business intelligence helps find incompetent business processes, discover new projects, identify innovative business ideas, and make data-based business decisions. BI is an umbrella term that includes data mining, data visualisation, dashboarding, performance benchmarking, descriptive analytics, and reporting. These techniques involved in BI allow businesses to present their data in a manner that is accessible and understandable whilst still informative and professional. Furthermore, an overarching use of BI software and procedures are key factors in business success.
Table of Contents
Introduction
The Importance of Business Intelligence
- Data-Driven Decision Making
- Real-Time Data Monitoring
- Improved Efficacy
- Access Control
- Marketing and Competitive Analytics
- Benefits and Disadvantages
The Components of Business Intelligence
- Data Sourcing
- Data Preparation
- Data Warehousing
- Online Analytical Processing
- Extracting, Transforming, Loading
- Data Mining
- Data Visualisation & Dashboard
- Corporate Performance Management
- Reporting
Conclusion
Why is Business Intelligence Important?
Now that you know what Business Intelligence is (as explained above) let’s get into some of the reasons behind its value in today’s society. For example, it’s collective ability to incorporate and improve data-driven decision-making, real-time data monitoring, efficacy, access control, and marketing or competitive analytics. There are multiple benefits to including BI in your typical business operations, which generally far outweigh the disadvantages. However, it’s important to be aware of these disadvantages, so you know how to work around them.
Data-Driven Decision Making
Data-driven decision-making is the collection and transformation of data into actionable insights. Typically, data-driven decisions will be made on the basis of a business’s key performance indicators (KPIs). This is a strategy many companies rely on to further their growth and stay ahead of the competition by promoting profits, optimising operations and improving overall performance. Thus, it is no surprise that the predominant purpose of BI is to provide actionable insights from data either through pre-set reporting methodologies or queries.
Further, a good BI tool will identify and highlight trends, allowing decisions to be made without emotional input or potential subconscious bias. Objective decision-making techniques promote fairness and an overarching balance in a company’s operations.
To make data-driven decisions, it is crucial that you understand your company’s goals so that you know which data is relevant during the data collection process. Once data is collected and organised, it is ready for an analysis that will draw conclusions and indicate how to progress. A typical example of data-driven decision-making includes tracking customer data to observe which products sell best with which demographic and using this knowledge to increase profits.
Real-Time Data Monitoring
Real-time data monitoring occurs when data is collected and stored in real-time, such as polling or streaming. It is a standard mechanism to ensure networks, services, and applications perform to the required standard. Typically, administrators will be notified immediately when there is an issue with data points or the system’s functionality.
Be it sales, production, or distribution, real-time monitoring helps identify a trend early. Business dashboards created with BI show live statistics and key metrics, even as the data grows. Using BI to monitor data in real time is a fantastic means to protect a business’s digital assets.
Improve Efficiency:
BI, when employed, provides greater visibility and insights and identifies the areas to be improved. This helps reduce errors and also saves resources in the long run. It also enhances the organisation’s efficiency by using data sourcing, mining, and reporting tools. BI offers swift insights into team performance, customer behaviour, trends, productivity, and so on. Being weaponised with this knowledge contemporaneously allows businesses to act on these insights without additional risks of error. Sometimes, these insights can mean the difference between customer satisfaction and dissatisfaction, so the reduced margin of error is an essential factor to consider in relation to BI.
Access Control
Access control is a technique involved in the security of data. It dictates the user access permissions for specific aspects of a business. Business Intelligence tools provide advanced user access control, clearly defining who has access to what. In today’s data-rich world, data security is of the utmost importance, so access control is a necessity regarding who can reach what data. When implementing this technique, consider the roles of each user and how that dictates what they should have access to.
Market and Competitive Analysis
Market analysis is the provision of investigated information regarding industries, customers and competitors. Its purpose is to determine how suitable a product or offer is to a specific market. Competitive Analysis is similar, however, more tailored towards similar businesses or ‘competitors’ in the industry, hence the name. It is a crucial tool in knowing your competition so that you can stay ahead of them or, at the very least, remain on the same page. BI also has the potential to provide insights into this data from the market & competitors, which in turn aids organisations in making educated decisions and planning for their future endeavours.
Overall Benefits and Disadvantages
As discussed above, there are multiple advantages of incorporating BI into your business. These all contribute towards overall data visibility, the accuracy of insights/reports and streamlining the overarching process of business operations. However, if you want to stay ahead of the competition, it’s important to consider the disadvantages of BI and how you should mitigate any risks associated with them.
Cost
In the initial stages of BI, it can be expensive. For businesses just starting out, this can be problematic. It would be worthwhile to invest in smaller BI tools, such as Fourth Dimension or similar devices, which provide extensive ranges of functions for affordable prices.
Knowledge
Stemming from this point, some users may be reluctant to engage in BI due to a lack of technical knowledge or understanding of functions. This issue can be simply combatted for larger enterprises by employing professionals to do the work for you. However, smaller companies should be prepared to teach users about the functions of BI. To help your learning, check out our other blogs on business intelligence!
Security
Perhaps the most prominent issue concerning BI is the security risks, considering the online nature of today’s world. As mentioned above, implementing an access-control scheme would be worthwhile so that if a leak occurs, you can track how the data was exposed. However, the main idea of data security is to stop data from leaking rather than damage control. This could be done by incorporating the appropriate security measures, educating employees on maintaining data security and conducting regular updates to the security system. Hence, it constantly reflects the utmost protection.
Data Quality
Finally, some may suggest that implementing BI tools creates issues with data quality. However, using a system not flawed by human error is arguably more effective than a system dictated by humans and may cause significant inconsistencies. BI tools have the capacity to collect quality data in an expeditious manner, which is far more efficient than the alternative.
What are the Components of Business Intelligence?
To understand how the benefits mentioned above are caused by implementing business intelligence tools, it may be helpful to understand how BI actually works. BI comprises various components to collect, present and analyse data to determine the correct decision. These components include data sourcing, data preparation, data warehousing, online analytical processing, ETL (extract, transform, load), data mining, data visualisation and dashboarding, corporate performance management and reporting.
Data Sourcing
Data sourcing is collecting and compiling data from various sources into one common database. For an effective BI or analysis, it is essential to find the correct data. The process objective is identified based on the data sourced. Data sourcing is simple and often conducted by the businesses’ internal database, such as ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), Purchase data, Internal transactions, etc. Dynamic links must be created between the tool and the data source to get real-time updates.
Data Preparation
Data Preparation is a one-time process of converting, refining and matching data from multiple sources with the structure of the database. It is essential for every Business Intelligence component to run smoothly as it prepares the data for analysis. This process ensures that data is accurate and consistent, reducing the presence of errors.
Data Warehousing
Data warehousing interlinks databases to the central database. Essentially, it is the compilation of data from multiple sources into a consistent warehouse to be more appropriate for business intelligence processes. Here, the records are organised and stored for analysis and reporting. Warehousing is a more inclusive process which overlaps with data sourcing and preparation.
OLAP (Online Analytical Processing)
This is an advanced multi-dimensional analytical process in modern BI tools to determine solutions and outcomes. It is most effective in handling multiple aspects of databases and passing multi-query arguments. OLAP provides fast online analysis, which means real-time responses and can support and optimise large business databases. OLAP databases typically contain two distinct types of data; numeric and categorical. There are several components that makeup OLAP.
Cubes are data structures that combine dimensions.
Measures are typically numeric values in a cube that control central cube values. For example, profits, sales, costs, and revenues.
Members are items of hierarchical structure which represent reoccurring data.
Calculated members are members of a dimension whose value is calculated at a run time.
Dimensions are sets of organised hierarchical levels in a cube typically used as the fundamental basis for data analytics.
Hierarchies are organisational systems in which members of a dimension are arranged so that each has only one parent member and no child members.
Levels are the different ranks within a hierarchy.
ETL
ETL is the process of Extracting, Transforming, and Loading. This process extracts data from one or many sources, transforms it into a single or standard format and loads it into a data warehouse or the system for further analysis.
Data Mining
Data mining is extracting valuable data from the available raw data using different tools and techniques. The most common are “prediction, estimation, classification, time series analysis, and market basket analysis”. This process allows for trends to be discovered from large pools of data.
Data Visualisation & Dashboard
Data visualisation is the representation of data via charts, graphs, and other visual forms to ensure accessibility and ease of understanding. It is beneficial for breaking down complex data sets into more manageable trends. The dashboard is an accumulation of visualised data, updated in real-time, to keep track of business activities. It is helpful for the stakeholders and decision-makers to understand complex and critical data and makes tracking KPIs easy.
CPM (Corporate Performance Management)
CPM, or Business Performance Management, is an analytical strategy to understand business performance and move towards a predetermined goal or maintain efficiency.
Reporting
This includes sharing outcomes of data analysis, data mining, or anything similar in an organised document or presented within the BI tool for the decision-makers, clients, and key personnel. The report is the final output from the processes within Business intelligence. Reports are usually static but can also be dynamic, thanks to BI, and typically allow decision-makers to draw conclusions that will form the basis of their decisions.
Signing Off
As you can see, BI is a unique tool when it comes to maximising business performance. With BI and the associated benefits, companies can efficiently transform data into actionable insights with informed decision-making.
‘AI and machine learning’ is starting to be incorporated into every stage of BI tools. Business intelligence is an evolving sector growing dramatically in user base, bringing in newer features as the market increases.
As of 2023, the applications of BI are endless, and soon it will be a vital tool in every business to make data-driven decisions. With affordable tools such as Fourth Dimension, small businesses & start-ups too can take advantage of BI tools.
See our other blogs in relation to data visualisation techniques, dashboarding, data analysis and data reporting for some helpful information that may aid in driving your business success!
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