Finding the right business intelligence software can be cumbersome. Many people looking for business intelligence tools are not fully aware of how these business intelligence solutions can help their organizations optimize their processes. This guide explores what business intelligence software is and how organizations can implement BI solutions to improve their profitability and scalability.
Business Intelligence Solutions - what they actually are?
Business intelligence software can be described as a set of tools utilized by organizations to access, analyse, and convert data into valuable business insights. Business intelligence tools usually transform data into easy-to-read visualization like charts, graphs, and dashboards. Previously, organizations would often rely on competitive intelligence. However, depending on external data sources was not as fruitful as business intelligence software. A BI solution or business intelligence system utilizes internal data that the business is producing through an analytical workflow that gives the company an overview of how the company's processes interlink/differentiate or affect each other.
Business intelligence software has become more prominent with the rise and incorporation of big data in the industry. Big data refers to when businesses accumulate, save, and mine business data. The rising popularity has made the business intelligence software industry more competitive than ever. Every day new tools are being introduced. Organizations are creating, tracking, and assembling business data on a large scale. This need for integrating cloud software with the proprietary system is further fuelling the drive to connect various disparate data sources. However, this data does not mean anything to companies if they cannot make sense of it or utilize it.
Informed decision-making is vital for all businesses. Without proper evidence or support for their strategic decisions, companies can land in big trouble. The data in question in this article can help enterprises to align decision-making with proper market evidence such as purchasing patterns and new customer trends. Organizations can gather, systematize, and analyse the data to understand customer needs, anticipate demand and supply changes, and thus prepare for any unforeseen events and maximize revenue growth.
Previously, business intelligence would take the form of quarterly/yearly reports that would discuss a set of defined KPIs. That is not the case in today's tech-obsessed world. Businesses are often backed up by business intelligence tools that are constantly gathering 'meaningful' data for an organization. Such insights help a firm decision on a course of action quickly.
Business intelligence platforms interpret a plethora of quantifiable business actions based on customer data. Such solutions also return queries based on the incoming data. Today, business intelligence systems can take many forms and types.
In this guide we will discuss the following aspects of business intelligence software:
- Business Intelligence tools for data storage
- Big data and BI solutions
- Business intelligence system for corporate reporting
Business Intelligence tools for data storage
All organizations have multiple systems in which data is processed and saved. All organizations must standardize formatting across all data sources and types to ensure that they can achieve the most accurate data analysis. For example, you might have seen that large organizations often have both a CRM and an ERP system in place which means that their customer information is saved differently. Their financial data is saved in another place. These separate systems may categorize data differently, and the corporation will need to standardize the data before analyzing it for insights.
Most business intelligence solutions pull data directly from the source applications through a webhook or a native API connection. However, some business intelligence software relies on a cloud data storage platform to collect different data sets in a shared location. For small and medium businesses or individual users, even for single departments, a native connection is sufficient. However, large organizations or even companies that produce large data sets require a more comprehensive BI solution.
Big data and BI solutions
Organizations can choose to store their data in different places, such as a data warehouse, an on-premises server, or a source system on which it runs queries or even a cloud database. What makes the field interesting of data analysis for users is the resulting insights. All analytics platforms vary, especially in terms of complexity - however, they all follow the same procedure of merging extensive, controlled data to discover patterns.
Data mining is also known as data discovery and entails automated/semi-automated data analysis. This analysis helps discover patterns and anomalies. Some of the standard connections derived from data mining involve categorizing certain sets of data, obtaining outliers in data, and getting links or dependencies from disparate data sets. Data mining helps isolate patterns used in more complex analyses, such as the predictive modeling approach. This makes it an integral part of modern-day business intelligence software and BI solutions as it helps organizations work with big data.
Predictive analytics involves comprehensive modeling and can even be linked to AI and ML techniques that allow the software to learn from earlier experiences and predict future results. The three main types of predictive analysis are descriptive modeling, predictive modeling, and decision analytics.
Natural language processing
Natural language processing (NLP) software examines large sets of unstructured data to discover concealed models. NLP has a significant impact in terms of social media - it allows businesses to track keywords/phrases to find patterns in how customers use them. NLP tools also gauge customer sentiment, deliver actionable insights, and learn market trends.
Business intelligence system for corporate reporting
The business intelligence software applications discussed above deal with the inner workings of a business intelligence system - however, business intelligence reporting focuses on presenting the findings of such business intelligence software applications.
Online analytical processing (OLAP)
OLAP uses multidimensional databases that enable users to query data warehouses and create reports that access data from various angles. OLAP allows business intelligence software to merge data, drill down into specific metrics, and view data for groupings of single metrics inaccessible in a conventional spreadsheet format.
Data visualization permits businesses to visually display data mining or other analytics results via graphs or charts. By visualizing the findings in such a format - organizations can gain quick and accessible insights into the most crucial metrics. Such quick and easy recognition of insights is not possible via spreadsheets.
BI dashboards are being incorporated all over the world. However, not all business users need full access to everything in a dashboard. Sales teams may only need access to the sales dashboard, while the marketing team might only need access to marketing data in the dashboard. Dashboards give quick and easy predefined visuals that allow organizations to focus on their customized needs. Some BI solutions have collaborative dashboards in which business users can control data visualizations, obtain a more detailed view, and benefit from interactive features for more context.
Conclusion: Choosing the right business intelligence software?
By comparing the tools and solutions mentioned above, organizations can find a business intelligence software that meets their exact needs. Organizations can also benefit from custom BI solutions provided by BI experts and create a solution that relieves their pain points and helps them uncover their untapped potential.