Business Intelligence is an essential part of a data-driven business approach. The data that is gathered over some time for a business works as an asset as it helps to create meaningful insights.
Business intelligence can be performed by a range of BI tools that are available in the market. BI software can be purchased to set up the data reporting and other features that form the basis of business intelligence.
In this article, we would observe in detail what business intelligence is and what are the key features that are considered necessary for business data analytics using these BI tools and techniques.
What is BI?
Business Intelligence means aggregating, arranging, and analyzing data from data sources across the organization, and performing data analytics to generate in-depth insights to let management make informed decisions for their business.
A survey conducted in 2013 by the IBM’s Institute of Business Value and the University of Oxford showed that 71% of the financial service firms had already adopted analytics and big data.
Raw Data is now recognized as the foundation of any business environment. Instead of letting this data uselessly put in files and records, the business must work with the data and make use of it to identify the different patterns that are making trends in the market.
Data are becoming the new raw material of business. – By Craig Mundie, Senior Advisor to the CEO at Microsoft
Data analysts use Business intelligence tools and techniques to study and analyze big data from businesses that are aggregated from different data warehouses. They reach conclusions about the performance of their products in the market using data visualizations. They can also identify common areas of mistakes that can become clear through data analytics and reporting techniques applied to the raw data.
15 real-world Examples of Business Intelligence tools and techniques
Many Business intelligence tools are marketed every day and each of them come with their own unique set of features and tools to help business analysts perform data analysis. These data analysis techniques and features help enterprise-level organizations make crucial decisions by monitoring key metrics in real-time data.
The use of these business intelligence tools has made the job of data analysts more powerful by providing them with new cutting-edge technology to perform data analytics and reporting easily.
Here, we have enumerated some key tools and techniques that let business intelligence software an ultimate solution for any enterprise business.
“BI is about providing the right data at the right time to the right people so that they can take the right decisions” – Nic Smith with Microsoft BI Solutions Marketing
Data visualizations
One of the main features that must be a part of business intelligence software is the ability to work with raw data and create meaningful data visualizations. The visual effect helps data analysts to look for the disparity and gaps in different areas of business processing.
Creative reports
This feature of business intelligence software offers a varied range of report layouts to choose from when designing visualizations for accessing data from multiple data warehouses and presenting them collectively.
Reports can be created and changed ad hoc and refreshed to populate with freshly synced data.
Data dashboards
Data dashboards are helpful when monitoring real-time data and comparing results set from multiple reports. End-users can monitor time-critical data on the data dashboard to access up-to-date information and avoid loss in business by making quick decisions. Data dashboards can be created spontaneously and designed uniquely by users to fulfill their individual needs.
Cloud Computing
Cloud computing takes business intelligence BI Tools to another level as their software can be housed at a remote location and can be accessed from anywhere in the world. This flexibility would give the business a unique chance to expand its work and profitability without compromising its services.
Customizable report layouts
Every business is looking for personalized information management systems and reposting tools. Customizable report layouts are a solution that these businesses are happy with because this would help their end-users design complex reports from their desktop with minimal staff training.
Ad hoc Querying
The Ad hoc querying feature makes it easier to find market trends for the business and helps to make informed decisions to increase productivity. Ad hoc reporting software like dotnet report builder lets users create ad hoc queries for intuitive data analytics.
Predictive analysis
Business intelligence software has the feature to perform predictive analysis using the big data in a business. This feature lets the data team study raw data from the previous years for the enterprise business and then make predictions about different key metrics in the future.
Predictive analysis and strategic business processes can help management to make informed decisions to get the required outcomes from this analysis.
What – if Analysis
What-if analysis is very popular in business intelligence tools and it aims to answer specific questions targeted at the data set. Data analysts perform an in-depth study of business data to gather these insights which in turn try to answer the what-if questions.
These questions are usually put forward by leaders in a business when they are planning to analyze their business strategies to expand their work.
Ranking reports
Ranking reports are used to compare and contrast all the products and services provided by a specific business. In ranking reports, an analysis is performed and a rank is assigned to each product.
Once all products are ranked, analysts try to improve the low-ranking products to perform better in the market.
Machine Learning techniques
Machine learning holds an important place in business intelligence as it is very useful to train a machine for repetitive tasks than working on any other model. If processes are programmed with clear, concise instructions then it would work to improve business intelligence processes in the software.
Customer relation management
Customers and clients are the most important aspect of businesses in terms of revenue and profitability and in terms of collecting data and performing analytics.
Customer feedback and information play a vital role in business intelligence as these tools can record and work with customer data to provide valuable insights that can improve the quality of products and services in a business. The latest CRM Softwares are available to take care of customer data for enterprise businesses.
Natural language processing
Business intelligence also employs AI techniques like Natural language processing to collect and build on user data that can be beneficial for business growth.
Detail analysis of unstructured data using natural language processing tools would greatly benefit business intelligence. Sorting similar queries from customers and responding in a unique way to each request would help bond customers to the business and establish trust.
Collaboration tool
Business intelligence software needs to have a facility to allow collaboration between employees in a work environment. Teamwork is everything and providing ease to perform data analysis and reporting tasks collaboratively can go a long way in making the business successful, keeping everyone informed and on the same page.
Data mining
Data mining is an emerging technique in business intelligence that is useful in identifying correlations between data entities coming from multiple sources.
Data in a business may reside at different data warehouses and there might be a need to aggregate and assemble this data for performing data analytics. Data mining helps to sort and identify data patterns.
Data Querying
Data querying is another specialized tool that is making its way in business intelligence software as it serves to answer specific queries from a data set. It usually groups data based on specific criteria or different filters are applied to the data set to answer questions that help management to reach conclusions regarding their products and services.
Case Studies that have used Business Intelligence
Amazon
Amazon is an eCommerce website that handles millions and trillions of product profiling, inventory, and transactions every day. It needs some robust business intelligence tools in place to handle the inventories in the warehouses as well as daily sales, purchases, and deliveries all across the globe.
The different BI tools and techniques not only help with product profiling and efficient searching but also run the overall sales procedure smoothly. Separate business intelligence softwares eases different parts of the whole process.
Starbucks
Starbucks is a famous beverage chain that has used Business intelligence software tools to promote its products. They gather customer information and their likes and dislikes in terms of their favorite drinks and other ordering habits through customer relationship management (CRM) tools. This data is then aggregated into the business intelligence tool to make visualizations that help the company to design special offers for their customers.
Google is a great example of business intelligence. Google works around data and uses different algorithms that sort the bulk of data to implement the data-driven approach. It uses business intelligence tools and techniques to understand and act on data for handling user requests.
Twitter uses business intelligence with AI to identify and eliminate inappropriate content on its platform. AI Algorithms are used to identify almost 95% of terrorism-related Twitter accounts and then they are suspended. Business intelligence also improves the overall user experience for Twitter.
Twitter uses business intelligence to understand user interest and sorts their video feeds according to the user’s choice. The business intelligence tools help Twitter to get users hooked to its content thereby increasing its popularity.
Facebook is a social media website that relies heavily on business intelligence software to assemble and manage its user data. This data helps give users suggestions and feeds according to their interests and lets them experience a personalized environment.
