Source: Thinklayer
Business intelligence (BI) is a component of data analytics
that enables organizations in accumulating, analyzing, and presenting data
to make educated decisions. BI technologies can assist organizations in
meaningfully visualizing their data, and delivering insights into their
operations, customers, and market trends.
One of the key purposes of BI is to improve decision-making
by providing stakeholders with accurate, relevant, and timely information. This
is accomplished through the use of business intelligence dashboards, which
integrate data from multiple sources and present it in an easy-to-understand
style. Users can utilize BI dashboards to quickly detect trends, patterns, and
anomalies in their data, allowing them to make data-driven decisions.
Source: Bismart
BI can be used for a multitude of purposes, including:
- Sales and marketing: Business intelligence may assist firms
in tracking sales performance, monitoring customer behaviors, and optimizing
marketing initiatives.
- Financial Analysis: Business intelligence (BI) can assist organizations
in analyzing financial data such as revenue, expenses, and profit margins to
discover development opportunities.
- Operations Management: By tracking key performance
indicators (KPIs) and identifying areas for improvement, BI may assist organizations
in optimizing their operations.
- Supply Chain Management: Business intelligence may assist
firms in monitoring their supply chain, tracking inventory levels, and
identifying bottlenecks in the process.
Source: Grydd
Overall, business intelligence (BI) plays an important role
in data analytics by providing organizations with the tools they need to
transform their data into meaningful insights. Organizations can use BI
technologies to make data-driven decisions that improve their operations,
customer experience, and profitability.
Keywords: business intelligence, data analytics, BI tools, BI dashboards, data visualization, decision-making, sales and marketing, financial analysis, operations management, supply chain management, KPIs, data-driven decisions, customer experience, profitability
References
Jourdan, Z., Rainer, R.K. and Marshall, T.E. (2008). Business Intelligence: An Analysis of the Literature1. Information Systems Management, 25(2), pp.121–131.
Montero, J.N. and Lind, M.L. (2021). Determining Business Intelligence Usage Success. [online] papers.ssrn.com. Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3774861 [Accessed 12 Dec. 2021].
Arnott, D., Lizama, F. and Song, Y. (2017). Patterns of business intelligence systems use in organizations. Decision Support Systems, 97, pp.58–68.
Feel free to comment below with your experience in Business Intelligence in Data Analytics.
Written by, Jasminder Kaur
Very interesting and informative.
ReplyDeleteVery interesting and informative
ReplyDeleteGreat article
ReplyDeleteVery informative
ReplyDeleteVery interesting, could you please do a post with practical examples?
ReplyDeleteThe blog post provides a concise and informative introduction to business intelligence (BI) and its various applications. It effectively explains how BI technologies can help organizations in making data-driven decisions by providing them with accurate and timely information through BI dashboards.
ReplyDeleteHow can BI help organizations in optimizing their operations management? What are some key performance indicators (KPIs) that can be tracked using BI, and how can they be used to identify areas for improvement?
Organizations can find areas for improvement and make adjustments to their processes to maximize their performance by tracking these KPIs. For example, if a process's cycle time is too long, the company can look for ways to streamline the process and reduce the time required to complete it. Similarly, if inventory turnover is poor, the company can seek strategies to boost sales or lower inventory levels in order to improve efficiency.
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