Data Analytics for Business: How to incorporate Data-Driven Change

Artificial intelligence (AI) and big data penetrate most of the new Web-based software that makes production and monitoring systems faster and more efficient. Many of these technological advancements in organizations result in continuous data collection processes by their own systems, and big data and artificial intelligence enable businesses to better leverage the data collected. And in favor, it helps build a data-driven decision-making culture with higher accurate moves to drive businesses forward.

🔗Changing Business Environments and Decision Support System

Adapting to change is hard in the workplace. Especially if the organization is not ready to accept change according to their current and potential knowledge. But as a rule of thumb for businesses: those who do not adapt and become agile will eventually perish to competitors. It is stated that change is an unavoidable part of how modern businesses must operate. The key driving forces of the continual changes are growing information flows, new business practices, customers, competition, employees, and rapidly changing technology. Technology plays a critical role in both initiating and enacting change.

💡What are BI and DSS?

• 👉Business Intelligence is used to review and transform complex data into meaningful, actionable information that may be used to support more effective strategic, tactical, and operational insights and decision-making. Company intelligence environments are made up of a number of technologies, applications, processes, strategies, products, and technical architectures that are used to collect, analyze, present, and disseminate internal and external business data.
• 👉The Decision Support System is an information system that aids a business in decision-making activities that require judgment, determination, and a sequence of actions. The information system assists the mid-and high-level management of an organization by analyzing huge volumes of unstructured data and accumulating information that can help to solve problems and help in decision-making.

Oftentimes, people get conflicted by DSS vs BI. Whereby both are complementary to each other. In today’s world, Most BI software includes in one way or another some form of DSS within its capable model. Alongside query, reporting, analytical processing, statistical & descriptive analysis, and data mining /explicit to specific software/.

📈Benefits to Organizations

Having multiple ways of analyzing current Data Assets within your organization will lead to better performance, decisions, and overall revenue. There is no doubt that turning messy numbers into actionable figures to carefully have a correct decision will impact positively businesses and organizations. From Analyzing to Prediction and Automation, as well as Risk Mitigation and Alignment of Operations Scope will have its revenue across your business ecosystem.

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🛫THE TAKEAWAY

Theory and practice show that when it comes to BI usage, modern enterprises are clearly divided. Banks, financial institutions, and commercial organizations are among the places where advanced implementations can be found. There, Business Intelligence is utilized for a variety of purposes, including consumer segmentation and profiling, predicting client loyalty, analyzing credit risk, detecting fraudulent activities, forecasting the development of important business processes, and more.

Organizations that employ business intelligence can be divided into two groups: those with strong business culture and those with a strong analytical culture.🧠

About me

I’m an articulate Data Analytics and Business Intelligence Expert with more than five years of progressive and continuous experience in the BI and Decision-Making field and project management, as well as 4 years of experience in the Finance sector. Personable with strong knowledge and experience in Operations, Risk, Data Analytics & Visualization. I am helping financial institutes and directors to perform accurate Financial Data Analysis & Analytics that will benefit in volume, growth, brand, and profits; and mitigate associated risks with taken actions.

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