In this post, let us consider Information Technology Management vs Business Analytics. Scroll down to learn more.
Information Technology Management vs Business Analytics
Information Technology Management
So, information technology management is a combination of three major domains that are related to technology and its applications in organizations. It is a vast field that addresses the whole spectrum of technology required by organizations.
Moreover, it concerns the application, development, deployment, and overseeing the use of information technology to support the business goals and objectives of an organization. IT management includes functions such as IT strategy, planning, design, implementation, and support for all aspects of information technology. The core areas include:
Business Systems Planning
It involves planning for current and future business processes and systems. The systems include accounting, inventory control, and customer relationship management (CRM) systems among others.
Infrastructure Management
It involves managing server, storage, and network infrastructures. Also, it involves managing the security of the data and systems. It includes capacity planning and monitoring and maintenance of the hardware and software.
Software Development and Project Management
It involves planning and managing the IT projects and programs and involves hiring and managing the IT professionals. Also, it involves developing, implementing, and supporting software applications for various business processes.
IT Audit
It involves overseeing the security of information technology systems in an organization. The IT audit is conducted to detect security breaches, detect vulnerabilities in the system, and recommend corrective measures.
What is Business Analytics?
Business analytics is the application of statistical and mathematical analyses and modeling techniques to derive insights from data and information to provide a better understanding of business processes, operations, and strategy. It provides a decision-making framework that helps with identifying opportunities, managing risks, and making informed decisions. Business analytics involves the following:
- It involves deriving insights from an organization’s data and information assets to support decision-making.
- It includes extracting patterns and hidden trends from data through mining techniques such as clustering, association rule mining, classification, and regression analysis.
- Creating a common language for a business by creating a shared view of all available data including structured data from databases, semi-structured data from websites, documents, spreadsheets, e-mails, and unstructured data from voice, video, and images.
- It also involves converting this data into information through data preparation, data integration, data modeling, analytics, reporting, and dashboards.
- Helping in forecasting future business activities by combining historical data with current business events.
- It helps in identifying vulnerabilities and risk patterns and recommends corrective measures to mitigate the risk and take advantage of opportunities.
Business analytics is used in areas such as frontrunner selection, customer relationship management (CRM), supply chain management, product innovation and development, sales and marketing, and financial forecasting among others.
To Conclude
As we can see here, IT management is a vast area that deals with all aspects of information technology in an organization. It includes planning for the current and future business processes and systems. It also includes managing the servers, storage, and network infrastructures. Also, it involves software development and project management. IT management also involves overseeing the security of information technology systems in an organization.
On the other hand, business analytics helps in deriving insights from an organization’s data and information assets to support decision-making. It involves extracting patterns and trends from data through mining techniques such as clustering, association rule mining, classification, and regression analysis.
