Business Intelligence & Data Mining

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• Business Intelligence & Data Mining 4:53:03

  • 1: What is Business Intelligence 04:29
  • 2: Startong Case in understanding BI needs in diff phase of business 06:29
  • 3: Decision Making Process and Need of IT systems 20:20
  • 4: Problem Structure and Decision Support System 11:12
  • 5: Introduction to BI Applications 17:43
  • 6: Dashboard presentation systems 07:18
  • 7: Different Types of Charts used in BI DashBoards 29:31
  • 8: Good DashBoard and BSC 12:32
  • 9: Examples of Bad Dashboards 1 06:35
  • 10: Examples of Bad Dashboards 2 01:08
  • 11: Process of KPI Development 26:14
  • 12: Overviw of Datawarehouse 07:33
  • 13: More explaining of data warehouse and steps in processing 08:50
  • 14: Data Warehouse Architecture - Tiers 17:36
  • 15: Data Warehouse - compomemts 15:01
  • 16: Approach to develop data structure and Models of database 16:12
  • 17: Basics of Data Mining - Meaning 35:10
  • 18: Basics of Data Mining - Stages of DM 24:45
  • 19: Data Mining Technique - Classification 07:14
  • 20: Data mining - Clustering 01:52
  • 21: Data Mining - Association Rules 04:40
  • 22: Data Mining Applicatons - Banking 02:39
  • 23: Data Mining Applicatons - CRM 03:37
  • 24: Data Mining Applicatons - other industries 04:23

Students will learn the following key skills and knowledge from the "Use of Business Intelligence: Basics of Data & Data Mining" course:

• Understanding Business Intelligence: Students will gain a comprehensive understanding of the role and importance of business intelligence in modern organisations. They will learn how business intelligence can drive informed decision-making and improve overall business performance.
• Data Analysis Fundamentals: Students will acquire essential skills in data analysis, including techniques and methodologies for analysing and interpreting data. They will learn how to identify patterns, trends, and insights from data and present their findings effectively using data visualisation techniques.
• Data Mining Techniques: Students will explore various data mining techniques and algorithms used to extract valuable information from large datasets. They will learn how to preprocess and clean data to ensure data quality and employ data mining algorithms to discover patterns, associations, and correlations.
• Predictive Analytics and Machine Learning: Students will be introduced to predictive analytics and its significance in business intelligence. They will gain knowledge of machine learning algorithms and their applications in building predictive models. Students will learn how to leverage machine learning techniques to make data-driven predictions and forecasts.
• Business Intelligence Implementation: Students will learn how to design and implement business intelligence systems effectively. They will understand the principles of data warehousing and data integration and explore best practices for data governance, privacy, and security in the context of business intelligence.
• Ethical Considerations in Business Intelligence: Students will develop an awareness of the ethical implications associated with the use of business intelligence. They will learn about privacy, consent, and legal considerations in data collection and analysis. Students will understand the importance of responsible and ethical use of business intelligence tools and techniques.

By the end of the course, students will have a solid grasp of the foundational concepts and practical skills required to leverage data effectively in a business environment. They will be capable of collecting, analysing, and interpreting data to make informed decisions, implement business intelligence systems, and navigate ethical considerations surrounding data usage.

Why Choose this Course?

• Conducted by industry experts
• Get Instant E-certificate
• Fully online, interactive video course
• Developed by qualified professionals
• Self-paced learning and laptop, tablet, and smartphone-friendly
• 24/7 Tutor Support

This course is designed for individuals who are interested in gaining a comprehensive understanding of business intelligence, data analysis, and data mining. It is suitable for:

• Business Professionals: Professionals working in various roles within organizations, such as managers, analysts, consultants, and executives, who need to make data-driven decisions and leverage business intelligence tools and techniques.
• Data Analysts: Individuals aspiring to become data analysts or enhance their data analysis skills will benefit from this course. It provides them with a strong foundation in data analysis techniques, data mining, and predictive analytics.
• IT Professionals: IT professionals involved in the implementation and maintenance of business intelligence systems, data warehouses, and data integration solutions will find this course valuable. It equips them with the knowledge required to design and implement effective business intelligence solutions.
• Students and Graduates: Students pursuing degrees or certifications in business, data science, or related fields can benefit from this course. It provides them with essential skills and knowledge in business intelligence, data analysis, and data mining, enhancing their employability in the job market.
• Entrepreneurs and Business Owners: Individuals starting their own businesses or managing small to medium-sized enterprises can gain insights into leveraging data effectively to make informed business decisions. They will learn how to implement business intelligence systems and use data mining techniques to gain a competitive edge.

It is important to note that while this course covers the basics of data and data mining, it can also serve as a refresher or introductory course for professionals seeking to update their skills or expand their knowledge in the field of business intelligence.

No previous knowledge of Business Intelligence & Data Mining is required to continue this course.

Completing the "Use of Business Intelligence: Basics of Data & Data Mining" course can lead to various career paths, including:

• Business Intelligence Analyst
• Data Analyst
• Business Intelligence Developer
• Data Scientist
• IT Project Manager

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