From defining People Analytics and understanding data collection to exploring Big Data infrastructure components and analyzing its applications, this course equips you with the skills to harness the power of data for strategic decision-making and organizational growth.

After the successful completion of this course, you will understand the following;

People Analytics:

Define People Analytics and distinguish it from traditional HR practices.
•Explain the benefits of using People Analytics in organizations.
•Identify the key concepts and techniques used in People Analytics, such as data collection, analysis, and visualization.
•Understand how People Analytics can improve workforce performance, retention, and engagement.
•Analyze the challenges associated with implementing People Analytics in organizations, such as data privacy and ethical considerations.
•Appreciate the role of People Analytics in a data-driven organization and its potential impact on business outcomes.
•Evaluate case studies and examples of successful implementation of People Analytics in different industries.

Data Collection and Analysis for People Analytics:

⦁ Identify the Different Data types and Sources used in People Analytics.
⦁ Explain the Importance of Data Cleaning and Preparation in People Analytics.
⦁ Apply Data Analysis Techniques, and Interpret Statistical Measures Used in People Analytics.
⦁ Recognise the Challenges Associated with Collecting and Analysing People-Related Data and Formulate Strategies for Addressing the Challenges.
⦁ Understand the Ethical Considerations Associated with Collecting and Analysing People-Related Data Such as Informed Consent and Confidentiality.

Big Data Infrastructure:

⦁ Understand the Components of Big Data Infrastructure Including Storage Systems, Distributed File Systems, and Processing Frameworks.
⦁ Identify the Characteristics and Benefits of Distributed File Systems Such as Hadoop Distributed File System (H.D.F.S).
⦁ Describe the Architecture and Capabilities of Apache Spark and its Role in Big Data Processing.
⦁ Recognise the Use Cases and Benefits of Apache Cassandra as a Distributed N..O.S.Q.L Database.
⦁ Compare and Contrast Different Big Data Storage and Processing Systems Such as Hadoop, Spark, and Cassandra.
⦁ Understand the Scalability and Fault-tolerance Mechanisms Used in Big Data Infrastructure Such as Sharding and Replication.
⦁ Appreciate the Challenges Associated with Deploying and Managing Big Data Infrastructure Such as Hardware and Software Configuration and Security Considerations.

Big Data Analytics:

⦁ Identify the Different Types of Big Data Analytics, Such as Descriptive, Predictive and Prescriptive Analytics.
⦁ Understand the Data Mining Process and its Role in Big Data Analytics.
⦁ Apply Machine Learning Techniques Such as Classification, Regression and Clustering to Analyse Big Data.
⦁ Describe the Principles and Applications of Natural Language Processing in Big Data Analytics.
⦁ Recognise the Benefits and Limitations of Big Data Analytics in Different Industries Such as Healthcare, Finance and Marketing.
⦁ Evaluate the Accuracy and Reliability of Big Data Analytics Results.
⦁ Understand the Ethical and Legal Considerations Associated with Big Data Analytics, Such as Data Privacy and Intellectual Property Rights.

All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details.

There are no strict entry requirements for this course. Work experience will be added advantage to understanding the content of the course.

The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience.

1. People Analytics Specialist
2. Data Analyst
3. HR Data Scientist
4. Big Data Engineer
5. Business Intelligence Developer
6. Data Architect
7. Big Data Consultant
8. HR Technology Manager