10-11.04.2024 - BCS Data Analysis - присъствен курс
Детайли за курса:
- 2 дни
- Цена на курса 1000 лв. + ДДС. Цена на изпита remote proctoring 790 лв. + ДДС
- 10/04/2024 - 11/04/2024
Entity relationship modelling, analysis class modelling and normalisation of data. They’re the three key approaches to analysing and modelling data, and they’re all covered on our course on Data Analysis.
You’ll also learn about approaches that reflect the business users’ needs and priorities, and gain an overview of the more mechanistic approach offered by normalisation. And finally we’ll explore the techniques used to validate data against stated requirements.
Presented to you by one of the expert training consultants pictured below, each member of our Data Analysis training team bring their substantial data analysis and data modelling experience to the programme.
Introduction to Business Information and Data – 3 hours
- Initial concepts and terminology
- Information versus data
- Data analysis versus data analytics
- Data modelling and data models
- Conceptual, logical and physical data models
- Static and dynamic views of data
- Structured and unstructured data
- The Data Lifecycle
Modelling Data Using Class Diagrams – 3.5 hours
- Classifying elements of substance and their attributes
- Classes and objects
- Attributes
- Associations and multiplicity
- Types of relationships (one-to-one, one-to-many, many-to-many)
- Resolving many-to-many relationships
- Showing multiple roles
- Aggregation and composition
- Generalisation
- Naming conventions
- Class diagrams
Defining Data Requirements – 3.5 hours
- Defining data
- Metadata (structural, descriptive and statistical metadata)
- Data definitions
- Domain definitions
- Relational data theory
- Two-dimensional structures
- Using keys to identify data (primary, foreign, concatenated, compound and hierarchic keys)
- Normalisation
- The normalisation process
- Un-normalised form, first normal form, second normal form, third normal form
- Relations
- TNF (Third Normal Form) model
- Aspects of data quality
Obtaining and Recording Data – 1 hour
- Identifying sources of data
- Validating data models using a CRUD matrix
- Data navigation paths and Data Navigation Diagrams
Analysis for Decision Making – 3 hours
- A process for data analytics
- Sourcing datasets
- Data lineage
- Validating and cleansing datasets
- Confirmation bias
- Sampling
- Outliers
- Consistency
- Dataset calculations
- Counting
- Totalling
- Averaging (mean, median, mode)
- Maximum and minimum
- Probability
- NULL values
- Identifying meaningful relationships
- Regression analysis
- Correlation and causation
- Time-series analysis and forecasting
- Interpreting results
Protecting Data – 1 hours
- The imperative for protecting data
- CIA (Confidentiality, Integrity and Availability)
- Data protection principles
- Data ethics
- Data ethics principles
- Online data
Изпитът e Multiple choice questions формат и е наличен в изпитните центрове на Pearson Vue и като Remote proctoring. И в двата случая е необходимо да имате 26 верни отговора от 40 възможни, за да вземете изпита. Времетраенето е 90 минути + 23 минути добавено време за non-native English speakers.
