Course - Data Storage and Processing - edX
Master the culture of data representation, interpretation and outcomes evaluation. Learn the fundamentals of relational and NoSQL database management systems.
Objectives
- Initial data processing (data cleaning and filling in the missing values)
- Data smoothing and normalization
- Normalization of unipolar and bipolar indicators. Normalization features for ball scales.
- Data visualization
- Time series analysis
- Descriptive statistics
- Data storage and access by means of relational DBMS
- NoSQL databases and Big data
Syllabus
Week 1:Data preprocessing
Basic concepts of data processing. Stages of data analysis (collection, sorting, transformation, building models and interpretation). Data measurements and scales. Data types and sources. Data preparing
Week 2:Data processing tools and visualization
Digital spreadsheets. Data visualization goals. Methods and purposes of correct data visualization.
Week 3:Data processing
Descriptive statistics. Data normalization and transformation. Time-series analysis and forecasting. Types of time-series smoothing. Trends, seasonal time series modelling
Week 4:Relational databases management systems
Introduction to relational DBMS starting from relational data model. SQL statements and queries creation. Database indexes and transactions requirements.
Week 5:NoSQL
Main characteristics of not only SQL databases. Non-structured and semi-structured data and scalability of NoSQL databases. Types of NoSQL databases: column-oriented, key-value store, document store and graph databases.
Data Analysis Steps
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Describing the objects under the study
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Variables Identification and a hypothesis generation
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Data Collection for the creation of a Population or a Sample
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Data Sorting
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Data Transformation
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Building Models
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Interpretation