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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

  1. Describing the objects under the study

  2. Variables Identification and a hypothesis generation

  3. Data Collection for the creation of a Population or a Sample

  4. Data Sorting

  5. Data Transformation

  6. Building Models

  7. Interpretation

https://www.edx.org/course/data-storage-and-processing