Data Fundamentals

Data Fundamentals

1. Data

   • Is representation of information
     • DATA LIFE CYCLE
       • Can be divided into
         • * Data governance *Data generation *Data storage *Data collection *Data processing *Data management *Data integration *Data analysis *Data visualization
     • TYPES OF DATA
       • Can be divided into
         • Structured
           • define structured data as data that can be organized in tabular form through rows and columns.
         • Unstructured
           • They are data that do not have a predefined format or structure.
         • Quantitative
           • refers to information presented in numerical form that can be measured and counted
         • Qualitative
           • refers to information that describes qualities and characteristics which cannot be measured in numerical terms.
     • DATA QUALITY
       • Can be divided into
         • DATA QUALITY ASSURANCE
           • DATA QUALITY PLANNING
             • Is a development scheme, what will be the general requirements, objectives, and a plan to reach the desired level of maturity of data quality management in the organization, must be defined.
           • DATA QUALITY CONTROL
             • Consists of the set of activities to specify and control the creation and updating of data to ensure that the data meets the requirements.
           • It is necessary to establish the current status of data quality to establish the activities to be developed to improve data quality.
         • DATA QUALITY IMPROVEMENT
           • Corresponds to actions to achieve a continuous improvement process so data quality is maintained and sustainable
         • RESOURCE PROVISION
           • It is necessary at the organizational level to understand the significance of maintaining a continuous management and develop skills related to data to provide resources.
       • DATA-RELATED SUPPORT
         • In this step, activities are developed, and tools are defined to support data quality management.
     • DATA ORGANIZATION
       • Can be divided into
         • DATA WAREHOUSE
           • A data warehouse is a unified repository for all data collected by the company’s systems. The repository can be physical or logical and emphasizes the capture of data from various sources, primarily for analytical and access purposes.
         • DATA LAKE
           • A data lake is a centralized storage repository that contains big data from various sources in a granular, raw format.