Data Analytics

Method in which qualitative and quantitative technique is used to enhance the productivity and business gain. It applies fundamental scientific principles to the analysis of large, complex data sets. Data Analytics are of three types.

-> Descriptive Analytics - What has Happened?

-> Predictive Analytics - What could happen?

-> Prescriptive Analytics - What should we do?

Analytics is data science of using data to build models that leads a faster and better decision making, cost Reduction, and improved services and products to the company.

Even before recording of data on any medium, the most primitive form of data analytics was maintained using the phases of the moon (i.e.., count of polishing & diminishing). Using the same, they used to predict the stormy, rainy and sunny days.

Data Analytics

Data Migration - Process of selecting, preparing, extracting, and transforming data from one storage system to other. Database migration is usually performed programmatically in automated manner.

Data Quality - The ailment of a set of values of qualitative or quantitative variables. Data quality is a perception or an assessment of data's fitness to serve its purpose in a given context.

Data Warehousing - Data warehousing is a technique of collecting and managing data from varied sources to provide meaningful business insights. It is a combination of technologies and components which allows the strategic use of data.

Data Processing - Series of operations that use information to produce a result. Common data processing operations include validation, sorting, classification, calculation, interpretation, organization and transformation of data.

Data Modelling - Discrete structured data representation of a real-world set of entities related to one another. Each entity (most often represented using a table) carries a set of characteristic attributes.