Data is the primary driver of an efficient AI model. It is the precursor of automation, adaptation, and prediction, so with data unification, the models can be fabricated up to the desired precision. Data consolidation refers to the collection, extraction, combination, transformation, and storage of data in a centralized manner.
Different techniques like ETL (Extract, transform & load), data visualization, data warehousing, and data integration can be amalgamated as per the customer’s necessity. The primary goal is to retrieve data from heterogeneous information sources and transform it into valuable insights with data cleansing, aggregation, interpolation, extrapolation, textual analysis, etc.