Customizable services to ensure that the client’s data is well organized, secure, and seamlessly retrievable by key business and analytics applications.
‘Wide Data’ is a framework for building comprehensive data foundation by collecting and unifying a large variety of structured and unstructured data from internal and external sources.
Characterized by the 3 Vs – Variety, Velocity and Veracity – Wide Data serves as an effective starting point for a 360° analysis of leading indicators.
By leveraging Wide Data, enterprises can account for external dependencies (macroeconomic factors, holiday calendar, weather phenomena, etc.) while training the AI/ML applications.
Collecting wide data requires a variety of techniques, including but not limited to APIs, ETL, keywords extraction, speech-to-text, web scraping, and image annotation. Findability Sciences offers the necessary skills, methods, and tools to build robust pipelines for secure data collection.
Wide Data delivers a distinct advantage in terms of identifying specific information and insights from individual data components.
Findability Sciences works both with pre-configured GRC systems and provide customized integration services for third-party applications.
Unstructured content from documents, emails, audios, images, and videos is processed using NLP (natural language processing) and Computer Vision to obtain structured data for training AI/ML algorithms.
Missing or ‘bad’ data is treated, multiple formats are reconciled, and an AI-ready dataset is produced after schema integration and entity resolution.
Data Unification forms an integral part of CUPPTM – our proprietary framework for AI solution development. CUPPTM stands for Collection, Unification, Processing & Presentation.
Enterprise customers rely on Findability Sciences to manage the key phases of their data pipeline, from collection to processing to storage to access.
Our data census and information architecture services provide detailed views of the organization’s data-scape (internal, external & third party) and help design secure pathways for relaying data to-and-fro from AI, analytics, and business applications.