Inability to define the nomenclature for data
Not being able to maintain the quality and trust in data
Lack of expertise to handle variety of databases
Prohibitive cost to analyze the unstructured data
Coordinated use of data-points leading to high efficiency data-ops
Increased data usability. reliability, and connectivity
Apps able to scale significantly reduce runtime maintenance costs
3X reduction in app data costs by processing information in ETL stage
Maintaining a data health check at the time of ingestion so that you can score and identify bad data sources
Comprehensive view of customers, products, channels, and campaigns
We maintain the sanctity of data for marketing (Camptag), sales (accounts, contacts, leads), and webpages.
We build scalable solutions using NoSQL databases like MongoDB, graph databases like Neo4J, and postgress databases like Redshift
NLP based text mining and OCR based pdf mining at the time of ETL
Data analysts skilled in big data
Proven use cases for digital marketing across industries
Data Governance,process rigor, automation, and optimization
Can work with streaming, unstructured, and large volumes of data across Azure, GCP, Apache, and AWS
