JerseyITech Intelligence’s Big Data Engineering services enable organizations for data transition, business decision making, and leveraging of AI. Data transition is in different phases: Data at Rest, Data in Motion, Data in Process, and Data in Consumption.
JerseyITech has helped clients integrate and organize large volumes of structured and unstructured data. This includes transaction data, organization data (finance, marketing, product, customer, employees, etc.), log files, system-generated data, primary and secondary research data, web data and social media data (text, image, video, and speech). Big Data Engineering helps businesses better align their Artificial Intelligence strategy with business objectives and respond faster to threats and opportunities.
The JerseyITech methodology is technology agnostic. We offer data management and transformation expertise in traditional, new generation, proprietary, and open source platforms, both on premise and on cloud.
ENGINEERING ON ANY TYPE OF INFRASTRUCTURE
Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), or on Premise
BUSINESS APPROACH TO DATA ENGINEERING
Focus on maximizing business outcomes from data rather than creating a data dump
DATA GOVERNANCE PRACTICES
Industry best practices and approaches around metadata, data quality, and data security
HOLISTIC DATA MANAGEMENT
Data practices and solutions across different data stages (Rest, In Motion, In Process, and Consumption)
TECHNOLOGY AGNOSTIC APPROACH
Capabilities across the data tech stack to enable ingestion through transformation and consumption
INDUSTRY DOMAIN RELEVANCE
Industry specific approach to data engineering and practices for efficient information management