Analytics Pathways Consulting Services | HCLTech

Analytics Pathways


Analytics Pathways is a consultative approach to engage business and technology stakeholders in defining their digital transformation journey across Big Data and analytics solutions.

Today’s digital ecosystem comprises a wide array of commercial and open-source software, cloud and on-premise offerings, and software-as-a-services solutions. Organizations struggle to define and deploy initiatives across the wide array of technologies across Enterprise and Big Data, MDM, Enterprise Reporting, and Data Science. Organizational change in terms of business process and retraining team’s enterprise EDW and reporting team to produce Big Data and advanced analytics is also challenging.

Analytics Pathways provides our consultants and clients with a knowledge base of questions, surveys, and assessment tools to analyse the current environment, measure needs and priorities, and evaluate the results and determine a path forward. Each Analytics Pathway engagement is tailored to the client’s objectives and scope using a set of 12 dimensions. It enables clients to analyze and align business and information strategies, business and technical architectures, data quality, governance and methodology, Data Science and applied analytics, and organizational readiness. Analytics Pathways provides the measurements to determine the path forward with future-state business processes and architectures, business cost, and organizational change management.

Clients receive a road map that aligns initiatives mapped to business value, time and cost to implement, and training guides. Moreover, business process and business models as well as co-innovation labs and proof-of-concepts may also be part of the engagement.


Big Data Pathways

  • Unified Big Data and analytics architecture
  • Traditional EDW and ETL to Big Data migration
  • Data security models

MDM & Data Governance Pathways

  • MDM maturity assessment
  • MDM technology assessment
  • MDM implementation road map

Data Science Pathways

  • Analytics maturity assessment
  • Future-state reference architecture
  • Bespoke algorithms to address specific use cases

Use Case Prioritization

  • Align key performance indicators and analytical methods
  • Identify quick wins using business value vs. cost & time-to-market quadrant analysis
  • Identify data sources and availability