
Dark data assessment: Get insights from unstructured data
Minimize sensitive data exposure and optimize costs with VisualizeNXT and ArchiveNXT. Download the brochure to learn more.

Data Analytics and AI/ML
Discover how our AI and ML solutions can help you democratize data use and become data-driven and customer-centric.

Enterprise quality insights and intelligence platform
Enterprise quality insights and intelligence platform ensures global quality in life sciences via real-time monitoring, data ingestion, and cloud-based enterprise insights.

Protecting data in the digital era
The digital revolution has driven enterprises to embrace cloud adoption, creating interconnected systems and data networks.

AlertAE: Next-gen pharmacovigilance solution
Intelligent identification and classification of adverse events, product quality complaints and clinical queries

HCLTech’s Rapid Analytics
HCLTech's Rapid Analytics, powered by SAP Analytics Cloud (SAC), allows users to quickly create new visualizations through self-service functionality — letting them model new scenarios on the fly.

What is Digital Analytics?
Digital analytics is the process of analyzing digital data from various sources like websites, mobile applications, among others. It provides a clear vision to the organization on how users or customers are behaving.

The evolving role of data in financial services
Beyond reporting, data is now viewed as a catalyst for innovation in financial services, but ensuring data quality remains a challenge

Patient-centric approaches to health data improve data governance
Taking a patient-centric approach to health data governance can help reduce costs, while also improving patient care and gaining new customers

Google Dataplex: A game changer in data fabric era
A blueprint to enhancing data quality and analytics for enterprise success

Automated case quality check
Both Pharma’s and patients benefit from better speed and accuracy provided by Automated Case Quality Check (ACQC). Read the blog to understand how ACQC works.

Invest in Data Quality, since ignoring it is a recipe for disaster
Investing in data quality is crucial for accurate insights and decision-making. Ignoring it leads to costly errors, inefficiencies, and risks that can harm business outcomes.