Businesses need to respond to all kinds of stimuli in real time to become a live enterprise. They learned this more than ever during the pandemic. Intelligent gathering, cleansing, storing, and using real-time data are crucial to ensure that technologies ranging from artificial intelligence (AI) to cybersecurity work seamlessly and deliver desired results.

From data-driven to data economy

Adapting to market dynamics: the three horizons
Show all horizons
Velocity, Variety, Volume


Data economy and live enterprise

Data is the new capital;
AI transforms life, economy

Key Patterns

  • Connected data
  • Ecosystems
  • Data exchanges
  • Intelligence at scale
  • Edge intelligence
  • Conversational systems
  • Human machine interactions
  • Autonomous


  • Connected data across enterprises, ecosystem players, and machines
  • Convergence of transactional and analytical platforms
  • Smart governance
  • Consumerization and monetization of data
  • Sentient enterprise
  • Augmented - AI engineering
  • Privacy first
  • Secure by design


Data and digital native enterprise

Innovate, Transform,
Reimagine Business

Key Patterns

  • Hybrid cloud
  • Integrated data platforms
  • Analytics
  • Digitize consumption
  • Migration and modernization


  • Structured and unstructured data
  • Data mesh
  • Experimentation and innovation by leveraging analytics
  • Extreme automation


Data-Driven enterprise

Better decisions

Key Patterns

  • Legacy data arch
  • DW and appliances
  • MDM
  • Reports and dashboards


  • Structured data
  • Decision support systems - descriptive and diagnostic insights

Key trends across data subdomains

Databases and platforms

Trend 1

Data platforms transforming into business growth enablers

Modernization and cloud adoption were earlier known to enhance cost-saving efficiency, but now they enable agility and connectivity to data as well. Platforms with packaged insights address specific business needs such as next-best recommendations, and off-the-shelf and/or custom-developed iterations are gaining popularity.

Trend 2

HTAP for faster insights

HTAP is an emerging application architecture that combines transaction processing and analytics within the same datastore. This trend has come in the spotlight with recent advances in research, hardware, in-memory, and cloud-native database technologies.

Data pipeline and streams

Trend 3

AI-driven data engineering to increase the velocity of innovation

Agility is critical to reduce time to market and remain competitive. While most organizations have adopted agility from a process perspective, data engineering techniques largely follow traditional ETL frameworks. They still rely on a requirement-driven approach, increasing the cycle time involved in provisioning new data for analytics needs.

Data consumption

Trend 4

Marketplaces helping businesses to democratize data consumption

Enterprises are leveraging marketplaces for the internal democratization of data consumption. This provides visibility on available enterprise data assets, enabling discoverability, collaboration, and consumption in a self-service manner. Marketplaces also enable a secure data exchange outside enterprise boundaries, critical for realizing the vision of a connected enterprise.

Trend 5

Sentient systems connecting AI/ML to business processes for better insights and actions

Sentient systems take AI/ML and insights generation to the next dimension by integrating with business processes to incite humans to action or drive autonomous decision-making. Real-time event sensing, contextual event processing, and intelligent decisions and actions are the key capabilities of a sentient system.

Data governance and operations

Trend 6

Proactive smart governance through AI-first

There is a shift from reactive and rule-based data governance to an end-to-end autonomous “no governance” ecosystem, leveraging the principles of AI-first, cognitive, and governance by exception. Smart data discovery, data tagging, DQ assessment, DQ rule discovery, relationship discovery, and automated cleansing enable smart governance.

Trend 7

Intelligent cloud-based data operations to increase operational efficiency

As increased cloud adoption has scaled up ondemand infrastructure, the focus is now around intelligent orchestration of infrastructure-ascode capabilities to drive operational efficiency. Capabilities such as leveraging ML-based techniques to predict capacity needs, identifying anomalies, and self-healing platforms will define the route of future data operations.

Data privacy

Trend 8

Growing data usage and privacy regulations call for unified rules

Growing data privacy regulations and data breaches are increasing the cost of privacy compliance, protection monitoring, and management. Advances in data-centric services have fueled the demand for better data privacy. As sentience and intelligence are increasingly embedded almost everywhere, enterprise and consumer advocacy groups have been asking for clearer rules to protect personal data and individual privacy.

Trend 9

Privacy-first modernization, driven by increasing cloud transformations

Cloud transformation and modernization offer significant opportunities for privacy-first app development. Organizations are looking to deliver high-quality applications at minimum cost. They need a test data management (TDM) strategy that supports waterfall and agile delivery models. With the rapid adoption of DevOps and increased focus on automation, the need for data privacy has grown immensely.

Data assurance

Trend 10

Cloud data validation for reliable data clouds and lakes

Data errors and inconsistencies accumulate, with data moving in or out of the cloud (or data lakes). Therefore, the lack of proper cloud data validation is an existential threat to data-sensitive organizations.

Trend 11

Developing end-to-end, self-service test data management

Organizations have shown increased interest in TDM in recent times, as they realize that proper test data can prevent financial losses caused by production defects. Test data has evolved from a few sample files to powerful test data sets with high coverage.

Data security

Trend 12

Securing data across the value chain, from origination to consumption

With enterprise boundaries fading, most of the enterprise data is either on public or private clouds. Further, with remote working, global teams, and increased cloud adoption, it is crucial to protect applications and data and the channels connecting to them. Digitization has also increased third-party and partner collaboration, leading to sharing of unstructured data.

Trend 13

Cloud access security brokers for enhanced data protection

Enterprises can now focus on core capabilities, with cloud adoption easing data storage concerns. Elevated concerns toward privacy and security breaches have increased the demand for cloud security solutions. That said, the prominence of cloud access security brokers (CASBs) is gaining traction. The global CASB market is estimated to expand at a compound annual growth rate of 18.2% during 2019-2025.

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