Kumar Srivastava

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Opinions expressed by ICN authors are their own.

Kumar Srivastava has spent his career building big data and analytics products as part of a diverse and broad application set such as social networking, online security, identity, reputation and trust management, online fraud and abuse, online search and advertising, digital platforms, mobile applications and monetization services.

Kumar has worked with organizations of all sizes, from Fortune 50 companies to midsize businesses and small startups, and he has been involved in research at Columbia University and has led products that have been honored as industry-defining by customers and analysts.

Srivastava holds several patents and regularly writes thought leadership articles about the convergence of big data, analytics, cloud, mobile and digital and its impact on and opportunity for entrepreneurship and innovation. He has been published in Forbes, Wired, Entrepreneur and other publications, and he wrote a book on APIs and platform product management.

The opinions expressed in this blog are those of Kumar Srivastava and do not necessarily represent those of IDG Communications Inc. or its parent, subsidiary or affiliated companies.

Key cloud trends for 2018

Planning for disaster recovery

Planning for disaster recovery

Let's face it: downtimes are not only frequent, but expected. What is your company doing to to ensure speedy recovery and restoration of service when the inevitable occurs?

Planning for disaster recovery

Planning for disaster recovery

How do leaders of enterprises plan for outages to minimize the impact on the users of all the individual service providers running their services on the enterprises' platforms?

Nobody likes apps that crash

Nobody likes apps that crash

Why developers should pay attention to their crash reports.

Best practices for a secure and trustworthy container platform strategy

Best practices for a secure and trustworthy container platform strategy

Container technology has a direct impact on the agility of a software development team and consequently have seen a huge increase in interest, adoption and usage.

IS ETL dead? In the age of AI, not quite

IS ETL dead? In the age of AI, not quite

It's just more complex, harder and significant.

Intelligent image and video management for the enterprise

Intelligent image and video management for the enterprise

As image and data quality goes up – driven by better capture, transfer, processing and compressing technologies – the ability to store and process these images and video data easily becomes a competitive advantage.

Disaster recovery in the age of data and AI

Disaster recovery in the age of data and AI

To ensure that data is not lost, and outages are recovered from swiftly and efficiently, enterprises need to invest in high levels of redundancy in their infrastructure.

Developing leaders for managing AI-driven businesses

Developing leaders for managing AI-driven businesses

A long-term approach and investment is required to train the next generation of business leaders who can leverage the state of the art to make the best decisions for their customers, users, employees, stakeholders and shareholders.

To be AI-first, move beyond managing data warehouses

To be AI-first, move beyond managing data warehouses

Enterprises need to define a path to data-maturity and that requires reshaping and reorganizing their data storage, description, maintenance and value generation processes, procedures, tooling and functions.

Changing the definition of software testing in the AI era

Changing the definition of software testing in the AI era

AI-driven software requires an updated approach to software testing.

The 'A' in AI needs to be for accountability

The 'A' in AI needs to be for accountability

AI needs to be accountable.

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