Data Value Gap – Data Observability and Data Fabric – Missing Piece of AI/AIOps

Some key challenges faced by CXOs & Enterprise leaders are –

  1. Predict and prevent service outages
  2. Predict and prevent security breaches
  3. Offer self-service Analytics and automate appropriate parts of IT

A pivotal inhibitor to mitigate these challenges is the Data Value Gap

Data automation and Data Fabric are emerging as key technologies to overcome these challenges. Learn from industry experts about these key technologies and how they create a lasting impact in enterprise IT.

A Globally Trusted Panel

Sean McDermott, CEO of Windward Consulting Group

Sean McDermott is a serial entrepreneur with 35+ years of experience in IT. A recognized voice in IT Operations Management, IT Service Management and AIOps, Sean is a member of the Forbes Tech Council and can be seen on Entrepreneur, InformationWeek, TechTarget and DevPro Journal.

Joe McKendrick, Principal, The Field CTO

Joe McKendrick is an author, an independent researcher and speaker exploring innovation, information technology trends and markets. Joe is a contributor and analyst for Forbes, CBS Interactive, Information Today, Inc. and RTInsights, among many others and was listed as one of 10 “key opinion leaders” in “Who’s Who in Digital Experience,” Onalytica, February 2021.

Jen Stirrup, CEO & Founder, Data Relish

Jennifer Stirrup is a #1 best-selling Amazon author and a recognized leading authority in AI and Business Intelligence Leadership, a Fortune 100 global speaker and has been named as one of the Top 50 Global Data Visionaries and one of the Top Data Scientists to follow on Twitter, and one of the most influential Top 50 Women in Technology worldwide.

The value proposition of AIOps post-COVID for enterprises:

  • Digital Transformation
  • Predictability
  • Cost Efficiencies
  • Decision-making

Data is to AIOps what Location is to Real Estate. How do you harness the Data?

Top Data Management Challenges that keep companies stuck:

  • Source of Data
  • Access to Data
  • Data Accuracy
  • Talent Gap

Your Preferred Approach to the IT Data Problem

  • Understand the tangible and intangible use case that drives your AIOps strategy
  • Develop a vision to garner organizational support and buy-in
  • Explore Data Pipeline Automation for quicker deployment
  • Leverage No/Low Code solutions to address the skills gap

Have we Finally Seen the Arrival of the Autonomous Enterprise?

How AI can be supercharged to bring the vision of the Autonomous Enterprise to reality?

Intelligent Data Supply Chain – How it can make your job easier and more rewarding?

Every enterprise wants to become digital and is looking to IT to deliver on that.

Why IT is under pressure

  • Service outages
  • Security breaches
  • Capacity issues

IT is expected to provide

  • Support for IoT and Operational Technology (OT)
  • Self-service options
  • Automation, org-wide
  • Superior customer experience
  • Superior user experience

The Problem with Data that Goes into AIOps

  • Silos and more silos
  • Data from disparate sources
  • IT Ops Data is messy
  • Many Data formats
  • Diverse Data platforms
  • Low-quality Data
  • Lack of Data management skills

The Data Value Gap that Goes With AIOps

  • Time spent loading and scrubbing Data
  • Scarce Data-quality efforts
  • Manual tasks compromise competitiveness
  • Low trust in own Data

An Intelligent Data Supply Chain is Critical

Only 16% of enterprises have them. “Data supply chains are a better way to source high-quality data. They build on the process and supplier management techniques.” – Tom Davenport.

Robotic Data Automation Fabric- The Solution

  • Automate Data Integration and preparation activities involved in dealing with Machine Data for Analytics and AI applications. 
  • Faster time-to-market
  • Quick time-to-ROI and time-to-insights
  • Reduce costs
  • Scale easily as an enterprise grows
  • Boost DevOps and ML pipeline observability
  • Use easy-to-build bots

Essential Components of the Intelligent Data Supply Chain

  • Data Intelligence
  • Data Automation
  • Data Integration

Unraveling the Buzzwords: Build a Good Foundation for Analytical Success

Learn clearly about the famous buzzwords in the realm of AIOps and technology. Move away from a hyped-up version of these technologies and learn about their real significance to organizations and enterprises today.

  • Data Fabric
  • Data Mesh
  • Data Lake and Data Puddles
  • RDA and Last-mile problem
  • The First-mile problem of AI
  • AIOps is a DataOps problem
Shailesh Manjrekar
Shailesh Manjrekar
Shailesh Manjrekar, Chief Marketing Officer is responsible for CloudFabrix's AI and SaaS Product thought leadership, Marketing, and Go To Market strategy for Data Observability and AIOps market. Shailesh Manjrekar is a seasoned IT professional who has over two decades of experience in building and managing emerging global businesses. He brings an established background in providing effective product and solutions marketing, product management, and strategic alliances spanning AI and Deep Learning, FinTech, Lifesciences SaaS solutions. Manjrekar is an avid speaker at AI conferences like NVIDIA GTC and Storage Developer Conference and is also a Forbes Technology Council contributor since 2020, an invitation only organization of leading CxO's and Technology Executives.