Big Data, Machine Learning and AI: Trends and Predictions

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BigData

FountainBlue’s February 2 VIP roundtable was on the topic of ‘Big Data, Machine Learning and AI: Trends and Predictions’. Please join me in thanking our participating executives and our gracious hosts at Nutanix.

Our executives in attendance represented a range of roles and companies, all with a perspective on how the data, the applications, the solutions, the challenges are impacting our companies and our day-to-day lives. Below is a compilation of ideas and thoughts from our conversation.

We began with the ideal qualities of Big Data: 

Velocity (how quickly the data is moving), 

Virality (how quickly the solutions are adopted and spread), 

Volume (the sheer quantity of data) and 

Veracity (the truth provided by the data).

With the advancement of infrastructures and systems, and with machines and solutions becoming quickly more versatile, more useful, more relevant, companies, leaders, industries are all adopting a wide range of solutions, which benefit everyone across the ecosystem – internal and external to the individual, team, company, geography and industry.

‘Wow’ was the collective response when we heard the wide-ranging use-cases around big data – scenarios which affect ourselves directly and indirectly, scenarios which makes us dream bigger, yet also be more wary about our safety, our privacy, our security, our future.

If machine learning can now help us see trends faster and better than the typical evolved and trained human, then it’s up to us to manage and design solutions to better serve every one of us. We mentioned a few times our concerns about the ethical and human elements surrounding the data – to help ensure that we apply it for the betterment of humankind, our environment, our ecosystem.

The advice and suggestions collectively as a group are summarized below.

  • Choose open source as a foundation for growing solutions and offerings to target markets. Actively participate in the open source community to give back, to influence the direction, to expand and create collaborative networks.
  • There’s value in the data, and winning companies will learn how to monetize on it, while also respecting the privacy and rights of the individuals who own the data.
    • Not all data is treated equal, so categorizing into data types will help build a standard and help respect the privacy of the users, the intentions of the solutions.
  • In this digital economy, data is the currency. Ensure Access, Security, Reliability, Speed, Versatility, Accuracy, etc., of same. This is not an easy task with the 4 Vs of data highlighted above.
  • Privacy, Security and Access will be consistent challenges and themes. 
  • A focus on customers and their demands for personalized access to data real-time provides a challenge and an opportunity in all industry sectors.
  • Heavily-regulated industries including healthcare and finance provide specific niche opportunities around the data due to the regulations and policies and lack of standards for the industries.

Highlighted opportunities and challenges are listed below.

  • There will be a battle around standardization, data location – Edge vs 5G for example, 
  • Balancing privacy, security and access
  • Selling your own usage data
  • Leveraging automation and robotics to better perform – more precision, more dexterity, less tremor, better access, use lighting and imaging
  • Leveraging data for diagnostics will add value across industries
  • Analyze trends to better predict and serve customers, to more strategic invest in ideas and companies
  • Understanding usage, sentiments, trends and tendencies is a huge opportunity and will only get bigger. 
  • With successful understanding of a broader range and larger volume of data real-time, there are opportunities to decrease churn, increase revenues, increase positive resolutions, increase Net Promoter scores, increase customer loyalty and referrals, etc.,

But the human will also be necessary.

  • As a sanity check for the data.
  • To program the HW/SW solutions and identify what’s relevant, what’s actionable, what’s valuable.
  • To provide feedback and intelligent guidance to automated scripts.
  • See beyond the data and its implications to imagine or extrapolate a trend or idea.

The bottom line is that Data and Content are in charge and affecting each of us across roles, industries, geographies and scenarios and collaboration is key. Energy and technology will help ensure the safe, secure real-time access to data which is actionable. Everything will be different, and yet the same, perhaps at a different scale.

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