Agile Data & DataOps

  • Forbes predicted a 50% increase in Predictive Analytics software applications by 2018, to nearly 3.5 bill $.  
  • Also, worldwide spending on Big Data and Predictive Analytics was expected to have grown at a rate of 30% by the end of 2018, reaching the 120 bill $.

Adjuvant Technologies

There are strong reasons why Credit Unions should pool data:

  • If a data scientist works on a pool data including 50 Credit Unions, these Unions get to split the cost of the data scientist, making Advanced Analytics more affordable.
    • It is important to use the pool to maximum advantage in learning aspects of the business that are common, such as economic sensitivities…
    • But also to calibrate the individual aspects of the business…
    • So that you get the benefit of the whole, and also that which is specific to the individual institution.
    • It would be beneficial for Credit Unions to have access to this data before it is 4-5 months old.
  • Lentiq is combining the concept of the Data Lake with that of Edge Computing to create what it calls interconnected micro Data Lakes”.
  • The goal is to allow as many users as possible inside an organization to access data, and to create an environment where they can perform Analytics and Machine Learning in a friendly manner.
  • Transformative innovation will only be achieved through a human-centric Machine Learning approach for all data projects.

New technologies will enable and extend Digital Transformation projects at the Edge. And this is only the beginning. Two examples:

  • 5G will be a huge game changer, as it enables new levels of connectivity and computing in economic activities such as:
    • Alternative energies.
    • Oil pipelines.
    • Transportation. 
  • Private wireless networks will move to 5G with Edge implementation, in the next 3-5 years…
    • Depending on other elements of Edge ecosystems evolving at the same time.

Automation & AI

  • Top AI and Analytics Trends for 2019:

    • Use of advanced computing algorithms to identify and optimize business insights humans cannot spot.
    • AI will deliver 2 trill $ in business value worldwide over the next year (Spain’s GDP in 2019 is 1.4 trill $, that of Italy is 2.1 trill $).
    • China is on the verge of becoming a global leader in AI research:  
      • PwC predicts that China will see its GDP boosted by 26% between now and 2030, by implementing AI in its domestic industry.  
      • If current trends continue, China will overcome Europe to become the world’s biggest AI researcher worldwide, over the next four years.
  •   Data-driven approaches, when combined with a deeper insight into clinical workflow, have the potential to reduce charting burden and cost of excessive testing, improving situational awareness and outcomes.
  • University of Pennsylvania Health System’s Senior Data Scientist Corey Chivers: Machine Learning, Artificial Intelligence and statistical modeling with large amounts of data can help clinicians make better decisions, improving patient outcomes.
  • Using a “reward function”, the team’s algorithm learnt how informative the test was at a given time.
  • Using the algorithm could have reduced the number of lab test orders by 44% in the case of white blood cell tests.
  • This also could help inform clinicians to intervene hours sooner when a patient’s condition began to deteriorate.
  • Natural Language Processing (NLP) & Analytics would be a natural fit for Business Intelligence (BI) vendors already geared to use natural language querying and audio or video data mining.
    • According to MarketsandMarkets Research, NLP & Analytics will be a billion dollar industry by 2020.  
    • NLP & Analytics can be extended beyond the call center, so that even more data can be collected and mined.