Algorithm & Analytics driving digital economy

Algorithm and Analytics – What you should know?

In today’s digital economy business – many should have noticed that most of the billion dollar companies have made platforms that allow the B2B and B2C segments to perform their need using ‘algorithms‘ and ‘analytics‘. It also has variety of terms that are interconnected such as ‘IoT’, ‘Big Data’, M2M’ and so on.

While I started exploring its importance in digital economy – Its too late for me; haven’t said that its worth sharing here for all of you (who doesn’t aware of). Here are few insights on how the legacy business model of respective industry segment has been distrubted by ‘Algorithm & Analytics’

  • The Chinese government has contracted China Electronics Technology Group to develop technology, similar to that used (big data surveillance) in the sci-fi thriller “Minority Report,” that can predict acts of terrorism before they occur based on large amounts surveillance data. Click here to read more
  • Amazon’s recommendation engine and Google’s PageRank as a couple of the many examples of the spectrum of transformative business models — and competitive differentiation — that algorithms have made possible. CIOs need to take note of a future where algorithmic business goes autonomous. Click here to read more
  • Scaling your business in an Algorithmic economy – Traditional industries have been using algorithms for decades. The difference now has been in the huge quantum of unstructured data continuously generated by the H2M and M2M interconnections that need a machine learning algorithm. Click here to read more
  • StreetScore is an algorithm that assigns a score to a street view based on how safe it looks to a human — but using a computer that algorithms to quantify urban perception can help us study crime patterns, gentrification and other phenomena of interest for urban economists, urban planners and architects.Click here to read more
  • The power of advanced audit analytics – Leading academics in accounting, for example, have argued that audits should be a continuous rather than annual process. Analytics, artificial intelligence, and direct linkages to transaction systems will allow audit processes to uncover anomalies in real time, all the time. Click here to read more
  • Banking industry drives algorithm analyzes, models, and predicts the stock market. The algorithm is based on Artificial Intelligence (AI) and Machine Learning (ML), and incorporates elements of Artificial Neural Networks and Genetic Algorithms. Ref 1, Ref 2
  • Programs that helps Hollywood studios to identify, enhance and deliver on-screen success, and guides investors in the creation of winning film investments –  with the selection and development of scripts by identifying likely successes and probable ‘Turkeys‘. Ref 3
  • Traditional solutions, which continue to fall short in detecting and stopping threats, can be enhanced with big data analytics.
  • Big data analytics + security technologies = stronger cyber defense posture‘.Ref 4, Ref 5
  • Telcos will need advanced data analytics to offer increased automation, predictive features, and creative use of AI and machine-learning techniques. They need to employ data analytics to create behavioral models to fully enable the services and provide customer control features. Ref 6, Ref 7, Ref 8
  • The truth about ‘Smart Cities’ is that there is only going to be one way that they can become truly ‘smart’: through data and analytics. Algorithms are also a fundamental tool for transforming big data, first into useful analytics and eventually into action. Smart cities will rely heavily on data and the algorithms. Ref 9, Ref 10, Ref 11
  • Chronic Illness Prediction and Prevention, Scoring the Quality and Efficiency of Care, On-Demand Peer Costs Comparison, Preventing Adverse Drug Reactions, Understanding the Prescribing Habits of Physicians
  • Improving Manufacturing Processes, Custom Product Design ,Better Quality Assurance, Managing Supply Chain Risk


[The End] Thanks for reading..

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