The past few years have seen Data Science and Big Data moving forward dramatically. While Big Data may not technically be a technology it is going to be a massive disruptor. The entire Business world has been transformed and will continue to be so in the upcoming years in which Humanized Big data is just a part of it.The trends Internet of things (IoT) and industry 4.0 bring intelligence to components and everyday appliances, resulting in a flood of data that is increasing exponentially. For instance in today’s production environment, technically advanced machines are already continuously sending data about the current status and sending alerts when maintenance is required. Big data’s greatest strength, however the quantitative foundation is also its greatest weakness. It is difficult to derive concrete action guidelines or actionable meaning from an analysis of current solutions, if the point is to make business decisions based on the collected data. Hence this requires an approach that is more qualitative than quantitative, as well as high degree of visualization of data.
Can and Should Big Data be humanized?
At the core of things, humanizing big data seems like something that would be the opposite of productive and certainly counterintuitive. The reality is that big data must start and end with humanity. Because people are the source of big data, they must also be heavily involved in the processing and the interpretation ideas flow through social networks, what motivates people to contribute to discussions, and the consequences of engagement. The reality is that you cannot isolate data from the motivational source. Essentially what we are seeing that new elements of behavior are affecting information, for example, governmental issues, opinions and agents communicating with and impacting each other. So in addition to looking at data in the conventional way, we must now consider political and social structures, and how individuals gain from and impact each other; we should consider how ideas flow hrough social networks, what spurs individuals to discussions, and the consequences of engagementWhen that happens no matter how perfect the machine, the Big data is typically interpreted incorrectly.
Is the Humanization of Big Data Our Greatest Challenge or Our Greatest Opportunity?
The answer is probably both. The biggest goal of the humanization of big data is to put the spotlight on the factor that is most important to business and industry. That factor is the customer or the potential customer of the business. The application of humanized big data means changing the way in which our data scientists do their job or the way in which we interpret our data.We are seeing massive floods of data arriving every day from political, business and other avenues. Industry 4.0 and IoT brings with it intelligence that can be used to help humanity in many ways.
Humanizing Big Data can give us a way to get solid plans of action or to take meaning that becomes actionable from the data that we have been given.
The Big Data that we are being given can help us to arrive at new answers and new ways of making life better for people. It may be one of the biggest disruptors, but only if we interpret it using a human touch. Humanizing Big data makes it accessible for analysts who operate in today’s enterprise business units. It’s rendering data into information that is easily accessible and highly relevant. It’s making analysis based on Big data effortless and natural. Instead of relying on Specialized skills in programming and Statistics, Data can be humanized by adding appropriate context and offering straight forward tools for building analytical applications.
The present time is a very special time in the history of social science because we are witnessing a dramatic transformation in our ability to observe and understand human behavior. Customer interaction is moving from physical to digital. More of our lives played out online, revealing more about ourselves. Opportunity lies in exploring the human characteristics that can be derived from corporate data.
Increasing number of studies demonstrating linkages to our inner landscapes:
- Likes can predict wide range of personality and demographic attributes.
- Musical tastes reflect thinking styles: ‘empathizer’ who likes to focus on and respond to the emotions of others, ‘systemizer’ who likes to analyze rules and patterns in the world.
- Smartphone usage can detect bi-polar disorder: Hyperactivity measured by an accelerometer, and GPS, Rapid speech monitored by speech analysis, Frequent conversations monitored through phone records.
Are we heading in a direction where it is less about engagement and more about ‘nudging’?
Data imbalances can mean that brands know:
• Your propensity to pay more
• What behavioral nudges you are susceptible to
• How should we use that information?
Analytics is a human endeavor : Companies need to invest in understanding this to really generate value from their data assets.Many have articulated that we are currently in the ‘trough of disillusionment’ around Big Data, the buildup around it having surpassed the truth of what it can deliver. To make it out of this trough, I believe we need to start engaging with a new agenda, which is a much more human-centered approach. If brands can ‘humanize big data’ then they have the opportunity to grow in a way that offers long-term, sustainable differentiation rather than the potentially shorter-term, replicable benefits created by access to data and technology alone.
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