Peter Koning On Data Science – Big Data Analytics

Many companies are starting to realize that the value of their business is not in the profits they earn from their business, but rather the valuable data they have about their business.

So just how does a company go about building a revenue stream from their own business data?

Most companies look to data scientists to develop models about their business, so that they can extract valuable answers to the “big data” questions they might have.

Data scientists use different algorithms and “machine learning” to create these models. However, there are several challenges with this approach as was recently outlined in this TechTarget article entitled Building predictive models more about value than glamour

•Data scientists are expensive and hard to find

•The model building takes a long time and is expensive

•The models are static and don’t easily handle new data types.

Realizing the issues get worse over time, it’s now becoming the norm for data scientists to put an expiry date on their models.

What alternative is there?

One upcoming and disruptive alternative method, is to use an AI (Artificial Intelligence) that builds the model on its own. The AI is fed different forms of data (e.g. time series sensor data from millions of devices, temperature readings, website statistics, etc.) and it determines the correlations – faster and more accurately than a human.

The advantage of this approach is that it’s much faster, more accurate, hugely scalable, and in some advanced solutions the AI can handle more data types in the future and adjust the model in real time. It simply figures it out and adjusts as needed.

Does this affect the future role of “Data Scientists”?

Not really – in fact by using advanced AI Predictive Analytics the role of the data scientist can become even more of a profit center – as a business consultant for the firm. Data Scientists will be viewed as valuable specialists even more now than in the past, as they connect the powerful AI developed models to the business data and deliver powerful answers even faster than before.

The role of data scientist is assured – in fact it will become even more critical for companies to have them on board in future, as businesses connect with an increasing amount of data over time. The data scientists that embrace the new Predictive Analytic AI engines and all the benefits they delivers have a brighter future than ever.