New Year’s resolutions aren’t just for losing weight and building your savings account. Here are some dreams for big data in 2021.

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SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningLast year was … interesting. While we couldn’t have predicted all that 2020 threw at us (and it was a lot), that won’t stop us from trying again this year, especially in technology.

Big data, like all technology, is evolving, so every year brings new opportunities and challenges. 

1. IoT standardization

The federal government passed legislation in December 2020 that requires Internet of Things (IoT) contractors to provide IoT security that conforms to specific government guidelines. This will drive IoT vendors to standardize their device security, a first step toward standardizing other elements of IoT, such as the diverse set of operating systems.

Until IoT device makers and solution providers attain standardization, it will be difficult for their customer companies to achieve full integration in their IoT networks.

2. Stronger business use cases

There are many guides available that describe how to develop a business use case, but what if you can’t find a good business use case to begin with?

Use cases for big data have to do two things:

  • They have to define a specific business problem that was unsolvable before, but that could be solvable and deliver benefits if big data and analytics can solve the problem.
  • The use case has to return measurable and tangible value.

3. Purposeful digital transformation

We are still at a point where too many organizations consider digitalization a success once they have digitalized information and stored it. But until you actively start integrating and using these new troves of digital assets with other enterprise IT, you’re not delivering enough benefit to the business from your digitalization. 

In 2021, it will be important for organizations to begin leveraging their digital data by integrating and using it with other corporate systems.

4. More customer sensitivity

Using big data and analytics to predict customer preferences and then pitching products to customers has been a resounding success in retail and other industries. But when do customers reach a point where enough is enough?

There are some signs now that customers want to feel that they have some privacy as well as preemptive outreach from companies in the form of emails, text messages, phone calls, and web pitches.

2021 is the year when companies should begin to determine the sweet spot for welcome recommendations and responses to customers without crossing the line into personal privacy. […]

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