If you are interested in pursuing a graduate-level degree in data science or business analytics, it’s beneficial to be aware of emerging big data trends.
For those working in data science and business analytics, demonstrate value is a key phrase to pay attention to. Almost all expert predictions for emerging trends in big data revolve around this idea. Data collection is becoming a core necessity for successful companies, and it’s extracting value that is driving current discussions.
The Emergence of the Chief Digital Officer
The chief digital officer (CDO) is an emerging career that is rapidly taking on significant importance. A CDO focuses on extracting value from data, moving beyond the technical areas of collection into deeper analysis. While job duties of a CDO vary by company, they’re often tasked with developing strategies that emphasize the leveraging of technology and data to improve business performance.
Artificial Intelligence and Business
A report from Forrester aimed at chief information officers warned that 2018 marks the point that organizations realize artificial intelligence and machine learning are not “plug-in panaceas.” Instead, like big data and cloud computing, they require challenging contributions from software engineers, data scientists, and professionals in business analytics to work in a way that has tangible advantages for businesses. AI capabilities soon to be trending with companies include smart recommendations on everything from contracts to business decisions, strategy, and direction.
Conversational Replaces Point-and-Click
In 2018 and into 2019 we are seeing more work being done to improve communication between machines and people. This is an important part of the 4th Industrial Revolution. The Forrester report found that about 25% of businesses surveyed want to replace traditional point-and-click interfaces with software that allows people to query data using language. Look for this big data trend to become standard procedure in the coming years.
Data Lakes Need to Prove Value
Early adopters of data collection have, in many cases, massive data lakes of unstructured data. The promise was to have a silo-busting data management system that could be used by everyone to identify and act upon trends and potential new efficiencies found in data analysis.
In reality, it hasn’t always worked that way.
With older, unstructured data, it’s been difficult to extract ideas that are useful for boosting an organization’s bottom line. There is promise in AI “deep learning” to uncover value in this unstructured data, but many companies face a decision on whether maintaining vast data lakes remains viable. It’s one major reason why you’ll be hearing a lot about demonstrating the value of data collection in the coming years.