Why Has the Data and Analytics Field Taken Off Recently and What Is in the Future for It?

By Eric Dougherty

English: Scientific visualization of an extremely large simulation of a Rayleigh–Taylor instability problem. This image was generated by the VisIt Visualization System. Creative Commons license: https://commons.wikimedia.org/wiki/File:Rayleigh-Taylor_instability.jpg

The data and analytics field has taken off recently due to a surge in technological advancements, rapid growth in data generation, and the recognition that data holds strategic value for organizations. Furthermore, the intersections of these factors lead to a future of both ethical and operational considerations when collecting, storing, analyzing, and implementing data.

One primary factor for the growth in the data analytics field is the massive influx of data volume. Where structured data, in the form of rows and columns, was an easy to interpret set of raw information with limited ranges and models for analysis; now, unstructured data, as exemplified by images and sensor data, leads to various interpretive and analytical opportunities. Business and technological advancements have also led to a large influx of data through means of social media, streaming services, and other online interactions. Within this large amount of data lie valuable insights that can inform efficiency, strategic design, and innovation. However, it is not enough to just collect this data. Storage capabilities must, in turn, also grow alongside large data quantities.

Advancements in technology such as processing capabilities, cloud computing, and machine learning algorithms have equally contributed to the potential of data analytics. Storing data on cloud has allowed paths to process unstructured data in ways that were not possible with data warehouse technology due to higher storage and processing potential. The growing sophistication of artificial intelligence has also changed the field of data analytics in terms of automation, accuracy, and access. As AI feeds into machine learning which also feeds into deep learning, the awareness of how these technologies are utilized and the ethics therein require a growing demand for attention, discussion, and action.

The future of data and analytics will inevitably grow and expand. With an increasing emphasis on streamlined and automated processes, as well as demands to make more informed real-time decisions, the field of data analysis is faced with equal parts excitement, interest, and trepidation. Standards of reliable, representative data must be balanced with privacy and security—all the while the locomotive of information streaming continues to accelerate at an unprecedented rate.

Eric Dougherty is Alumni/ae Editor of Action Academe.