Blog Outlet: Data Science Central
Blog Title: Top 3 Trends in Big Data Analytics
Author: Dr. Athanasios Gentimis
The presence of big data analytics and students who are pursuing big data analytics degrees has grown exponentially with the emergence of digital technology and advancing high-tech fields. With the incredible amount of data that is created and stored on a daily basis, the data field helps researchers and individuals identify patterns, correlations and trends to help businesses and society make informative decisions that impact our day-to-day lives.
Over the past decade within the field of big data analytics, several trends have emerged. The top three are outlined below.
- Eliminating Statistical Techniques
Statistical techniques are not working anymore. We are moving away from averaging sets of data. Instead, clustering and trend analysis have moved to the forefront and are currently used universally within the field of data science.
- Advancements in Technical Analysis
Back in the day, researchers conducted polls to collect data. Nowadays, there are social media analysis functions. It is quite easy to plug data sets into fields and download the analysis for free. You can teach a computer to even perform certain outputs automatically.
- Topological Data Analysis
This type of analysis is able to determine if the data is repeating or if there are any clusters or algorithms present. Currently, faculty at Florida Polytechnic University are conducting research where we are finding trend analyses in stock markets. The goal is to model a case to determine when stocks change based on how volatile and how frequently they change.
Big data analytics continues to advance, and many trends are currently being evaluated, tested and introduced into the business world. As the field continues to grow, data scientists will continue to use their expertise, entrepreneurial thinking and innovation to spur scientific breakthroughs and develop models to predict behaviors, trends and outcomes.