The importance of AI and Analytics

No matter your line of work, access to reliable data will -- or should -- always be at the forefront.

Just look at the global pandemic we find ourselves -- hopefully -- climbing out of. Throughout the more than 12 months of this international nightmare, facts seem to change daily -- with this juxtaposition between perceived “real” and “fake” news. Facts should never change. The best way to ensure your facts are accurate is by using data you can trust. As the adage goes, numbers never lie. 

Advancements in data analytics, powered by artificial intelligence (AI), have helped utilize data more effectively during the pandemic.

AI utilizes data impartially. No agenda whatsoever. It’s been a pivotal part in analyzing COVID-19 data and continues to help the medical field make advancements in all areas.  Baidu Research’s open-source AI platform reduced the time needed to study COVID-19’s RNA sequence, enabling a deeper understanding of the virus that is necessary for vaccine creation.

AI had also helped scientists comb through the large amounts of data coming in at once. This helps isolate the most prevalent information quicker to help build effective therapies and treatments. AI helped in contact tracing, including China monitoring movements and identifying possible contacts of infected individuals to mitigate the virus’s spread.

But what good are analytics if you don’t keep up with them?

AI relies heavily on analytics, which isn’t stagnant. The need for current data goes beyond global pandemics.  A thorough but rapid study of the latest data can lead to the best decisions. This leads to the most updated real-time analytics.

Real-time analytics is necessary to analyze all network interactions in real-time and apply advanced machine learning to help your teams detect threats, ensure delivery of critical applications, and protect your cloud. 

But numbers by themselves won’t tell you the whole story. You need a team around you to analyze these numbers, figure out exactly what they mean, which are useful and nonsense, and how to act upon them.

Have you turned on the power of AI for your data yet?