We Google, We Facebook, and now we also Uber and Snap! How did these platforms become common nouns! Looking beyond the obvious, we would understand that the power is in the name: Big Data and Analytics.
We leave tons of data behind for analysts to understand and project what our online behavior might look like in the future at times of Holiday Shopping, Sales and other unique behavioral insights. The idea of having a Big Data analytics team is not new. Since the 60s, companies focused on driving advantage in their favor by hiring the top talent who could crack codes, and write new algorithms for better analytics, and developed AI ML engineered models for smart technologies that measure behaviors.
Here are some essential tips to understand the real Big Data Analytics approach and how it helps trainers to accomplish complex results.
Are you a Business Analyst or a Data Science Engineer?
Data Science is the foundation on which both Business Analytics and Big Data Analytics are built on.
Big Data Analytics is a subset or sub-specialization within Business Intelligence groups. A team of data analysts could be reporting to the Project Manager or Chief Data Officer at an enterprise level. Big Data Analysts feed simplified data outcomes to BI teams so that they can make accurate decisions in a minimum amount of time.
Automation Learning
The life of an analyst is 90% easier than what it was during the early part of the 2000s! Reason: There are countless automated business analytics and Big Data analytics platform that can quickly generate results and also do A/B testing in hours, if not minutes!
From finding latent relationships between the various factors to leveraging AI and Machine Learning algorithms, automated Big Data Analytics training can collect, analyze, and deliver real-time data insights that everyone on your team can see and verify for their results.
How to Succeed in Business Analytics using Big Data Training?
I often refer to an abbreviation created to explain the Big Data Analytics Training goals. I tell this to every professional I meet during the online sessions.
This is what it sounds like:
A.I.M.S.
“A” refers to Aspirations (Your end goal)
“I” refers to Imagination (ability to find creative solutions to complex problems)
“M” refers to Management (Some level of management skills go a long distance when it comes to getting that top job with a multinational big data or IT-based company)
“S” refers to statistical understanding and hard coding skills
Of all the above-average Big Data analysts that I have met, almost 90 percent of them had a hard skill advantage. They were either part of online coding forums or were part of DevOps teams that worked extensively on Big Data supporting programming languages such as R, Python, and Java.
So, I would rephrase the “AIMS’ to AIMS-Code.
Isn’t it easy now to fix the priorities before you join any training course online!
