SAS for Beginners: Riding High on the Analytics and Data Science Wave

SAS for Beginners is Stepping Stone to Analytics

What began as a random study on the agricultural field in the US has now become one of the foundational courses for the most powerful data science projects in India. Training in SAS analytics is a key skill for leading projects in banking, finance, pharmaceutical and IoT industries. If you are still waiting for confirmation on why certification in SAS course is a must-have for 2019, continue reading this…

SAS for Beginners is Stepping Stone to Analytics

Believe it when we say that SAS has provided close to 100,000 or more certifications since the program was launched in 1999. Since then, SAS courses in Bangalore and other metro cities in India have trained close to a lakh graduates and professionals in five specialized categories.

These categories are:

Most data scientists surfing the wave of AI and data science would attribute their success to their initial work in SAS as beginners.

What would you learn as a SAS beginner?

A certified SAS foundational course would train professionals in business analysis, visual exploration, data modeling and data analytics leveraged by leading BI and Market Research companies, including those consulting IT and technology integration vendors.

In the initial phase, a SAS developer and analyst would be enshrined to work with complex data for analysis and reporting. Post training, SAS professionals would extensively work with platform architecture and analytics governing algorithms as well as create Metadata for Discovery, Management and Statistics.

Benefits of SAS course for Beginners

The benefits of learning SAS course in Bangalore far outweigh the initial investment you make. Certified professionals would agree about the benefits (as listed below) have completely transformed their career path in AI and Data science.

The benefits include –

  • Gaining valuable insights into business growth and predictive analytics for market competitiveness
  • Resolving urgent business risks and mitigating future challenges
  • Future-proofing Data Management with data governance and compliance standards
  • Forecasting Project Management outcomes

Enterprise Management: The Digital Transformation

Two things hampering the adoption of Enterprise Management platform are – Lack of SAS expertise, and high administrative costs. This directly impacts the adoption of Data Science and AI for enterprise applications.

Automated workflows and data forensics are growing at a rampaging pace in a centralized infrastructure. SAS trained professionals could certainly pave way for secured applications in statistics based on detailed documentation of investigations at reduced administrative costs.

As the era of Big Data commerce matures further, data analysts would advise – “Buddy, sort your priorities in SAS intelligence tools for 2020, now!”