Course Overview

Data analytics is important because it helps businesses optimize their performances. Implementing it into the business model means companies can help reduce costs by identifying more efficient ways of doing business and by storing large amounts of data.

The applications of data analytics are broad. Analyzing big data can optimize efficiency in many different industries. Improving performance enables businesses to succeed in an increasingly competitive world.

One of the earliest adopters is the financial sector. Data analytics has an important role in the banking and finance industries, used to predict market trends and assess risk. Credit scores are an example of data analytics that affects everyone. These scores use many data points to determine lending risk. Data analytics is also used to detect and prevent fraud to improve efficiency and reduce risk for financial institutions.

The use of data analytics goes beyond maximizing profits and ROI, however. Data analytics can provide critical information for healthcare (health informatics), crime prevention, and environmental protection. These applications of data analytics use these techniques to improve our world.

Though statistics and data analysis have always been used in scientific research, advanced analytic techniques and big data allow for many new insights. These techniques can find trends in complex systems. Researchers are currently using machine learning to protect wildlife.

The use of data analytics in healthcare is already widespread. Predicting patient outcomes, efficiently allocating funding, and improving diagnostic techniques are just a few examples of how data analytics is revolutionizing healthcare. The pharmaceutical industry is also being revolutionized by machine learning. Drug discovery is a complex task with many variables. Machine learning can greatly improve drug discovery. Pharmaceutical companies also use data analytics to understand the market for drugs and predict their sales.

The Internet of things (IoT) is a field that is used alongside machine learning. These devices provide a great opportunity for data analytics. IoT devices often contain many sensors that collect meaningful data points for their operation. Devices like the Nest thermostat track movement and temperature to regulate heating and cooling. Smart devices like this can use data to learn from and predict your behavior. This will provide advanced home automation that can adapt to the way you live.

The applications of data analytics are seemingly endless. More and more data is being collected every day — this presents new opportunities to apply data analytics to more parts of business, science, and everyday life.

What You Get Out of This Course?

• Training Portal Access for subscribed courses, which includes recorded sessions, study material, and interview preparation guidelines.
• Publicly verifiable Certificate of Completion, you can download and share the certificate link on any platform.
• Real-time practical oriented training
• Experienced and Certified Trainer.
• Advanced & Customized Curriculum.
• Course Materials Provided.
• Small Class Size with High-Quality Teaching Methods.
• Digital Profile and Resume Building Tips
• Mock Interviews with Personalized Feedback
• Communication Skills to Build Confidence
• Affordable Fees
• Flexible Timings