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Suppose you are working as an analyst, and your manager asks you very specific questions like “what is the current sales trend?”, “what are my customers buying?”, “is my customer buying a mobile? which is the most likely product he may buy along with it?”, “how much do we need to produce to meet the market demand?” how would you answer them? 

To answer all the questions above, one needs to start with mining data. It also helps machine learning engineers in processing the data. Keep reading to...

Power BI is recognized as one of the most in-demand skills in the domain of Data Science. It is used to visualize any data using the unified, scalable platform for self-service and enterprise business intelligence (BI) that’s easy to use and helps you gain deeper data insight. 

In this article, you will learn the following:

• The fundamentals of Power BI
• Types of visualizations in Power BI
• Features of Power BI
• Components of Power BI

Let us dive into a situation where you are driving a vehicle;...

As the amount of data generated every day increases exponentially, creating a logical, simplified database has become the need of the hour. This is why data modelling has become one of the most crucial aspects of Data Science. In this article, understand:

Businesses need data to thrive. They scrounge through petabytes of data they are surrounded by to unearth business intelligence. But not everyone in an organization is data-savvy enough to comprehend the information extracted using data. 

Data Science is one of the highest-paying jobs in the world and a top choice for professionals who make career switches. As for Shilpa Ingole, a professor with a decade-long experience, her lack of industry experience was a significant hurdle that stood in the way of her career aspirations. Despite having a Master's degree in Information and Technology, she wasn't confident about pursuing a career in Data Science.

As the name implies, data science is the area of study that investigates enormous volumes of information by using modern tools and techniques in order to find unseen patterns, derive meaningful information, and make business decisions based on that information. Predictive models are built using complex machine learning algorithms in data science. The data used for analysis can come from many different sources and be presented in a variety of formats.

Naga Lakshmi Pothuguntla, from Andhra Pradesh, had an 11-year career gap when she discovered the huge demand for Data Science professionals in India. With just 7 months of experience as a Junior Software Engineer, this mother of two had several challenges to tackle before she could become a Data Science professional.

Data is becoming increasingly crucial for making critical business decisions. All types of businesses use data to determine which new products to create, which markets to enter, which investments to make, and which potential clients to pursue. 

Engineers, for sure, make a unique breed. Their consequential acts of leveraging the rules of our world to build things that nature readily didn't give us are what led to the advancement of humankind in the first place. Due to the very same reason, the field of engineering is never going out of demand. 

Dr. Drakshayani Desai had more than a decade of experience as a research guide when she stumbled upon an unexpected career impasse. With a Ph.D. in Image Processing and extensive experience as a professor, she had established a very successful career in academia. But, to keep up with the rapidly-changing demands of the industry, she made an ever-so-daunting decision to switch to a career in Data Science in her forties. And so she did. Drakshayani is currently employed at Prolifics, a leading...