In the last few blogs, we saw how to summarise and analyse the data using statistical methods and visualisations. But the raw data need to be processed to convert it into a usable shape. Data Preparation is the most important and foremost part of Data Science. It involves data pre-processing and data wrangling. Raw data […]
In our last article, we discussed the evolving future of Artificial Intelligence and Data Science; and that the fields are expanding across all the industries be it pharmaceuticals, agriculture, banking, manufacturing, logistics and so on. In this article, we will talk about the various job roles in data science and how to kick start […]
No one has the ability to capture and analyze data from the future. However, there is a way to predict the future using data from the past. It’s called predictive analytics, and organizations do it every day. In this blog post, I’ll be taking a look at predictive analytics, starting with what it is and how […]
You cannot play tennis without a tennis racquet, or soccer without a football. Data science is a sport too, and you cannot play it without the right set of the tools. I’m going to give you a go-to collection of the most commonly used data science software/ tools. They are intuitive, effective, powerful, and — […]
If you are new to data science or to the big data industry, understanding complex jargon that dominates the industry can be difficult and overwhelming. With words like predictive analytics, machine learning, data munging and acronyms like IOT thrown casually in conversations, it’s easy to feel left out. Have no fear, most commonly used data […]
If you are new to Hadoop & Big Data you must be wondering what the various Hadoop job roles entail, which one you would be most suitable for and what do you need to do to get one of those jobs. Datameer’s has predicted the global Hadoop market to be $50.2 billion by 2020. Source: […]
Many people have this doubt, what’s the difference between statistics and machine learning? Is there something like machine learning vs. statistics? From a traditional data analytics standpoint, the answer to the above question is simple. Machine Learning is an algorithm that can learn from data without relying on rules-based programming. Statistical modeling is a formalization of […]
R is probably every data scientist’s preferred programming language (besides Python and SAS) to build prototypes, visualize data, or run analyses on data sets. There are so many libraries, applications and techniques exist to explore data in R that I’m sure even experts don’t know them all! Aspiring data scientists who are reading this though, […]
Nearly 30 years ago, when Sam Walton‘s Retail Link gathered consumer info using product bar codes, the big data pronounced its advancement in the digital world. Now when Walmart, Amazon, Facebook, and Twitter are all relying on data aggregation and analysis to uplift their business strategies, we know that big data has a lot of […]
The success of our students in their careers is what matters the most to us and when our students land their dream job, their success becomes our success. One amongst many such moments came when our student Sashikant Dwivedi (Linkedin profile) got his dream analytics job at TCS as a Sr. Analyst (Risk Analytics-Mortgage) and sent […]
