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Data Cleaning – the secret ingredient to the success of any Data Science Project

how to become a data scientist

  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 […]

Predictive analytics explained in simple terms

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 […]

Programming languages in Data Science

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 — […]

jargon free

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 […]

hadoop

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: […]

Machine Learning vs Statistics

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 […]

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