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Data Modeling Trends in 2019

IT technologies are rapidly changing our lives. Whether it’s your daily grocery purchase, monthly bill payments, booking railway tickets, or receiving online healthcare consultation, data technologies have penetrated every business model, large, medium, or small. Recent cloud platforms, coupled with Big Data and IoT technologies, have ushered in a new era of “smart technologies” powered […]

Data Scientist vs. Data Engineer

The Background of Data Science Roles It was thought that the year 2018 would create a huge demand-supply gap in the Data Science market as supply would fail to keep pace with the rising demand for expert Data Scientists. However, the recent buzz from Gartner, which says more than 40 percent of Data Science tasks […]

Data Science Trends in 2019

When it comes to major Data Science trends to watch in 2019, the co-founder and CEO of Kaggle, Anthony Goldbloom, has predicted that very soon Data Centers will be replaced by departmental or business-specific Data Science teams. As discussed in Data Science Trends in 2018, last year’s major trends continued from 2017 as the growth […]

Ten Myths About Data Science

Click to learn more about author Daniel Jebaraj. Introduction Data Science is now being used as a competitive weapon. As with other technologies and processes that can transform the way companies operate, there’s a lot of contradictory information about it that’s causing considerable confusion. Most of today’s business leaders have heard that Data Science can […]

The Future of NLP in Data Science

According to many market statistics, data volume is doubling every two years, but in future this time span may get further reduced. The vast portion of this data (about 79 percent) is text data. Natural Language Processing (NLP) is the sub-branch of Data Science that attempts to extract insights from “text.” Thus, NLP is assuming […]

Why Data Science is Not Statistics

Click to learn more about author Alex Paretski. Statistics as a branch of applied mathematics plays an important role in identifying hidden patterns in data. That’s why it is frequently used interchangeably with broader terms such as Data Science, Data Analytics, Business Analytics, and Machine Learning. Not only is this comparison technically incorrect, but it […]

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