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manavpietro 36, Male, New York, USA - 63 entries

Jan 2017
1:21 AM IST

BIG DATA TO REVOLUTIONIZE PHARMACEUTICAL INDUSTRY

From patient information to research records, pharmaceutical industries has long been involved in data collection and data analysis in order to deliver better services. However, the era of big data analytics has resulted in explosion of data in terms of volume, variety and veracity. The process of data collection and data analysis has become simpler now. The actual process of analysis is followed by integration of data to transforming and then cleansing it.

The big data opportunity promises to transform the way industries work, especially those that generate massive amount of data. In pharmaceutical industries, data is generated from myriad sources including patients, R&D, caregivers, and retailers among others. Effective use of big data will help this industry in discovering a new drug and later developing it into approved and effective medicines in a shorter period of time. While some of the drug discovery firms like Numedii and GlaxoSmithKline have already started leveraging big data analytics, some of them are in the early stages of using it. In order to deliver and develop the successful treatment of the next generation while addressing the issues related to managing and processing data, big pharma should start looking for the ways to maximize its value.

Tags: analytics, Big Data, Big Data and Analytics, Big Data IQ, pharmaceutical industries

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1 comment(s) - 11:45 PM - 02/13/2017

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divyanshikulkarni 22, Female, India - 23 entries

Aug 2024
8:42 AM IST

Learn Data Science, Big Data, and Data Analytics Concepts and Applications

Are you confused about the difference between data science, big data, and data analytics? Then USDSI� brings a detailed guide explaining their intricate differences, roles, and importance in the world of data science.

Now all organizations, whether they are start-ups or already established, are actively adopting data science technology into their business to boost their productivity and stay ahead of their competition. This has led to an increase in the data science market size which is expected to reach around $322.9 billion by 2026, as predicted by Markets and Markets.

This means, the demand for skilled data science professionals is also going to increase. If you are looking to make a career in data science, then it is important to learn the difference between these three big data science terms.

In a nutshell, here’s how they differ:

Data science: it is the process or technology that encompasses various tasks and processes required to convert raw data into actionable insights and build efficient data models to solve business problems.
Big data: Big data refers to the huge amounts of data that act as the fuel for data science models. These data can be in petabytes or zettabytes
�Data analytics: it is the process of all the statistical and mathematical processing required to identify trends and patterns within the data.

If you find these basic differences useful, you may be interested to learn the complete roles, applications, and tools used in these processes.

So, download your copy of this detailed guide, and enhances your understanding of these data science terms.

Tags: Big Data

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