Why Businesses Need to Adopt Data Science & Machine Learning

Industries like Information technology, healthcare, bank, retail, airline industry and internet giants like Google, Amazon, Net Flix, Google play, Linkedin, Imdb are using data science to grow their business and to improve their operational efficiency. Data science helps you get useful information about your industry, products and customers, thus keep you ahead of your peers.

In 90’s computer science was a thing and everyone wants to be a designer or a programmer, to be a part of IT industry. But as the time went, it lost its shine, several technologies reinvent the past, but most of them did it poorly. But this is not the case with every technology.

Data science comprises everything, whether it is data cleansing, analysis, and preparation. Previously, data analysts use software like excel, but now things are changing. Moreover, excellent improvements in languages such as Python and R make analysis easy with less code.

Here are Five reasons which will help you know why industry requires data science.

1. Data is growing

Many sources have predicted the exponential growth of data by 2020 and beyond. Machine and human-generated data have experienced a 10x faster growth from 2010 to 2018 and soon the machine-generated data will grow at the rate of 50x.

1. First comes the bytes which is equal to 8 bits

2. Later the kilobytes come into light.

3. A modest update is a megabyte (1,000,000 bytes)

4. With the arrival of Gigabyte people get really thrilled.

5. But then comes the terabyte (1 000 000 000 000 bytes) which changed the way people think about storage in personal computers.

6. Now we are measuring data in Petabyte, Exabyte, and Zettabyte (1 000 000 000 000 000 000 000 bytes) and soon internet traffic will grow more than 1.3 Zettabytes.

2. Integrates data with customers programs

Industries require a unified picture of their customers, with data science you are well equipped to access your customer needs. When your data professionals have more accurate data they are able to build better predictive models.

Moreover, customer professionals don’t have knowledge of maths and stats. On the other hand, data professionals can easily make sense from the data coming from different sources such as CRM, support, and sales. They can answer important business questions which will company gaining vital insights from the data.

3. Graphs are very effective

A stream of data can be well explained with a graph. And programs like spreadsheets are making it easy to create only if the data is small enough and in the correct format. There are plenty of theories in data science that people will never need, but the way it underlines the graphs complexity and shapes the data is priceless. Different data graph science practices help you make your graphs more compelling and separates you from others.

4. Replicable output

When a web developer has to get back to project, he becomes frustrated because he has to retrace all the steps that he had used to determine the data, his own data manipulations ways and the assumptions he made to drive the output.

However, in data science, the concept of replicating data is refreshing. The tools for replication in data science are remarkable so if you are coming to your project after several weeks or month, the data science will allow getting the footprints of your project and helps you get the right speed.

5. Future-ready

Every organization wants to move ahead in the business and data science can help them to a great extent by providing the best tools and techniques in their business practices. Keeping this incredible toolkit with yourself ahead of your requirements will let your light shine.

5 Reasons Why Line of Businesses is Adopting Data Science?

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