Business and Technology News
Data Science Impact in Business
09 Mar, 2024
- How Data Science will Impact Future of Businesses?
- Impact of data science in business. Adding data science to your business practices can make a marked difference in productivity, decision-making, and product development. It can help you minimize or eradicate the risk of fraud and error, increase efficiency, and provide better customer service.
- With more than 6 billion (and counting) devices connected to the internet, approximately 2.5 million terabytes of data are generated every day. By the year 2020, millions of more new devices are expected to get connected, projecting around 30 million terabytes of data each day. This figure will definitely fascinate you.
- In order to help the enterprise prepare for the bright future of data science, we have outlined the following 5 key factors shaping the future of the data science industry.
- Making data actionable for data science
Poorly crafted data is one of the biggest obstacles to the success of data science. In order to accelerate data science projects and reduce failures, CDOs and CIOs must focus on improving the quality of data and providing data to teams that are relevant to the projects at hand and is actionable
Shortage of data science talent
While data science remains one of the highest growth areas for the new graduates, the need far exceeds the available supply. The solution continues to accelerate hiring, whereas, also looking at alternative means for other professionals in areas such as analytics and BI in order to accelerate the data science process and democratize data science access. This is where automation can have an impact on data science.
Accelerating “time to value”
Data science is an iterative process. It includes creating a “hypothesis” and then testing it. This backward and forward approach involves many experts — from data scientists to subject matter experts and data analysts. Enterprises — small or big — must find ways to speed up this “effort, repeat test” process and accelerate the process of data science for greater forecasting.
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