Staying relevant and keeping up with the competition are probably the biggest challenges for global businesses today. The competition has forced enterprises to think out of the box to stay the competitors afloat. It has given rise to the latest trends in the business world, including business analytics data science. It is a new concept for many people out there, so let’s first explain what business analytics data science is all about.
What is Business Analytics Data Science?
Data science is all about extracting value or knowledge from data or numbers. Businesses can use this knowledge to improve their business operations or expand their reach in the market. Data provides experts with the answers to different questions, and hard-facts support these answers. Businesses apply data science protocols to gain control over different metrics like operations, growth strategies, customer engagement, etc. With the passage of time, an increased number of enterprises are dedicating resources into analytics to dig out crucial information about their business’s health. It means is that if you have a business analytics degree, you can ensure a fantastic career in analytics and data science. The truth of the matter is that only crunching numbers or data doesn’t solve businesses’ problems, which is why data scientists are always in high demand in the job market.
This article paints a clear picture of how data science is the next frontier for business competitiveness.
Different Uses of Data Science
As more businesses and industries open their arms to data science, we can already see its use is gaining popularity. Some of the standard services in today’s enterprises are intuitive search in search technology, weather forecast, customer behavior, fraud detection in banks, oil and gas sources prediction, evidence-based medicines, and sentiment analysis from social media traffic. You can already feel the difference that data science impacts retail, e-commerce, financial services, consumer services and products, telecommunications, pharmaceuticals, insurance, high-tech, and manufacturing.
Common Ways Data Science is Deployed Today
As mentioned earlier, more businesses and enterprises are embracing data science in their business operations. The usage of data science primarily relies on the size of the organization. The larger enterprises generally like to hire in-house teams of data scientists and analysts. Such large corporations have to cope with an immense amount of data. Hiring in-house teams allow them to make better decisions that are backed by robust data. Even though having employed a massive team of data scientists is not always the best idea, larger enterprises like to hire and keep a decent amount of resources to get the job done. Secondly, some corporations purchase a Commercial-Off-The-Shelf (COTS) to comply with standard requirements. Thirdly, many medium and large enterprises also like to hire a data science company to focus on the core business. The third option is the most common one because it provides flexibility to the enterprises.
Case Studies
Procter & Gamble (P&G) and Amazon are two prime examples of enterprises that have benefited from data science. P&G has gone to the extent of institutionalizing the data and design thinking approach, which has allowed the company to deal with over $20 billion brands in their products base. Similarly, Amazon has thrived brilliantly by implementing data science, allowing the company to understand customer behavior and preference better. The approach has helped Amazon to become one of the largest product sellers (more than 20 million products) from the days of selling only books online in 1996.
Many other examples of smaller organizations have benefited drastically from data science and joined the elite league of big players in the last few years. Some of the most significant benefits for these companies were identifying new growth areas and designing innovative products and services. Furthermore, cutting down business expenses, improving productivity and profitability, getting rid of obsolete practices and technologies, rectifying challenges in the supply chain, and lots more.
What Lies Ahead?
The evolution of data science is quickly turning into a revolution for businesses across the globe. After their successful use by larger enterprises, smaller companies have also started making it an essential part of their business operations. Decision-makers believe that ignoring data science could be the most significant risk for their business now. The rise of smartphones and smart home technologies has further augmented the importance of data science. As humans generate new data exabytes every day, companies are more interested in studying the data through social media streams and other streams to align their business models accordingly.
Conclusion
Considering the above trends, we can safely assume that the business world will have increased data science usage in the coming years. The businesses that are yet to join the bandwagon must revisit their business growth strategies and ideologies. It is all about leading and not following when it comes to implementing data science in business operations. So, if you want to stay relevant in the new-age business world, relying on data science will expand your reach.
Danis Woods in Businessman, investment banker and stock exchange traders. On the same time he loves writing financial blogs to shed lights on different aspects that new and existing businessman are not aware of.
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