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Nowadays, absolutely everything is based on data. It doesn’t really matter if you sell shoes, run a marketing agency or produce bicycle tires. Data is essential for you. You use it all the time. Data helps you in almost everything you do. From searching on Google, through hiring new workers up to creating financial reports. It really is all about data. Check our examples of data science projects!
Data Science applications can offer various benefits. Before diving into the development process, it is essential to understand the business goals and identify areas where data can be utilized to achieve those goals, assess data availability, and determine feasibility.
At Addepto, we can guide you through the entire process, ensuring that the result is an application that delivers the most significant impact for your business. Feel free to share your challenges with us, and we will find a suitable solution to address them
Edwin
CSO & Co-Founder – Addepto
This topic is very wide, but let’s shorten it just to the essence.
Firstly, with data science, you can make better decisions. Why? Because they are made not on someone’s opinion but on a much more reliable source. Only data science and machine learning systems can analyze millions of bytes of the given data within seconds.
It is a massive simplification, but more or less it works like that: you have a problem to solve -> you input that into the data science examples-> the application analyzes all the data available -> you receive the best solution. Do you see the difference? You may have your instinct, but it can be unreliable. Data science and machine learning systems do not have this problem. They work without emotions and rush.
Secondly, the usage of data science helps in rising sales. Machine learning systems can explore historic data, make comparisons and analysis of the market and, on that basis, make recommendations of how, when, and where your product or service will sell best. What’s more, data science can help you in improving accuracy in reaching your target audience.
Data analytical systems, such as Google Analytics, deliver you accurate data about who visited your website or e-commerce, when, from where what was he or she interested in, and many more. If you have been using Google Analytics already, you know how powerful a tool it is. It helps you to suit your target audience’s needs, and that is done by modifying your advertisements, your website’s layout, or even offers too!
Using data science may cause your company to implement some changes, because with the data-based solution probably you will see some new and unexpected possibilities. But the results of implementing the data-based strategy can also be unexpectedly good!
Let’s see right now data science real-life examples in several areas. Let’s focus on 6 data science examples of such applications. We will see how data science helps in manufacturing, sales, retail, logistics, marketing, banking and more. For more information take a look at the data science consulting page.
The first data science real-life example is the manufacturing industry. Many manufacturers depend on data science to create forecasts of product demand. It helps them in optimizing supply chains and delivering orders without risk of over/under-ordering.
Data science can make a lot of savings for your manufacturing company especially in supply chain optimization. Here are some benefits of data science implementation into your company:
While we talk about optimizing the supply chain, we go straight to the second example of data science projects: it is also of huge importance in the logistics industry.
It might be interesting for you – Data Science in the mining industry
Another data science example is customer analytics in the retail industry. Let’s take a closer look at the advantages of this data science project example.
For marketers, it is very valuable to analyze user behavior on their websites. Therefore, using data science in marketing, companies can determine:
Customer Journey analysis allows you to create more and more perfect recommendation systems which on the basis of this information indicate time-specific products that customers are willing to buy. Furthermore, implementation of such systems helps stores to be closer to the customer and thus drive their business.
The banking sector is the next data science project example. And one of the biggest problems of this sector is NPL – Non-Performing Loans. These are the loans that haven’t been settled for at least 90 days. After that period loans become NPL – “endangered”. And the problem is very serious. As EBF (The European Banking Federation) informs, on average, 3.74% of all worldwide loans are NPLs. [1] How data science can help to solve this problem?
Read more about Data Science in Finance
Sales – exactly what every company is about. Sales representatives have a very tough job. Hundreds of phone calls, meetings, follow-ups, offers, and presentations. Always in a rush. Every day. But data science usage can help them as well! Consider two data science examples.
Another important data science example – predictive analytics in healthcare.The predictive model analyzes historical data, learns from it, identifies trends and then generates accurate predictions based on those tendencies. So, data science in healthcare helps hospitals to:
Find out 7 ways Data Science is revolutionizing healthcare
The last data science example is weather predictions in the agriculture sector. Nowadays, data science is changing the way farmers and agriculture professionals make decisions.
Weather has a significant impact on agricultural production, affecting crop growth, development, and productivity. Using data science in agriculture sector, farmers can get such elements of agriculture weather prediction as [2]:
There’s so much more to data science! There are tons of examples of data science applications! With this article, we barely scratched the surface! Check our data science Case Studies and read our other articles to see how data science could be implemented.
Remember – we are always here for you. Just drop us a line or give us a call! We will gladly talk with you about implementing data science into your business!
Data science is the field of study that involves extracting insights and knowledge from data through various processes and algorithms. It is essential for businesses because it allows them to make informed decisions based on data-driven analysis, leading to improved efficiency, productivity, and competitive advantage.
Data science enables businesses to make better decisions by analyzing vast amounts of data quickly and accurately. Instead of relying on intuition or opinions, decisions are based on empirical evidence and statistical analysis, leading to more reliable outcomes.
Data science can benefit industries in various ways. For instance:
Data science plays a crucial role in sales and marketing by providing insights into customer behavior, preferences, and trends. It helps in identifying potential leads, personalizing marketing campaigns, optimizing pricing strategies, and improving sales forecasting.
Yes, data science can be used to predict future trends and outcomes by analyzing historical data patterns and extrapolating them to make forecasts. Predictive analytics techniques, such as machine learning algorithms, are commonly employed for this purpose.
Businesses can get started with implementing data science by:
Some common challenges businesses may face when adopting data science include:
The article is the updated version of the publication from Aug 19, 2021.
References
[1] Ebg.eu. Banking in Europe: EBF publishes 2018 Facts & Figures. URL: https://www.ebf.eu/ebf-media-centre/banking-in-europe-ebf-publishes-2018-facts-figures/. Accessed Aug 20, 2021.
[2] Data-flair.training. Data Science in Agriculture – Advancing Together & Benefiting Farmers. URL: https://data-flair.training/blogs/data-science-in-agriculture/. Accessed Aug 20, 2021.
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