Uses of Data Science in Different Industries

 

Uses of Data Science in Different Industries

 Within Business Intelligence, the role of Data Science is starting to gain ground. Data Science is the collection of all available data, which coordinates with each other and ensures that it can then be visualized. It, therefore, differs from the traditional BI, because it is much broader and data come together that may not have the same structure at all.

 Big data comes first for many companies

 New technologies such as the Internet of Things, artificial intelligence, or blockchains have an ever greater impact on the competitiveness of companies. This is the result of a representative survey of managers in 604 Indian companies with 20 or more employees, which the digital association Bitkom carried out in 2020. As a key result data science comes first among the planned or already implemented technologies up to 57 percent.

 Big data - large amounts of data - is obtained from almost every business context and is increasingly being used strategically by companies. The amount of data is usually large, unstructured, and complex. This data pool contains e.g. B. Data from customers and employees, such as click rates or social media activities, records from monitoring systems, and data from manufacturing processes of networked production systems.

 Data Science is more effective, smarter, and faster through larger amounts of data

 Raw data becomes information. Knowledge arises from the information. Knowledge from data analysis creates value for companies. The goal: to be able to record, harmonize, structure, and ultimately analyze large amounts of data (with high data quality) from many different sources. In the course of digitization, almost unlimited storage space, cloud computing as “infrastructure” and faster computing speeds offer the ideal breeding ground for profitable evaluations. Data has therefore become an important part of business capital. In particular, the systematic approach in the field of data science offers companies a wide range of analysis options. For example, unknown patterns are searched for in large databases to open up new opportunities for business activities. In addition, a multidimensional perspective on one's own business model should be made possible. Data, therefore, form the basis for finding knowledge. These discoveries extend into the future of a company or entire industries. The systematically elaborated forecasts of modern software solutions, such as so-called “prescriptive analyzes”, are only used by 15 percent of companies in India. And Almost 64% of people are includes existing employees under another stream and newly entire students are searching for the best data science course in Hyderabad to build career very effectively.

 Is it possible to design innovative products, services, or business processes for the future in the past? Are future challenges and opportunities foreseeable? That sounds like a promising solution. However, so far only a few companies in India have used the latest analysis tools, for example for customer data. Possible losses inefficiency and a lack of customer orientation can be the result. This leaves many opportunities unused to use data in the company to advantage. For innovative product development and targeted marketing measures, however, customer data can be valuable for a high degree of customer-centricity.

 How companies of different sizes use data science

 This section covers the following segments: small, medium, large, and very large companies worldwide and in India. The number of employees in a company serves as the basis for this type of classification:

      ●        Small businesses (1-100 employees).

      ●        Medium-sized companies (101-1,000 employees).

●        Large companies (1,001-5,000 employees).

●        Very large companies (more than 5,000 employees).

 Benefits of data science for different Industries

 Data science has applications in all sectors and organizations where significant amounts of data are present. Because this is the case in almost every organization these days, data science is relevant for everyone. This sounds a bit silly, but it really is.

It is undeniable that Big Data analytics has a major impact on our economy. Some industries have been completely transformed by the widespread adoption of this technology. Here, we describe many industries that have been completely changed by Data Science.

 ●        Sports Industry

 Data science has found its way into the training field in most top sports. In different football teams, the movements of players on the field are analyzed with advanced pattern recognition software. With this data, training and competition strategies can be optimized. Within the NFL, players are observed by sensors in their shoulder pads. And it was an analysis of rowing patterns that earned the British Olympic gold. Analyzing images is as old as the video camera itself, but since the advent of Big Data analytics, coaches can analyze individual movements on a large scale and compare them with historical data and external factors. This has changed training and competition preparation forever. 

 ●        Hotel industry

 The hotel industry is also making good use of this technology. It is the way to measure and analyze customer behavior and customer satisfaction on a large scale. In addition, they have more insight than ever into market movements and can target their marketing much more specifically. Think of hotels with special honeymoon packages that only advertise this to people who are (just) engaged using Facebook. Or hotels that use the many data that Google collects about consumers. Via Google Ads, they can advertise when consumers “not from place X” show interest in “place X” and are therefore probably planning a trip.

 ●        Government and the public sector

 Different cities are becoming smarter by collecting information about residents and visitors on a large scale. For example, there are municipalities that have streamlined their recycling to ensure that an unnecessary number of half-full cars do not have to drive through the municipality. Bus lines are also being optimized based on usage and stops. Various governments also use Data science to regulate traffic. The more data that is collected, the better the traffic flows can be regulated. Think of opening and closing rush-hour lanes, planning for widening motorways, and opportunities to optimize public transport even more.

 ●        Agricultural sector

  The agricultural sector also continues to innovate and benefits greatly from the Big Data revolution. For example, the right time to feed, fertilize, plant, harvest, inseminate, and milk is now all measured and analyzed to ensure that the available resources are used efficiently. Matters such as the weather and the market price of products are also included in various analyzes. A pest may not be controlled with data, and a bad harvest cannot be completely prevented. But by using Big Data in the right way, farmers now have insights that they did not have in the past. This makes it possible to respond more quickly to these risk factors and reduce crop loss due to weather conditions or vermin.

 ●        Financial sector

 Major steps have also been taken within the financial sector by Big Data analytics. Consider, for example, the KYC / CDD working method in fraud departments. Many accounts can be analyzed in a short time by means of analytics and machine learning. Suspicious behavior is then tagged, after which employees can zoom in on the case. By subsequently also feeding the results of these studies back to the algorithm, the systems become smarter and more work can be done with fewer people. We previously wrote about predicting bitcoin prices through Big Data and machine learning in data science. But this way of forecasting can of course also be used outside of bitcoin. This way, trends can be recognized at an early stage and, for example, stock traders have more knowledge to optimally serve their portfolios.

 ●        Retail

 Within retail, both e-commerce and traditional stores benefit from Data science. Walking patterns and average basket value are analyzed in physical stores. By experimenting with supply, offers and impulse products, an optimal store layout is then realized. In addition, individual purchasing behavior is also measured by, among other things, loyalty programs. With this knowledge, retailers can purchase the right products at the right time and make personalized offers to different target groups within their customer base.

 Data science may have an even greater impact in e-commerce. Data is the driving factor in online marketing. Who sees which version of the website and who sees which ad on social media is all based on results from data analysis. The more data, the more conversions marketers can get from their ads.

 Both also discover interesting patterns through Big Data. For example, unexpected products that are often purchased simultaneously can reveal new cross-selling opportunities. And by also collecting external information about their customers, they discover new characteristics of their ideal customers. This in turn opens doors to new forms of advertising and personalized offers.

 ●        Transport

In addition to the government using Data science to improve the infrastructure, transport companies also use this to optimize their time on the road. The routes and resources are optimized through large-scale data analysis. For example, routes can now be adjusted in real-time based on traffic, historical reception ratios, and packet order.

 ●        Healthcare

 Medicine data science and analytics also enables cheaper healthcare. For example, complex DNA analysis can be carried out more quickly to predict the occurrence of diseases and proactively suggest countermeasures. The data analysis even makes it possible to develop group-specific drugs for people with very similar DNA structures.

 ●        Science and Research

 In science and research, too, data science can lead to greater efficiency, for example by evaluating the data from an experiment. For example, the Geneva research center CERN generated 40 terabytes of data per second during an experiment with a particle accelerator. This amount of data is not a problem for big data analytics, but unfortunately, it is for us humans.

 ●        Product development and production

 Data science can already bring a decisive advantage during development. For example, the evaluation of social media channels or customer ratings can reveal social trends and market gaps at an early stage. As production is getting smarter and smarter, it's not surprising that big data also plays a major role here. The numerous processes are monitored by sensors and generate large amounts of data. This data can be used to ensure preventive maintenance and prevent production delays or downtimes.

 ●        Distribution and logistics

 Sensors are also increasingly being used in the supply chain, for example to measure fuel consumption or to record the position data and the condition of wear parts. The structuring of this data means that costs can be sustainably minimized by planning transports promptly, changing routes and loads, or minimizing downtimes and maintenance costs.

 ●        Marketing and Sales

 Through data science, you can greatly improve the relationship with your customer. Because you know the needs of your customers more precisely and can even address each individual customer directly with personalized offers.

Conclusion - Discover your opportunities

 With this blog, we have only discussed a fraction of the impact of Data Science. It is the force behind innovations in various industries and the backbone of emerging technologies and methods. Do you want to discover the opportunities within your organization, or are you looking for a good data scientist? Please contact us for a no-obligation consultation by filling in the contact form below. We will contact you as soon as possible after receiving this form to discuss the possibilities.