The reason behind the recent popularity and adoption of Big Data analysis by large corporations and SMEs is to gain competitive advantage and offer unique services for every client. However, many companies are still not clear what Big Data is all about and what advantages this analysis option has for their business model. Therefore, today we take a look at various industries that are already using Big Data analytics.
The economic benefits of Big Data analytics
Big Data Analytics has a big goal to help companies make better business decisions with data. This goal is achieved through new hardware and software-based process structure in large, yet unstructured data. In this way, the large amount of data available in a company is made understandable thanks to business intelligence consultants and used productively.
According to surveys, big data is primarily used to get to know the customer better, to evaluate internal information in a more targeted manner, and to build a better data landscape.
Industries for which big data analytics have great advantages
1. Sales & Marketing
Big data analysis is used most often in marketing to reduce costs. This can be achieved through a tailor-made range of products and services combined with individual marketing measures. All known customer information (e.g., demographics, location, transactions, and interests) is evaluated. On this basis, patterns can be derived when making purchasing decisions.
These are used to create and target new customer segments. Cross-selling, based on detailed customer information, offers further benefits. At the same time, however, customers can also be identified who are dissatisfied and could possibly migrate. A timely response (e.g., through discounts) can counteract this situation.
As production is getting smarter, it's not surprising that big data plays a big role here too. The numerous processes are monitored by sensors and generate large amounts of data. With this data, preventive maintenance can be ensured, and production delays or downtimes prevented.
3. Distribution and logistics
Sensors are also increasingly being used in the supply chain, for example, to measure fuel consumption or record position data and the condition of wearing parts. The structuring of this data means that costs can be sustainably minimized by planning transports in a timely manner, changing routes and loads, or minimizing downtimes and maintenance costs.
4. Marketing and sales
Data analysis can greatly improve the relationship with your customers. Because you know the needs of your customers better and can even address each individual customer directly with personalized offers.
5. Finances and Insurance
Big data analytics can be used to make reliable predictions or risk calculations in the financial industry. In the investment business, for example, it is, therefore, possible to react more quickly to market developments or falling prices.
Insurance fraud, large or small, causes millions of dollars in damage annually. Predictive analytics and other big data methods can improve fraud detection and generally adapt insurance services.
6. Health care
Big data analytics also enable cheaper health care. For example, complex DNA analyzes can be carried out more quickly in order to predict the occurrence of diseases and to proactively propose countermeasures. Data analysis even makes it possible to develop group-specific drugs for people with very similar DNA structures.
7. Science and research
Data analysis can also lead to greater efficiency in science and research, for example, by evaluating the data of an experiment. 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 data analytics, but unfortunately for humans.
With advancing digitization and the associated amount of data collected, the importance and relevance of big data will continue to increase in the future. Big data is only of use to companies if the information can be properly analyzed. The possibilities seem limitless, and companies can gain a great competitive advantage by correctly assessing markets, customers, and their changes and responding to them with appropriate measures.
However, the complexity and complexity of big data analytics must not be overlooked. Nowadays, companies need to have the advanced technical knowledge and a large budget to do the right analysis.
And yet: There is always criticism and skepticism, as the data quality is often insufficient, and data protection problems are also discussed. So in the future, it will be important to invest in the development of improved software and to make the topic accessible to small and medium-sized companies as well.