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Business intelligence is essential to the business, helping companies make informed and effective decisions. Regardless of the activity field of the company, business analytics is its integral component. In the healthcare and pharmaceutical industries, analytics is critical to maintaining a company’s competitive position in the market. Medical and pharmaceutical companies own a huge data amount that requires proper storage, processing and analysis. This, in turn, allows to see real information from patients, regulators, competitors, etc. The main business analytics goal in this area is to empower decision-making, develop and implement innovations designed to save lives.

How exactly business analytics helps pharmaceutical and healthcare companies:

• Minimization of research and development costs

At the moment, there is a rapid increase in the cost of launching a new medicine. Also, patents on already existing and in-demand medicines are expiring. It becomes relevant to accelerate the process of new medicines development. In this case, analytics will allow to get the most out of large data sets, publications, scientific information, and also allow to create forecasts and make decisions;

• Improving the design and quality of clinical trial results

The use of big data technology in the healthcare and pharmaceutical industries helps reduce costs and increase efficiency. This is possible due to the increased speed of clinical trials, analysis and determination of a large number of data points (historical data, patient monitoring data, demographic data, etc.). In turn, a qualitative study of the results of clinical trials provides an opportunity to improve the efficiency of diagnosing diseases;

• Precision medicine

The modern world is made up of data. This leads to the complexity of their processing. Big data analytics helps solve this problem by combining data from various sources (medical records, medical sensors, genome sequencing, etc.). This allows to identify patterns and create medicines for the patient based on his individual needs;

• Providing information to improve marketing strategy and sales

High-quality work with data contributes to a better market understanding, to analyze the work of sales representatives, to analyze marketing channels and make decisions based on this data. Healthcare and pharmaceutical data is growing exponentially. In this situation, it is important to have modern technologies for processing and analyzing data, as well as predicting future trends using historical trends and data.

Each company has its own requests and needs that need to be covered with the help of data. However, there are basic requirements for an effective result of working with data:

1. Data structuring

Increasing efficiency is possible with the help of the correct data organization, management and storage. In healthcare and pharmaceuticals data is used for any purpose: evaluating medicines, future use, market potential, funding clinical trials, etc. Data structuring provides a quality process for organizing, processing, extracting and storing data for effective work with them.

2. Data collection

Algorithms and modeling techniques help to identify data patterns and interrelation. This, in turn, allows to make more accurate forecasts in research, development, marketing, clinical trials, etc. The use of clustering, associative segmentation and data classification tools improves the quality of medicines development and delivery methods.

3. Artificial Intelligence and machine learning

These tools are used to manage a huge data amount. Pharmaceutical and healthcare companies are using AI and machine learning to find medicines more easily.

4. Visualization

Better perception and understanding of data, trends and patterns, information is possible with a graphical format. Data visualization helps analysts and clinicians identify patterns and interrelatoin and make informed decisions quickly.

Of course, working with data requires certain skills and training. At the moment, there are many online portals that offer tutorials. However, in order to choose a program, it is important to understand the data that the company owns, its needs and goals, as well as the tasks that employees must solve with the help of data.